Loïc Tudesque

Mathieu Chevalier

Pengbun Ngor

Ratha Chea

Ratha Sor

Kong Heng

Bunyeth Chan

Chuanbo Guo

Mingli Lin

Tongtong Fang

Mrs Sovan

Ratha Seng
email: ratha.seng@gmail.com

Robert S Pomeroy

Sovan Lek

Louise Teh
email: l.teh@oceans.ubc.ca

Natachia Bond

Krishna Kc

Evan Fraser

Ra- Shid Sumaila

CHAPTER III: LIVELIHOOD DYNAMICS IN THE DEVELOP-ING WORLD: EXPERIENCE FROM POST-CONFLICT CAMBO-DIA

sharing insights, discussion and support at different points

RESUME

L'objectif général de ce travail était d'évaluer les stratégies des moyens de subsistance dans le lac Tonle Sap en rapport avec divers facteurs de changement. Plus précisément, l'étude visait à étudier les variations et les déterminants des moyens de subsistance (spatial et temporal), ainsi que les impacts des futurs changements et des communautés de pêcherie (CFis) dans les plaines inondables de Tonle Sap. En utilisant les approches multivariées, j'ai pu mettre en évidence les résultats suivants :

 Les différentes caractéristiques écologiques déterminent les différentes stratégies des moyens de subsistance et les ressources environnementales sont indispensables pour la période post-conflit des pays comme le Cambodge ;

 Les divers facteurs humains, naturels et économiques, sociaux et physiques ont influencé le choix et le revenu des ménages ; parmi lesquels, la possession de terrain était le plus important;

 La perte de net revenu est attendue dans tous les futurs scenarios de changement, particulièrement avec ceux qui dépendent uniquement un moyen de subsistance, subi une perte en moyenne de 18% dans tous les scénarios, comparativement à 9% pour le groupe des multi-moyens de subsistance ;  La taille idéale de la zone communautaire est de 2 310 hectares et l'impact positif des CFis peut être réalisé en améliorant la planification, le processus opérationnel et le mécanisme de résolution des conflits, également qu'en développant et renforçant des réseaux et la conformité des règles.

Les résultats suggèrent que les moyens de subsistance sont spécifiques au contexte et le choix des stratégies des ménages est associé à une gamme de facteurs socio-écologiques. Nous devons éviter une prescription unique pour aborder les problèmes des moyens de subsistance dans le Tonle Sap. Effectivement, les implications politiques pour améliorer la participation aux moyens de subsistance ainsi que pour maximiser les avantages économiques et sociaux à long terme pour les ménages devraient accorder une attention particulière aux ménages pauvres en ressources. Par conséquent, l'augmentation de la richesse et des biens du ménage, ainsi que l'établissement des programmes efficaces de conservation des ressources améliorent effectivement la capacité d'adaptation des ménages en réponse aux changements inattendus et également contribuent à renforcer et soutenir les organisations des CFis.

MOTS CLÉS : Moyens de subsistance, déterminants, impact, communauté de pêcherie, Tonlé

Sap

ABSTRACT

The overall goal of this research was to assess the livelihood strategies in the Tonle Sap in the face of various drivers of change around the lake. Specifically, the study intended to investigate livelihood variations and determinants (both spatial and temporal), and the impact of future scenario changes and of the Community Fisheries (CFis) in the Tonle Sap's floodplain. By using multivariate approach, I am able to highlight the following findings:

-different ecological characteristics influencing livelihood strategies and the environmental resources are imperative in post-conflict Cambodia; -various human, natural and economic, social, and physical capitals have influenced household's choice and income. Land was the most significant; -net income loss is expected for under all future scenarios, with those engaged in single livelihoods experiencing an average loss of 18% across all scenarios compared to 9% for the multi-livelihood group; -an ideal size of community area is 2,310 hectares and the positive impact of CFis can be achieved by improving planning, operational process and conflict resolution mechanism, developing networks and reinforcing rule compliance.

The findings suggest that livelihood is context specific and the choice of household's strategies is associated with a range of socio and ecological factors and we should avoid a one-size-fit prescription to tackle livelihood problems in the Tonle Sap. Policy implications to improve livelihood participation and maximize the long-term economic and social benefits for household should consider special attention to resource poor households, increase household's wealth and assets, design and implement effective resource conservation programs, improve households' adaptive capacity in response to unexpected changes and continue strengthening and supporting the CFi organizations.

KEY WORDS: Livelihoods, determinants, impact, community fisheries, Tonle Sap ACKNOWLEDGMENT First and foremost, I would like to thank my thesis directors: Prof. Sovan LEK, Université Paul Sabatier -Toulouse III, France, and Prof. Robert POMEROY, University of Connecticut. USA, for their guidance, support, patience during the period of my PhD. Prof. LEK and Prof. POME-ROY have provided me exceptional scientific supports from the very beginning till the end of my PhD journey and are always ready to assist in whatever academic problems I am facing. Also, I have a great privilege to be recruited to involve in the Belmont Forum-funded Tonle Sap Climate Change Project by Prof. Sovan LEK, where I have opportunity to meet all amazing researchers, scientists and professors from the three continents (Asia, Europe and America), including my codirector Prof. Robert POMEROY. Furthermore, I would like to take this opportunity to thank H.E

LIST OF TABLES

LIST OF FIGURES

Status and importance of inland small-scale fisheries

Fish stocks, both marine and inland, have either degraded or collapsed from their historical peaks [START_REF] Allan | Overfishing of Inland Waters[END_REF][START_REF] Pauly | Towards sustainability in world fisheries[END_REF]. The main threats to biodiversity associate with either overfishing or being fished at their biological limit, putting them at risk with increasing human and environmental pressures. Overfishing has been natural resource concerns in both industrialized and developing world. It is considered to precede all other human disturbances in contributing to the resource extinction [START_REF] Jackson | Historical overfishing and the recent collapse of coastal ecosystems[END_REF]. In Southeast Asian countries, overfishing leads to several negative impacts, such as decreased employment opportunities and revenues, food security, poverty, social stability and conflicts [START_REF] Salayo | Managing excess capacity in small-scale fisheries: Perspectives from stakeholders in three Southeast Asian countries[END_REF]. From the governance perspective, it is being compromised by the failure of the centralized governance system of resource [START_REF] Acheson | Institutional Failure in Resource Management[END_REF][START_REF] Pomeroy | Community-based and co-management institutions for sustainable coastal fisheries management in Southeast Asia[END_REF] which drove an increased recognition of community role in resource management.

The total capture production from inland waters, exclusive of aquaculture, is 11.9 million metric tons in 2014, of which Asia made up the largest share of the world total catch. China accounted for 19.3%, followed by Myanmar (11.6%), India (10.9%), Bangladesh (8.4%), Cambodia (4.2%), Uganda (3.9%), Indonesia (3.5%), and Nigeria (3%), making up almost 65% of the world total inland production. However, the actual catch size could be much greater than this figure or even higher than the marine catches (FAO, 2016). The inland fisheries are generally small-scale and subsistence in nature, making it difficult to properly value. The contributions of inland waters are usually underestimated.

Fishing and fishery products play important role for livelihoods and food security especially among low income families in developing countries where employment op-tions are limited. Small-scale commercial and subsistence fishing are often the last resort choice of employment of households where lucrative labor opportunities cannot be found [START_REF] Kura | Fishing for Answers: Making Sense of the Global Fish Crisis[END_REF]. Additionally, the fish contribution, in 2013, to total animal protein intake was 17% for global average and it constituted more than 50% in developing nations like some small-island states, Bangladesh, Cambodia, Ghana, Indonesia, Sierra Leone and Sri Lanka (FAO, 2016). Globally, the annual fish consumption per capita was 20 kg and the figure was projected to increase (FAO, 2016).

In the Lower Mekong Basin, it was estimated up to 52 kg [START_REF] Hortle | Consumption and the yield of fish and other aquatic animals from the Lower Mekong Basin[END_REF]. Overfishing, habitat loss and environmental degradation or the combination pose serious threats to freshwater fisheries, its biodiversity and those whose livelihoods primarily depend on the resources. Freshwater ecosystems and their associated biological resources are, on average, more threatened than those of the marine [START_REF] Ricciardi | Extinction rates of North American freshwater fauna[END_REF]. The under-appreciation of the importance of freshwater fisheries put this sector (i.e. smallscale fisheries) even at higher risk.

The Tonle Sap's fisheries and livelihoods

According to [START_REF] Yu | Rice production response in Cambodia[END_REF], Cambodia is divided into four main agro-ecological zones, namely Plateau/Mountain, Plain, Coast, and Tonle Sap. The Plateau/Mountain zone includes the northeast Cambodia and Kampong Speu province in southwest bordering the coastal provinces is dense in forests and with low population density. The coastal zone consists of a very small portion of the country located in the Southwest.

Crop cultivation, mostly rice, is mainly in the Northwest-Southeast corridor, known for a high population density. Thus, the northwest areas bordering Thailand around the Tonle Sap zone and southeast areas bordering Vietnam in the Plain zone are the main producers of rice. Dry season rice is mostly grown in the Plain zone, accounting for 70% of total land area of the country.

The Tonle Sap Lake, the largest lake in Southeast Asia and one of the most productive freshwater fisheries in the world, covers about 5 to 8 percent of Cambodia's total land area (MRC, 2003). Connected to the Mekong River by the 120 km long Tonle Sap River, the Tonle Sap Lake's surface area annually fluctuates from 2,500km 2 to over 15,000km 2 driven by seasonal flood pulse from the Mekong River accounting for 53.5 percent of total water inflows into the lake system (M. [START_REF] Kummu | Water balance analysis for the Tonle Sap Lake-floodplain system[END_REF].

The rice fields, rivers and forests have supported the livelihoods of Cambodian population for centuries. Local people depend on the traditional ways of living from rice farming, fishing and extracting forest resources, mainly for subsistence purposes.

Households become more or less diversified (i.e. crops, fishery, forestry) depending on the degree of interactions of the adjoining ecosystems.

In Cambodia, fish and fishing activities have been primary sources of nutrition and income. Fish from the Tonle Sap provide an essential source of protein and micronutrients critical to the health of families in a country still plagued by high rates of childhood malnutrition, as well as livelihoods. Fish supplies up to 80% of all animal protein in the diet [START_REF] Hortle | Consumption and the yield of fish and other aquatic animals from the Lower Mekong Basin[END_REF], of which the majority are from the Tonle Sap Lake [START_REF] Baran | Fish resources in Cambodia (2001-2011). In Atlas of Cambodia -Maps on socioeconomic development and environment[END_REF]. The annual fish consumption per capita is as high as 71 kg around the Tonle Sap's floodplain in the high-yield fishing areas [START_REF] Ahmed | Socioeconomic Assesment of Freshwater Capture Fisheries in Cambodia[END_REF].

Moreover, income from capture fisheries and other aquaculture contributes about 10% of Cambodia's Gross Domestic Products (GDP) [START_REF] Baran | Climate change and fisheries: vulnerability and adaptation in Cambodia[END_REF].

The lake provides essential ecosystem services and supports livelihoods of at least 2 million people as well as a large number of small-scale fishers. Households in the vicinity of Tonle Sap Lake primarily engage in small-scale artisanal and subsistence fishing, with supplemental income from agriculture, raising livestock, aquaculture, offfarm work, and remittances (Bond, 2015). Yet, many of the poorest household depend on one livelihood, which is generally fishing [START_REF] Nuorteva | Water, livelihoods and climate change adaptation in the tonle sap lake area, Cambodia: Learning from the past to understand the future[END_REF]. In particular, floating villages on the Lake are heavily dependent on fisheries resources, and their limited access to land resources, education, and livelihood options make them especially vulnerable to ecological change [START_REF] Nuorteva | Water, livelihoods and climate change adaptation in the tonle sap lake area, Cambodia: Learning from the past to understand the future[END_REF]. Moreover, almost 70% of floating households on Tonle Sap Lake were classified as being low-wealth (Bond, 2015), where wealth was an index measuring household location, diet diversity, and livelihood strategy. In contrast, richer households were typically not as reliant on fishing as their main income source (Bond, 2015). While inhabitants around the Lake have adapted to seasonal changes of the lake, they have poor capacity to react to irregular environmental events [START_REF] Nuorteva | Water, livelihoods and climate change adaptation in the tonle sap lake area, Cambodia: Learning from the past to understand the future[END_REF]. Lower income Tonle Sap fishers, therefore, exemplify a vulnerable population.

Problems 1.3.1 Livelihoods, natural resources and post-conflict building

A livelihood comprises "the capabilities, assets and activities required for a means of living"; a sustainable livelihood is when it "can cope with and recover from stress and shocks, maintain or enhance its capabilities and assets, without undermining the natural resource base" [START_REF] Scoones | Sustainable Rural Livelihoods: A Framework for Analysis[END_REF]. In developing countries and those affected by conflicts, a significant percentage of population relies on land, water, forests and other natural resources. In conflict-affected countries, it is estimated that the dependency on agriculture and natural resources is around 60% to 80% [START_REF] Bruch | Human Conflict: Targeting Natural Resources[END_REF]. The armed conflicts usually destroy the livelihood systems and house-holds are forced to adopt coping strategies which are sometimes environmentally unsustainable. Not only does the conflict damage the livelihood bases (i.e. household capabilities and assets, natural resources and infrastructure), but it also undermines the formal institutions especially the tenure systems governing access to resources which sometimes turn into conflicts or violence. The weakened formal institutions results in poor enforcement of rules, particularly when dealing with environmental resources [START_REF] Clements | Payments for biodiversity conservation in the context of weak institutions: Comparison of three programs from Cambodia[END_REF][START_REF] Travers | Incentives for cooperation: The effects of institutional controls on common pool resource extraction in Cambodia[END_REF]).

Moreover, the potential sources of conflicts are associated with resource access and ownership [START_REF] Andre | Land relations under unbearable stress: Rwanda caught in the Malthusian trap[END_REF]. In some cases, the conflict is driven by social groups who work together to take advantage of the weakened institutions and of peace by further devastating the economy and local livelihoods through unsustainable and illegal resource extractions [START_REF] Oglethorpe | Overview C: Conservations in times of war[END_REF].

On the pathway of reconstruction, war-torn countries may adopt economic policies that emphasize accelerating rapid economic growth, resource extraction and attracting foreign investments by neglecting long-term livelihood and ecological purposes of the natural resources. For instance, Cambodia's recovery policies have resulted in rapid structural transformation. Cambodia has been highly depending on subsistence agriculture, dominated by rice, and its allied activities such as forestry and fishery [START_REF] Acharya | Off-farm and Non-farm Employment: A Perspective on Job Creation in Cambodia[END_REF]. However, the share of agriculture to GDP has been on the decline from over 50% to just about 30% over the past two decades and is offset by increasing role of services and industry which is principally dominated by tourism, garments and construction (World Bank, 2015a).

Meanwhile, arable land per capita in Cambodia has continued decreasing since 1990s (World Bank, 2016). Cambodia prioritizes the allocation of arable land to business tycoons and foreign investors in the form of Economic Land Concessions over the landless and land-poor families under the Social Land Concessions program [START_REF] Neef | The Politics and Ethics of Land Concessions in Rural Cambodia[END_REF][START_REF] Vrieze | Carving Up Cambodia: One concession at a time[END_REF]. The average farmland is one and a haft hectares; 48% of rural households own land of less than one hectare, and 20% of rural population has no land access (World Bank, 2006, 2015a). With an average household size of five, the majority of the rural population faces a high level of vulnerability.

While poverty rate has declined sharply from the early 1990s of more than 50 to 20 percent in 2011, one-fifth Cambodians are living close to the poverty line and are at risk of vulnerability due to simple shocks (World Bank, 2014). In Cambodia, the highest poverty incidence is centered in areas where households are more primarily dependent on agriculture and natural resources such as Tonle Sap, the plateau and mountain areas [START_REF] Varis | Poverty, economic growth, deprivation, and water: the cases of Cambodia and Vietnam[END_REF]World Bank, 2006, 2014). To ensure economic viability and to cope with change, households in developing countries and in Cambodia in particular pursue a variety of livelihood activities like crops, livestock, fishing, forestry, and nonfarm [START_REF] Babulo | The economic contribution of forest resource use to rural livelihoods in Tigray, Northern Ethiopia[END_REF][START_REF] Ellis | The determinants of rural livelihood diversification in developing countries[END_REF][START_REF] Nielsen | Quantifying rural livelihood strategies in developing countries using an activity choice approach[END_REF][START_REF] Soltani | Poverty, sustainability, and household livelihood strategies in Zagros, Iran[END_REF]. Households decide to diversify their livelihood strategies depending on varying socio-economic factors [START_REF] Eneyew | Determinants of livelihood strategies in Wolaita[END_REF][START_REF] Tesfaye | Livelihood strategies and the role of forest income in participatory-managed forests of Dodola area in the bale highlands, southern Ethiopia[END_REF].

The poorest households generally rely on a single strategy, for example fishing, and have limited access to land resources, education, and livelihood options, making them especially vulnerable to ecological change [START_REF] Nuorteva | Water, livelihoods and climate change adaptation in the tonle sap lake area, Cambodia: Learning from the past to understand the future[END_REF]. For instance, even though inhabitants around the Tonle Sap Lake have adapted their life and livelihoods to the annual fluctuations of the natural resources of the lake, they have poor capacity to react to irregular environmental events [START_REF] Nuorteva | Water, livelihoods and climate change adaptation in the tonle sap lake area, Cambodia: Learning from the past to understand the future[END_REF]. Lower income Tonle Sap fishers, therefore, exemplify a vulnerable population.

Livelihood vulnerability

Within the global change literature, livelihood vulnerability is seen as being dependent on peoples' exposure (likelihood of being impacted), sensitivity (dependence on natural resources), and capacity to adapt to likely impacts [START_REF] Adger | Vulnerability[END_REF]. These three dimensions collectively determine the extent to which peoples' livelihoods are vulnerable to climate and socio-economic change. Cambodia is classified as being highly vulnerable to the effects of climate change on fisheries [START_REF] Allison | Vulnerability of national economies to the impacts of climate change on fisheries[END_REF]. However, poverty, marginalisation, and lack of alternative livelihoods impede fishing communities' ability to cope with changes in fishery productivity [START_REF] Baran | Climate change and fisheries: vulnerability and adaptation in Cambodia[END_REF].

Despite the relative abundance of the Tonle Sap's natural resources, the area remains one of the poorest in the country. The inhabitants of the Tonle Sap are also highly vulnerable especially related to the changes in the Mekong River and the lake itself. The upstream dam development of the Mekong River and its tributaries, notably the large hydropwer projects in Mekong countries, are threathening the ecosystem and the livelihoods of the Tonle Sap's flood plain as it causes the rise of dry-season water level [START_REF] Keskinen | The Tonle Sap Lake, Cambodia: waterrelated conflicts with abundance of water[END_REF]. The increase in dry-season water level leads to the destruction of flooded forests surrounding the lake and therefore causes significant loss of livelihoods of the people and negative impact on aquatic production in the lake.

The effects likely put additional pressure on the remaining resources and thus potentially cause resource competition and fuel related conflicts in the area.

Agricultural expansion

Rice and fish are backborn of the Tonle Sap's flood plain. Cambodia considers rice as "white gold" and has an ambition to become one of the major milled-rice exporting countries in the global market. This has its effects on the Tonle Sap area as well. The development of large-scale irrigation projects in the upper basin and the emergence of private irrigation structures in the flood plain influence the avaiability of resources to different user groups [START_REF] Keskinen | The Tonle Sap Lake, Cambodia: waterrelated conflicts with abundance of water[END_REF]. The rapid agricultural development does not only associate with the built irrigation structure, the access to the floodplain has also been improved through the construction of rural roads. Literature shows that built structures have led to biodiversity loss as a result of flow modification, habitat alterations or loss and water pollution (WorldFish Center, 2007).

Associating the impact on local livelihoods, the destruction of flood plain not only change the traditional forms of livelihoods of different user groups, but the effects are more concerning with the subsistence and small-scale fishers who generally have lower capacity (i.e. household capital) to take advantage of opportunities provided by the development of either the infrastructure or irrigation scheme. For instance, households in southern edge of Steung Chinit irrigation project in Kampong Thom reported decreased fishing income and are forced to diversify into either farm or non-farm employment because of the declined inome (WorldFish Center, 2007).

Management change

The fisheries of the Tonle Sap were traditionally divided into three types: smallscale or subsistence fishing, middle-scale or licensed fishing and large-scale or fishing lots. Open-access areas are shared between small-scale and middle scale fisheries, which are outside the fishing lots and fish sactuaries. While small-scale or subsistence fisheries can fish for the whole year round, middle-scale fisheries can only operate with a fishing license restricting the number and kinds of gears used and the fishing period which is allowed only during the open season between October to May (for areas north of Phnom Penh). 63% of gears used for middle-scale fisheries are gillnets [START_REF] Ahmed | Socioeconomic Assesment of Freshwater Capture Fisheries in Cambodia[END_REF].

Large-scale fisheries or fishing lots refers to as industrial fisheries in which access and exploitation rights are acquired through public auction; and locations, boudaries, fishing actions, timing and other conditions are determined in the leasing contract. The fishing lots cover large areas and use large traping device. The lessee has his own force to control access and regulate fishing activities inside the lot and prevents any unlawful access or fishing activities within the defined boundaries.

In 2000, first fishery reform was carried out by converting 56% of total fishing lot areas for Community fisheries. In 2012, the government completely abolished the industrial-scale century-old private fishing lot system covering an area of 270,217 hectares, and re-arrange 35% of the areas for conservation and the remaining for open access [START_REF] Sithirith | The Patron-Client System and Its Effect on Resources Management in Cambodia: A Case in the Tonle Sap Lake[END_REF]. The transition from the private fishing lot areas to communityuse areas poses questions to be investigated in terms of fishing income, functioning and impact of community-based fisheries management, fishery sustainability and the conditions for succesful co-management of resources.

Solutions

Small-scale fisheries has become scholarly and policy attention because of its social and economic dimensions, especially in some of the world's poorest countries. The sustainability of the resources is important as it can continue to maintain food security and income for those depending on them. Recent studies associate with factors to improve performance and promote sustainability of the fisheries [START_REF] Franco | Five key attributes can increase marine protected areas performance for small-scale fisheries management[END_REF][START_REF] Kosamu | Conditions for sustainability of small-scale fisheries in developing countries[END_REF]. For instance, Di [START_REF] Franco | Five key attributes can increase marine protected areas performance for small-scale fisheries management[END_REF] identified key attributes (i.e. high enforcement, presence of management plan, fisher participation in management and board and promotion of sustainability) essential to increase the performance of smallscale fisheries. In developing countries, sustainability of small-scale fisheries associates with improving social capital and community engagement [START_REF] Kosamu | Conditions for sustainability of small-scale fisheries in developing countries[END_REF]. Additionally, [START_REF] Pomeroy | Managing overcapacity in small-scale fisheries in Southeast Asia[END_REF] shows similar finding by highlighting people and communityfocused solutions should be enhanced to manage overcapacity or overfishing in Southeast Asia. Other researchers emphasize wealth-based approach [START_REF] Allison | The livelihoods approach and management of small-scale fisheries[END_REF][START_REF] Schuhbauer | Economic viability and small-scale fisheries -A review[END_REF] and the vulnerability of small-scale fisheries to management change [START_REF] Tilley | Predicting vulnerability to management changes in data-limited, small-scale fisheries[END_REF].

Within the recent literature, there is a common understanding on the importance of socioeconomic conditions, the vulnerability and adaptive responses of resource users as well as a shared concern over resource sustainability. Here, I propose the livelihood approach based on Sustainable Livelihood Framework and the co-management of fisheries resources as the solutions to address livelihoods of fishing communities in the Tonle Sap. The two approaches integrate the social and ecological perspectives by linking human livelihoods and natural resources, which is important to maintain ecosystem integrity and productivity.

Sustainable Livelihood Approach (SLA)

The SLA by [START_REF] Chambers | Sustainable rural livelihoods: practical concepts for the 21st century[END_REF] initially built on three fundamental conceptual principles of capability, equity and sustainability. Within the generality of meaning used by [START_REF] Sen | Capability and Well-being[END_REF], capability refers to an ability to perform basic functionings a person is capable of doing or being. The functionings represent various activities or states a person manages to do or to be in life. The livelihood capability mean an ability to cope with stress or shocks or being capable to find or make use of livelihood opportunities [START_REF] Chambers | Sustainable rural livelihoods: practical concepts for the 21st century[END_REF]. The capability means not just being reactive, but proactive and dynamically adaptable. This also focuses on household strengths or assets that enable them to make decision of livelihood choices or withstand crises.

While livelihoods of some people are predetermined, for example as successors from their parents, many other are influenced by socio, economic and ecological environments and it depends on their adaptive capabilities whether being able to exploit new opportunities or become vulnerable to the change.

The role of assets was also suggested by [START_REF] Swift | Why Are Rural People Vulnerable To Famine[END_REF] to improve understanding of the famine vulnerability. It provides additional insights not just about the patterns of social or economic failure by different groups of asset holdings, but why? It continues to explain why war and conflicts are a crucial cause of vulnerability. It also helps to explain how households and the community make decision about their livelihood strategies and rebuild their life. Furthermore, the 5-asset pentagon (human, natural, financial, social and physical) (Figure 1) provides an appropriate way to picture the multidimensional nature of poverty and vulnerability being faced by fishing communities, such as poor living condition, inadequate services, lack of skills and assets, or high exposure to risks [START_REF] Pittaluga | Poverty profiles of artisanal fishers: methods based on SLA model[END_REF][START_REF] Townsley | Livelihoods and aquatic resource management[END_REF].

Equity can be measured in terms of distribution of income, assets, capabilities or opportunities [START_REF] Chambers | Sustainable rural livelihoods: practical concepts for the 21st century[END_REF]. In fisheries, equity means fair allocation of access rights or enforcement of rules. It focuses on people and social justice where people not only gain access to assets or resources but are able to maintain adequate and decent living.

According to [START_REF] Chambers | Sustainable rural livelihoods: practical concepts for the 21st century[END_REF], sustainability falls into two groups: environmental and social sustainability. Environmental sustainability concerns with resource productivity and its effects on livelihoods. It associates with the enhancement of one livelihood activity which may impact other livelihoods. From ecological literature, sustainability refers to "the ability of a system to maintain productivity in spite of major disturbance, such as is caused by intensive stress or a large perturbation" [START_REF] Conway | Agroecosystem analysis[END_REF]. On the other hand, social sustainability concerns with internal capacity to respond to pressure. This also links to resilience which is referred to " an ability of ecological or livelihood system to bound back from stress or shocks" [START_REF] Allison | The livelihoods approach and management of small-scale fisheries[END_REF]. To enhance the resilience in the Tonle Sap, it is necessary to understand how households cope with changes and the determinants in their livelihood choices.

The development of SLA leads to a broader view of sustainability to encompass other dimensions. The four key pillars of sustainability associates with social, economic, institutional and environmental factors [START_REF] Carney | Livelihoods Approachs Compared[END_REF], which are important in fishery management. For instance, the focus of institutional dimension is critical since the degraded or collapsed fishery resources [START_REF] Allan | Overfishing of Inland Waters[END_REF][START_REF] Pauly | Towards sustainability in world fisheries[END_REF] is in part attributed to the governance system [START_REF] Acheson | Institutional Failure in Resource Management[END_REF][START_REF] Pomeroy | Community-based and co-management institutions for sustainable coastal fisheries management in Southeast Asia[END_REF]. The main challenges associate with addressing compliance, conflicts and resource depletion [START_REF] Ayers | Emergence of co-management governance for Hawai'i coral reef fisheries[END_REF][START_REF] Butler | Evaluating adaptive co-management as conservation conflict resolution: Learning from seals and salmon[END_REF][START_REF] Evans | Assessing the impact of fisheries comanagement interventions in developing countries: A meta-analysis[END_REF].

Figure 1 presents the sustainable livelihood analysis framework, illustrating the interactions between various elements such as livelihood capitals or assets, livelihood activities and outcomes, external vulnerability context, and policies and institutions.

The role of assets is significant as earlier discussed and particularly in the context of Tonle Sap and war-torn Cambodia, in which the livelihood base was destroyed or weakened and households have limited adaptive capacity (Bond, 2015;[START_REF] Nuorteva | Water, livelihoods and climate change adaptation in the tonle sap lake area, Cambodia: Learning from the past to understand the future[END_REF]. Access to assets or livelihood activities are also influenced by policies, institutions and processes. Postwar economy policies, fisheries reforms and the roles of community-based fisheries management enable access to livelihood assets and activities.

Furthermore, livelihood assets or capitals permit households to make decision of livelihood choices or undertake the livelihood activities. The framework also emphasizes on the significance of the external environment, known as vulnerability context, affecting livelihood sustainability. Trend, shock and seasonality influence households' success or failure. Understanding these external factors can help to design policies and interventions which assist people's existing coping and adaptive strategies [START_REF] Allison | Putting the principles of the Sustainable Livelihoods Approach into fisheries development policy and practice[END_REF]. For instance, various studies indicate that the livelihoods of households in the Tonle Sap are likely to be adversely impacted by future socio-economic, policy, ecological and climate change [START_REF] Arias | Impacts of hydropower and climate change on drivers of ecological productivity of Southeast Asia's most important wetland[END_REF][START_REF] Salmivaara | Socio-Economic Changes in Cambodia's Unique Tonle Sap Lake Area: A Spatial Approach[END_REF], adding to existing poverty problems in this region which is higher than the national average (JICA, 2010).

The concept of SLA has been used to study different topics of livelihood in rural development, poverty, fisheries and natural resources management [START_REF] Allison | Putting the principles of the Sustainable Livelihoods Approach into fisheries development policy and practice[END_REF]; C. [START_REF] Barrett | Dynamic Poverty Traps and Rural Livelihoods[END_REF][START_REF] Ellis | The determinants of rural livelihood diversification in developing countries[END_REF][START_REF] Erenstein | Poverty mapping based on livelihood assets: A meso-level application in the Indo-Gangetic Plains, India[END_REF][START_REF] Solesbury | Sustainable Livelihoods : A Case Study of the Evolution of DFID Policy[END_REF]. The approach has been popular to study resource management systems, identifying what existing systems are appropriate and why some have failed (Ferrol-Schulte, Wolff, Ferse, & Glaser, 2013). However, the main limitation is associated with the level of detail of information collected, which can be costly and labor intensive. Nevertheless, this does not undermine the value of this holistic, multidimensional approach if the livelihood intervention focuses on people-centered solution.

Community-based fisheries management (co-management)

The failure of conventional fisheries management [START_REF] Allan | Overfishing of Inland Waters[END_REF][START_REF] Pauly | Towards sustainability in world fisheries[END_REF] makes the co-management more appealing. The overarching issues are resource depletion and conflicts [START_REF] Ayers | Emergence of co-management governance for Hawai'i coral reef fisheries[END_REF][START_REF] Butler | Evaluating adaptive co-management as conservation conflict resolution: Learning from seals and salmon[END_REF]. Co-management can be broadly defined as a shared responsibility and authority between the government and local resource users/community [START_REF] Pomeroy | Fisheries Co-management and Small-scale fisheries: A Policy Brief[END_REF]. Thus, resource users directly and formally involve in decision making and resource management process through the delegation of regulatory functions to fishers' organizations. The complexity of the socio-ecological systems requires the knowledge of more than a single agency and collaborative actions of multiple parties to effectively address the problems. This bottom-up approach is now widely recognized as a means to managing natural resources, which promote collaboration and learning, responsible resource use and rule compliance [START_REF] Jentoft | The community: A missing link of fisheries management[END_REF][START_REF] Nielsen | Fisheries co-management-an institutional innovation? Lessons from South East Asia and Southern Africa[END_REF][START_REF] Yandle | Sharing natural resource management responsibility: Examining the New Zealand rock lobster co-management experience[END_REF]. It is vital to address sustainability, efficiency and equity which exist in small-scale fisheries today [START_REF] Pomeroy | Fisheries Co-management and Small-scale fisheries: A Policy Brief[END_REF].

Below as the summary of different aspects of co-management have been emerged to the frontline of the literature over the past decades.

-Co-management is power and responsibility arrangement between the government and local fishers/community [START_REF] Pomeroy | Fisheries Co-management and Small-scale fisheries: A Policy Brief[END_REF]. The recognition and legitimization of local fisher organizations help promote equity, even to some degrees, in the partnership arrangement and address imbalance of power and make collaboration less problematic [START_REF] Berkes | Evolution of co-management: Role of knowledge generation, bridging organizations and social learning[END_REF][START_REF] Nadasdy | Reevaluating the co-managment success story[END_REF].

-Co-management is an institutional building. The arrangement promotes closer collaboration between the community and government and other agencies, providing opportunities for empowerment, capacity building and leadership development. Identifying appropriate local institutions and building on their strengths or establishing new ones, formulating favorable policy environment, supporting network building and feedback learning over time develop leadership and institutional capacity and economically and politically empower the impoverished majority through transfer of access of and control over resources from a few to a community at large [START_REF] Pomeroy | Conditions affecting the success of fisheries co-management: Lessons from Asia[END_REF].

-Co-management provides means of building trust and social capital. The success or survival of co-management depends on the established relationship of trust and mutual respect among partners [START_REF] Pomeroy | Conditions affecting the success of fisheries co-management: Lessons from Asia[END_REF] and social capital in general . Usually, local fisheries have low trust on the government and are rarely ready to work together [START_REF] Jentoft | User participation in fisheries management: lessons drawn from international experiences[END_REF][START_REF] Pomeroy | Conditions affecting the success of fisheries co-management: Lessons from Asia[END_REF]. Trust and working relationship grow through coordination, communication and consultation process which provides opportunities for clarification of needs, roles and responsibilities, concerns, and expectation of all partners.

-Co-management is a process. Co-management is not an end point, but an evolving and learning process [START_REF] Armitage | Adaptive co-management and the paradox of learning[END_REF][START_REF] Pinkerton | Translating Legal Rights into Management Practice: Overcoming Barriers to the Exercise of Co-management[END_REF]. It may take substantial time for the co-management to evolve in its development process [START_REF] Pomeroy | Conditions affecting the success of fisheries co-management: Lessons from Asia[END_REF].

-Co-management is a problem-solving and conflict resolution mechanism. Comanagement enables learning among partners and increasingly addresses complex problems of the socio-ecological systems [START_REF] Olsson | Adaptive comanagement for building resilience in social-ecological systems[END_REF][START_REF] Plummer | Adaptive co-management for climate change adaptation: Considerations for the barents region[END_REF]. It provides means to address conflicts among user groups and reinforce rule compliance [START_REF] Kearney | Co-management: The resolution of conflict between commercial and recreational fishers in Victoria, Australia[END_REF][START_REF] Pomeroy | Conditions affecting the success of fisheries co-management: Lessons from Asia[END_REF].

-Co-management is a governance approach in which resource users directly involve in managing and making decision about the resources which influence their livelihoods. It is considered the alternative to the centralized governance system to address ecosystem sustainability [START_REF] Acheson | Institutional Failure in Resource Management[END_REF][START_REF] Pomeroy | Community-based and co-management institutions for sustainable coastal fisheries management in Southeast Asia[END_REF].

Co-management should not be considered as a single alternative strategy to address all problems of fisheries management, but as a set of alternative management strategies, appropriate for specific areas and situations (R S [START_REF] Pomeroy | Fisheries Co-management and Small-scale fisheries: A Policy Brief[END_REF]. While co-management is not a universal panacea, more experience and research are needed to -Institutional Arrangement Analysis: This component links contextual variables characterizing key attribute of the resources (biological, physical) and the resource users (technology, market, social, cultural, economic, political) with the management institutional arrangements (rights and rules). The relationship between contextual variables and institutional arrangement influence the actions of resource users and authorities in coordinating and cooperating in fisheries resource governance, management and use. This associates with incentives and disincentives which shape the patterns of interactions and behaviors between co-management partners.

-Co-management Performance Analysis: The second component focuses on the outcomes. The outcomes, in turn, influence, the contextual variables and behaviors of co-management partners (i.e. resource users, authorities and other stakeholders). The performance analysis enables the evaluation of the co-management institutional arrangement associating with management efficiency, equity and sustainability of resource utilization.

-Characteristics of Successful Co-management Institutional Arrangements: The last component, the most important aspect, concerns with identification of conditions and processes which lead to successful long-enduring fisheries co-manent arrangements.

Across developing countries, the co-management is now considered as a mainstream approach to small-scale fisheries management [START_REF] Evans | Assessing the impact of fisheries comanagement interventions in developing countries: A meta-analysis[END_REF]. An assessment of the impact of fisheries co-management in developing countries by [START_REF] Evans | Assessing the impact of fisheries comanagement interventions in developing countries: A meta-analysis[END_REF] Across developing countries, the co-management is now considered as a mainstream approach to small-scale fisheries management [START_REF] Evans | Assessing the impact of fisheries comanagement interventions in developing countries: A meta-analysis[END_REF]). An assessment of the impact of fisheries co-management in developing countries by [START_REF] Evans | Assessing the impact of fisheries comanagement interventions in developing countries: A meta-analysis[END_REF] indicates a positive trend associating with both the outcome and process indicators. On the outcome measures, only resource access shows a negative trend while other four indicators, namely resource well-being, fishery yield, household well-being and income, indicates positive change. Associating with co-management process indicators, the top five measures as participation, influence, rule compliance, control over resources and conflict report a positive trend especially across Asian countries for both marine and inland fisheries. Despite some reported challenges, the co-management approach shows more on the success than failure in small-scale fisheries particularly in the Asian context.

Specific objectives

The co-management can be conceptualized as an institution intervention in the SLA framework to achieve desired outcomes of fishing communities in the Tonle Sap.

The livelihood of fishing households and their adaptive strategies depend on the vulnerability context, the interactions of livelihood assets and activities and the performance of co-management arrangement (community fisheries). Here, the overall goal of this research is to assess the livelihood strategies of fishing communities in the Tonle Sap in the face of various drivers of change around the lake, by integrating SLA and co-management perspectives in the analysis.

The specific objectives of the research are to:

1. assess spatial and temporal characteristics of livelihood strategies of post-conflict Cambodia from 1999 to 2013; 1.1 identify livelihood cluster and characteristics in Cambodia, associating with crops, livestock, fishery, forestry and nonfarm.

1.2 Assess spatial and temporal variations of livelihood strategies in Cambodia from 1999 to 2013, associating the five strategies.

2. analyze the current livelihood choices and the determinants of household total income; 2.1 identify factors (associating with livelihood assets) affecting households' livelihood choices.

2.2 identify factors (associating with livelihood assets) affecting households' total income. 4. assess the impact of community fisheries and the determinants in the Tonle Sap.

4.1 assess the impact of community fisheries associating with different ecological zones and community size (area) in the Tonle Sap.

4.2 identify factors influence in the impact associating with ecological zone and community size in the Tonle Sap.

Study area

Study area for livelihood dynamics and determinants

The study area for understanding livelihood dynamics and identifying the determinants of household's choices and income focuses on entire Cambodia, which includes Cambodia's all regions of Plateau/Mountain, Plain, Coast, and the Tonle Sap. Covering the entire country helps to better understand the variations of livelihood strategies and provides a broader picture of household's choices and responses to socioeconomic, policy, ecological and climate change. That broader context has its implications on the Tonle Sap, especially in terms of the linkages between livelihoods, natural resources and post-conflict development. For instance, how the macro change influences livelihood resources and strategies, institutional processes and household's economic performance.

Similarly, the analysis of the determinants of livelihood strategies and income from the national setting provides useful insights and comparative views how household's choices and economic performance in Tonle Sap may differ from the national benchmark.

Study area for economic impact to future scenario change

The location for the assessment of economic impact is in Pursat province which is situated in northwestern Cambodia. It is one the three provinces in the Tonle Sap (Pursat, Battambang and Kampong Thom) previously identified as important case studies by the Belmont Forum's Tonle Sap climate change project. This project is a consortium of 18 different institutions worldwide, including Cambodia, France, US and Canada, seeking to improve income and productivity of Tonle Sap fisheries in the face of climate change. Pursat has one of the largest coastlines along the Tonle Sap Lake and is con-nected to an important tributary and fishing location. The study area focuses on 26 villages located in three districts of Pursat province (Krakor, Kandieng, and Bakan) (Figure 6).

Study area for impact of CFis

Battambang and Kampong Thom exhibit an important fishing-farming ecology in the Tonle Sap and therefore were selected to study the impact of CFis. While fishing is fundamental in both zones, Kampong Thom reflected a more significant role of farming in which large-scale private irrigation structures were built up to support the rice production systems. In contrast, households in Battambang still largely depend on fishing as their primary livelihood. A total of 26 CFis located in both provinces was used to assess the impact of CFis and comparative study (Figure 13).

Cambodian Socio-Economic Survey (CSES)

The Cambodia Socio-Economic Survey (CSES), a nationwide representative sur- The CSES 1999, 2003/2004, CSES 2008and CSES 2013 were chosen to study the dynamics and determinants of livelihood strategies. For the study on livelihood dynamics, four years (1999, 2003/2004, 2008 and 2013) were selected as the research objective was to investigate the spatial and temporal variations of livelihood strategies.

Another important reason is that variables in the selected years are appropriate for timeseries analysis. The determinants of livelihood choices and income (objective 2) focuses on 2013 survey as the study was aimed what factors influence households' income and decision to participate in livelihood activities at present.

Consolidating data into a single data matrix ready for analysis took some efforts and sometimes was challenging. For instance, datafile for each year is not in a single file, but a separate main category which is sometimes inconsistent in structure and makes it difficult to be merged by household reference number. The value of some variables are not consistently coded, for example land size can be coded in square meter, acre, hectare, or other. In some cases, there are different in coding system across years.

Care must be taken when trying to consolidate data across years. Even effort being taken to improve consistency of the survey, there are still some small variations and therefore coding system and operational manuals should always be referred carefully for each year from which the data is extracted.

For this study on livelihood dynamics, the total number of household observations is 28,388 across the four years. The analysis of livelihood determinants was based a total of 3,138 households.

Household and Community Fisheries surveys

Data collection is part of the project funding by the Belmont Forum's Tonle Sap climate change project. Additional funding was supported by Open Society Foundation which partly funded the fieldwork in Kampong Thom. Three provinces of the Tonle Sap (Pursat, Battambang and Kampong Thom) were identified for household and CFi surveys. For the household survey, the goal is to gain understanding the characteristics, livelihoods, and opinions associating with the changing fishery resources. The goal of CFi survey was to assess the performance of CFi in managing fishery resources in Tonle Sap lake.

For the case study on economic impact to future scenario change, a total of 181 households in Pursat were randomly selected to complete the surveys. 26 CFis were selected for the study of the determinants of impact of CFis with a total of 437 respondents.

Overview of statistical analyses

Case study on livelihood dynamics

The main objective of the study on livelihood dynamics was to examine the livelihoods of Cambodian households from multiple resource dependence (crops, livestock, fishery, forestry and nonfarm self-employment) during the post-conflict recovery by looking at spatial and temporal variations of the livelihood strategies from 1999 to 2013.

Non-metric multidimensional scaling (NMDS) and cluster analysis were performed to analyze the livelihood strategies characteristics, and spatial and temporal variations. ArcMap was also used to display clustering results and spatial and temporal patterns of livelihood classifications.

Case study on livelihood determinants

The aim of the study was to use various socio-economic variables taking from the CSES 2013 to identify the determinants of livelihood choices and total income for households in Cambodia. In the first stage of analysis, household net income from each livelihood strategy (crops, livestock, fishery, forestry and nonfarm self-employment) was calculated using standard income method earlier mentioned.

Multinomial logit regression (MNL regression) was used to identify the determinants in livelihood strategy choice because the choice is a polychotomous variable. In the MNL regression, crop strategy was set as reference strategy as majority of Cambodian rural labor force engaging in crop production strategy. Furthermore, in order to see the determinants in household's total income, ordinary least-squares regression (OLS regression) was carried out with the same set of explanatory variables.

Case study on economic impact of future scenarios

The objective of the study was to investigate the economic impact of households' adaptive responses to future socioeconomic, policy, ecological and climate change in the Tonle Sap. The four future scenarios conditions were set as below:

-Scenario A (Less fish) -A 50% reduction in fish production in Tonle Sap Lake.

-Scenario B (More farm land) -An increase in agricultural land due to changes in flood plain habitats.

-Scenario C (Urbanization) -The creation of more jobs due to urbanization and increased economic activities in urban centers, particularly in Phnom Penh.

-Scenario D (Stagnation) -The status quo is retained, i.e., same situation as today.

The analysis was based on household survey in Pursat province, one of the five provinces in the Tonle Sap, and involved two steps: (i) estimate net income from current activities, and (ii) estimate economic impact from future scenarios.

To estimate net income from current livelihood activities, benefits and costs data collected from the field survey were used for the calculations and livelihoods were divided into 3 groups:

-Group 1 = Fishing only -Group 2 = Fishing + Farming and/or Off-farm work -Group 3 = Non-fishing work

To estimate economic impact under future scenarios, four hypothetical conditions were proposed:

-Scenario A (Less fish) -A 50% reduction in fish production in Tonle Sap Lake.

-Scenario B (More farm land) -An increase in agricultural land due to changes in flood plain habitats.

-Scenario C (Urbanization) -The creation of more jobs due to urbanization and increased economic activities in urban centers, particularly in Phnom Penh.

-Scenario D (Stagnation) -The status quo is retained, i.e., same situation as today.

For each scenario A-D, each respondent provided: a) whether they would continue with their current livelihood strategy (i.e., allocate same amount of time or resources to each livelihood activity); and b) how they would reallocate their time to different livelihoods options. If in (a) the respondent indicated no change in current allocation, then current livelihood net income was assigned to that scenario.

The net income of each livelihood activity the respondent chose for each scenario was assigned based on the respondent's current livelihood net income. If an individual chose a new livelihood that he/she did not currently participate in (i.e., no current net income data was available for that activity), then an averaged net income for that livelihood activity was assigned. For detailed information on the methods and calculations, see section 5.2.

Case study on impact of CFis

This study aimed to assess the impact of CFis associated with different ecological zones of the Tonle Sap and the size of community managed area, seeking to understand the links between management arrangements and the ecological determinants.

The analysis involved two steps. First, the classification and regression trees (CART) analysis [START_REF] Breiman | Classification and Regression Trees[END_REF] was carried out to identify the impact of CFi in association with ecological factors of the Tonle Sap and the size of the community area. Second, logistic regression was implemented to find the determinants of the impact of the CFi based on the CART model results by using a set of explanatory governance variables.

Introduction

In developing countries and those affected by conflicts, a significant percentage of the population relies on land, water, forests and other natural resources. In conflictaffected countries, it is estimated that approximately 60 to 80 percent of household income are from agriculture and natural resources [START_REF] Bruch | Human Conflict: Targeting Natural Resources[END_REF]. The armed conflicts usually destroy the livelihood systems and households are forced to adopt coping strategies which are sometimes environmentally unsustainable.

Revitalizing livelihoods is critical during the recovery as it can either promote development and peace or fuel violence or new forms of conflict. The potential sources of conflicts are associated with resource access and ownership [START_REF] Andre | Land relations under unbearable stress: Rwanda caught in the Malthusian trap[END_REF]. In some cases, the conflict is driven by social groups who work together to take advantage of the weakened institutions and of peace by further devastating the economy and local livelihoods through unsustainable and illegal resource extractions [START_REF] Oglethorpe | Overview C: Conservations in times of war[END_REF]. On the pathway of reconstruction, war-torn countries may adopt economic policies that emphasize accelerating rapid economic growth, resource extraction and attracting foreign investments by neglecting long-term livelihood and ecological purposes of the natural resources. This pattern was also observed in the damaged economy of post-war Japan where maximizing natural resource harvesting was initially prioritized to address immediate needs of the country [START_REF] Jones | Fisheries Policies and the Problems of Instituing Sustainable Management: The Case of Occupied Japan[END_REF][START_REF] Makino | Co-management in Japanese coastal fisheries: Institutional features and transaction costs[END_REF][START_REF] Yoshimura | Present state of rivers and streams in Japan[END_REF]. This article examines the livelihoods of Cambodian households from multiple resource dependence during the post-conflict recovery by looking at spatial and temporal variations of the livelihood strategies from 1999 to 2013. Given multidimensional links of peacebuilding, economic growth and natural resources, Cambodia shares important historical and current characteristics and draws interest for an investigation of the dynamics of livelihood change at the micro level.

The linkages between farm/resource-based and nonfarm strategies have been popular among scholars and development practitioners, particularly in a transitional and developing economy [START_REF] Djurfeldt | Seasonality and farm/non-farm interactions in Western Kenya[END_REF][START_REF] Fritzsch | Is non-farm income diversification a feasible option for smallscale farmers? An assessment using a composite fuzzy indicator[END_REF][START_REF] Hitayezu | Farm households' participation in rural non-farm employment in post-war Rwanda: Drivers and policy implications[END_REF]; T. T. [START_REF] Nguyen | Rural livelihoods and environmental resource dependence in Cambodia[END_REF]. The study adds to existing literature on the livelihood diversification and, hence, provides a good understanding of the socio and ecological interactions and how households might cope with various drivers of change over time. Another specific contribution of this study is related to the role of nonfarm self-employment in rural economy in which the sector is recognized to play a vital role in addressing rural-urban migration and contributing to national income growth [START_REF] Lanjouw | The rural non-farm sector: Issues and evidence from developing countries[END_REF].

The research differs from previous studies in two important aspects. First, while some studies focus on a particular area, especially by [START_REF] Nguyen | Rural livelihoods and environmental resource dependence in Cambodia[END_REF] and [START_REF] Rahut | Non-farm employment and incomes in rural Cambodia[END_REF] in the context of Cambodia, here the analysis covers the entire country and thus contributes to the generalization of the findings of the livelihood strategy patterns.

Second, the analysis during the 15-year period from 1999 to 2013 provides a more dynamic picture of the livelihood strategies moving from post-war and closed-economy period to an open and market-based system.

The combination of temporal and cross-sectoral analysis provides a useful basis for determining and understanding livelihood change and other driving force of variations over time. By doing so, this study offers policy makers useful information to feed into development initiatives, for improving the efficiency of policy interventions, and for sustaining peace.

Post-Conflict Cambodia and Livelihoods

Cambodia is a small and one of the least developed countries in Southeast Asia.

Once a center of the glorious Khmer Empire, Cambodia has struggled for independence, peace, and stability over the past centuries. Cambodia's history has been uneasy periods of the French colonization ; of the Indochina War until 1975; one of the world's most murderous regimes, the Khmer Rouge (1975)(1976)(1977)(1978)(1979); and of civil war until the Paris Peace Accord in 1991. Despite returning to peace in 1991, Cambodia continued to experience some armed conflicts among political fractions and between the government and the Khmer Rouge forces. It wasn't until 1998, when the remaining force of the Khmer Rouge dropped off their weapons, that the Cambodian people were able to realize the long-awaited dream of full peace after decades of wars and bloody conflicts.

On one hand, Cambodia shares many similarities with other post-conflict or wartorn states including being at a low level of economic development, depleted physical and human capital, highly resource and aid dependent, and limited capacity to prevent economic failure and sustain peace. On another hand, Cambodia might be a distinct case. With one-third of the population killed during the Khmer Rouge regime between 1975 to 1979, the conflict prolonged for another two decades. Cambodia started from an extremely low starting point and the country was almost completely destroyed. Experience from Cambodia is not just about a post-conflict, but a 'post-post-conflict'. That is because peace was not being realized after one conflict was ended and it always returned to a new form of conflict until 1998.

Building a post-conflict Cambodia could be more challenging when one of every 236 Cambodians is an amputee (Human Rights Watch & Physicians for Human Rights, 1991) and the country is classified as one of the world's most contaminated with landmines and explosive remnants of wars (ERW). Landmines remain problematic despite many years of demining efforts, which continue to threaten the life of the Cambodian people and constrain land accessibility by rural population, especially for livelihoods.

Since the restoration of peace, Cambodia has experienced a period of rapid growth.

Between 1999 to 2013, Cambodia's economy has grown at an average rate exceeding 8 percent per annum. The period from 1999 to 2008 was particularly fast, achieving a two-digit economic growth rate, placing Cambodia among the world's top performers and as one of only 46 countries which have achieved an average 7 percent annual growth rate for 14 consecutive years [START_REF] Guimbert | Cambodia 1998-2008: An Episode of Rapid Growth[END_REF]. The Cambodian growth rate is one of the fastest among post-conflict and developing economy standards, and only below a few high performance countries such as China, Hong Kong and Singapore for some selective decades since the 1960s [START_REF] Guimbert | Cambodia 1998-2008: An Episode of Rapid Growth[END_REF][START_REF] Hill | Cambodia: Rapid growth in an open, post-conflict economy[END_REF]. Furthermore, Cambodia has tripled income per capita over the past two decades and recently graduated to lower-middle income economy. Meanwhile, the poverty rate has declined sharply from the early 1990s of more than 50 to 20 percent in 2011 (World Bank, 2014).

The growth rate has resulted in rapid structural change. During the early 1990s, Cambodia was primarily engaged in subsistence agriculture, dominated by rice, and its allied activities such as forestry and fishery. Almost 80 percent of total labor force is engaged in agriculture [START_REF] Acharya | Off-farm and Non-farm Employment: A Perspective on Job Creation in Cambodia[END_REF]. Although agriculture continues to grow, its share of GDP has been on the decline from over 50 percent to just about 30 percent over the past two decades (World Bank, 2015a) and the share is offset by increasing role of services and industry which is principally dominated by tourism, garments, and construction. Cambodia's economic recovery policies aim at promoting rapid growth rather than improving resource governance and protecting property rights and tenure.

In that sense, Cambodia prioritizes the allocation of arable land to business tycoons and foreign investors in the form of Economic Land Concessions over the landless and landpoor families under the Social Land Concessions program [START_REF] Neef | The Politics and Ethics of Land Concessions in Rural Cambodia[END_REF][START_REF] Vrieze | Carving Up Cambodia: One concession at a time[END_REF].

A number of policies are formulated to attract foreign investments and accelerate growth including the Open Sky Policy for the tourism sector, adoption of investment law and incentives, and the establishment of special economic zones (SEZs) in mid-2000s. This resulted in rapid urbanization in some areas of the country. At the same time, there is a rapid increase in the level of rural-urban migration. For instance, Phnom Penh's population has increased by 70 percent from about 1 million in 1998 to 1.7 million in 2013 (Asian Development Bank, 2014). A study in 2011 in 375 villages across Cambodia reveals that half of rural migration is to Phnom Penh and one-third is to other countries, mainly Thailand (MoP, 2012).

Materials and methods

Data source and study area

Data for this study was derived from the Cambodia Socio-Economic Survey CSES 1999 (4 th survey) was selected as the first year in this study because it was the year that Cambodia marked the real national unity after decades of conflicts. The CSES 2003/2004 (5 th ), CSES 2008 (7 th ) and CSES 2013 (13 th ) were chosen to understand the temporal change in household's livelihood strategies. Sampling procedures and field operations manual for all surveys were detailed in NIS ( 2016). This study focused on all provinces in Cambodia, featuring different ecological zones such as upland, plain and coastal areas.

For the four periods of time, the total number of household observations is 28,388.

The individual household observations were pooled into district-level data using median values. In this study, the district was the unit of analysis, which was further elaborated below.

From the socio-economic survey data, five categories of households' livelihood portfolio were selected: (1) crops, (2) livestock, (3) fishery, (4) forestry and hunting, and (5) self-employed nonfarm activities. The selection of livelihood strategies was based on existing literature showing that households pursue a variety of livelihood activities as a survival strategy associating with agriculture, natural resources and nonfarm [START_REF] Babulo | The economic contribution of forest resource use to rural livelihoods in Tigray, Northern Ethiopia[END_REF][START_REF] Ellis | The determinants of rural livelihood diversification in developing countries[END_REF][START_REF] Nielsen | Quantifying rural livelihood strategies in developing countries using an activity choice approach[END_REF][START_REF] Soltani | Poverty, sustainability, and household livelihood strategies in Zagros, Iran[END_REF]. Furthermore, the role of nonfarm livelihoods is fundamental after the recovery period and while the conflict-affected countries are en route to development. The empirical evidence from Africa and Asia confirms growing role of rural nonfarm income during the transformation process [START_REF] Canagarajah | Non-farm income, gender, and inequality: Evidence from rural Ghana and Uganda[END_REF][START_REF] Kung | So What If There Is Income Inequality? The Distributive Consequence of Nonfarm Employment in Rural China[END_REF] According to [START_REF] Yu | Rice production response in Cambodia[END_REF], Cambodia is divided into four main agro-ecological zones, namely Plateau/Mountain, Plain, Coast, and Tonle Sap. The Plateau/Mountain zone includes the Northeast Cambodia and Kampong Speu province in southwest bordering the coastal provinces is dense in forests and with low population density. The coastal zone consists of a very small portion of the country located in the Southwest.

Crop cultivation, mostly rice, is mainly in the Northwest-Southeast corridor, known for a high population density. Thus, the Northwest areas bordering Thailand around the Tonle Sap zone and Southeast areas bordering Vietnam in the Plain zone are the main producers of rice.

Data analysis

The analysis of livelihood strategies of households involved several steps. In the first stage, household net income from each livelihood strategy was calculated. As evidenced in recent literatures in which income share is used to measure standard of living, poverty and livelihood strategies, net income from each livelihood strategy was calculated to gain an understanding of livelihood dynamics and choices of household [START_REF] Babulo | Household livelihood strategies and forest dependence in the highlands of Tigray, Northern Ethiopia[END_REF][START_REF] De Sherbinin | Rural household demographics, livelihoods and the environment[END_REF][START_REF] Soltani | Poverty, sustainability, and household livelihood strategies in Zagros, Iran[END_REF]. The income share method has been long recognized as an important factor to measure economic performance, especially in the evaluation of household's livelihoods and to enable direct and straightforward comparison across several different years. In computing the net income from each livelihood strategy, a standard income method was followed as below:

Net Income = Total Revenue -Total Cost
The value of income or revenue is nominal. Net income in this study is equivalent to net profit accounting for both variable production and selected fixed costs, but not all. Data on some fixed expenses (depreciation) at household level were not available particularly associating with valuation of assets and their cost classification. Total revenue was calculated as Quantity of Production x Selling Price. Total cost was the sum of all cost items of each livelihood strategy.

Net income from crops: Revenues from crop cultivation were from all types of crops, fruits, and vegetables. The total cost of crop inputs comprised of expenditure in seeds & seedlings, fertilizers, hired labor, transportation, technical support, and other payments.

Net income from livestock: It included revenues from both livestock and poultry production comprising livestock and poultry sales and by-products. The production expenditure items such as feed and feed supplements, hired labor, veterinary services and medicines, service payment for technical support and transportation cost were aggregated to obtain the total cost for livestock.

Net income from fishery: Total revenue from fishery was made of revenue from aquaculture and proceeds from captured fishery. Similar to livestock, the total cost for fishery consisted of breeding stock, feed, hired labor, fuel, repair and maintenance, payment for technical support, boat rent and transportation.

Net income from forestry and hunting: The total revenue from forestry and hunting were from resource extracting activities including timber (charcoal, firewood, timber and others) and non-timber (juices, root crops, honey, herbs, wild animals or birds and others) forest products. The total cost was made up of feed, fuel, transportation, hired labor, rents, tools and equipment expenses.

Net income from self-employed nonfarm activities: The nonfarm activities associate with enterprise and business activities in secondary and tertiary sectors. Nonfarm revenues were proceeds from economic activities associating with merchandising, manufacturing and services. Total cost includes cost of sales or goods sold, variable production costs, fixed expenses, overhead and other operating costs.

Then, household-level net income data from each livelihood activity was grouped into district-level data. The total 28,388 household observations were then summarized into 578 district observations using median values for the analysis.

All the statistical analysis of the data was performed using R 3.2.5 and mapping visualization of spatial patterns of livelihood strategies was carried out through ArcMap 10.2. To analyze the livelihood characteristics, non-metric multidimensional scaling (NMDS) was performed to measure the district dissimilarity by using the 'metaMDS' function in vegan package [START_REF] Oksanen | vegan: Community Ecology Package[END_REF]. The NMDS technique enabled the district points and livelihood strategies to be plotted in ordination space. In the twodimensional NMDS diagram, the distance between each district point indicates the dissimilarity of the samples. Then, cluster analysis performing hierarchical clustering based on the ward agglomerative method on the results of the NMDS's solutions was undertaken to identify groupings of district points which have surface similarity (R Core Team, 2016). The results were placed into ArcMap to display clustering results and spatial patterns of net income classifications. Kruskal-Wallis test was performed to test for significant differences among clusters and of variations among years, followed by post-hoc tests using R's function kruskalmc in package pgirmess [START_REF] Giraudoux | pgirmess: Data Analysis in Ecology[END_REF].

Results

Household cluster and characteristics

With the five livelihood strategies (crops, livestock, fishery, forestry and nonfarm), the NMDS ordination with a stress value of 0.15 was found. The hierarchical clustering of 578 samples between 1999 to 2013 identified four distinct clusters (Figure 3a and Figure 3b). Cluster 1 (23% of all samples) was characterized as crops and livestock dependence. Cluster 2 (40%) and 3 (19%) were more diversified and natural resourcedriven. Cluster 2 was dominated by crops and its allied activities such as forestry, fishery, and livestock whereas cluster 3 was principally contributed by natural resource income, including forestry and fishery. Finally, Cluster 4 (18%) was associated with nonfarm and livestock.

Figure 3. Non-metric multidimensional scaling (NMDS) ordination of the district data based on the five livelihood strategies; a, ordination map of dimensions 1 & 2 of NMDS showing samples clustered by hierarchical clustering into four clusters and the relating livelihood strategies; b, boxplots showing contribution of each livelihood strategy to each cluster on the NMDS map

The NMDS ordination map (Figure 3a) showed clearly along the first axis the opposition between livestock and nonfarm on the one hand and to the forestry, fishery and crops on the other hand. The non-parametric multiple comparison Kruskal-Wallis test revealed a significant difference between the four clusters (χ²=356.49, df=3, p<0.001).

The post-hoc pairwise comparison tests showed a significant difference between each cluster. Axis 2 showed the opposition between natural resources (forestry and fishery) to the land-based one (crops and nonfarm). The Kruskal-Wallis test revealed a significant difference between clusters (χ²=375.74, df=3, p<0.001). The pairwise comparison indicated that cluster 1, 2 and 3 are significantly different. No significant difference was observed between the cluster 2 and 4.

Temporal and spatial trend of livelihood strategies

The variation of livelihood strategies was significantly explained along the axis 2 of the NMDS diagram (Kruskal-Wallis test, χ²=102.95, df=3, p<0.001) (Figure 4). The post-hoc analysis revealed the significant difference between 1999-2004, 1999-2013, and 2008-2013. No difference was observed between 2004and 2008. Overall, from 1999 to 2013, there was a clear trend from land-based activities (crops) towards more natural resource dependence involving fishery and forestry. It thus illustrated that more and more households were turning towards fishing, aquaculture, timber and non-timber forest products. The geographical cluster maps (Figure 4) provide a clearer picture of the temporal trend of the spatial patterns of livelihood strategies. The patterns had shifted from basic agricultural and land-based activities of crops and livestock (cluster 1) to more diversified strategies of farming and natural resources (cluster 2 and 3). Natural resource dependence became more evident in 2013 in which cluster 3, dominated by forestry, had risen. As shown in Table 1, districts driven by crops and livestock had declined from 54 percent in 1999 to 3 percent in 2013, while districts depending on forestry and fishery income had increased from 9 percent in 1999 to 30 percent in 2013. Nonfarm activities remained stable across the four years despite some marginal change in 2008.

Discussion

Livelihood diversification and spatial dependence

The results revealed four distinct livelihood groups associated with farming, natural resource, and nonfarm activities. The cluster 1 is highly dependent on land for crops as a primary livelihood strategy. Livestock is also integrated into household's choice of strategy or being adopted by other households depending on a range of socio and ecological factors. For cluster 2 and 3, the livelihood strategies are mixed but turn towards more resource dependence. The cluster 2 is highly dependent on both land and natural resources. Land is an important capital for crops and other activities such as livestock and aquaculture. In addition, households also rely on capture fishery and watershed forests along the plain area, mountains, and foothills as a way for survival. Cluster 3 is those districts which are highly dependent on natural resource income, especially forestry. Timber and non-timber forest products contribute significantly to household's income share and access to those resources is more economically important than the land ownership. Finally, cluster 4 was concerned with districts less dependent on land resources, which are characterized as nonfarm and livestock.

The pattern explained the relative strength of links between the livelihood strategies and the ecosystem. People rely on products, services, or land from nearby resource areas and establish the conditions for actions to satisfy their livelihood needs. The rice fields, rivers and forests have supported the livelihoods of Cambodian population for centuries. Local people depend on the traditional ways of living from rice farming, fishing, and extracting forest resources, mainly for subsistence purposes. Households become more or less diversified (i.e. crops, fishery, forestry) depending on the degree of interactions of the adjoining ecosystems. The results show that Cambodian households remain highly dependent on agriculture-related strategies. The sector employs more than half of Cambodia's total labor forces [START_REF] Yu | Cambodia's Agricultural Strategy: Future Development Options for the Rice Sector -A Policy Discussion Paper[END_REF]. On top of this, crops play a prominent role to varying degrees, contributing to clusters 1, 2, and 3, and accounting for more than 80 percent of the total samples.

For instance, [START_REF] Barrett | Nonfarm income diversification and household livelihood strategies in rural Africa: Concepts, dynamics, and policy implications[END_REF] and [START_REF] Reardon | Household income diversification into rural nonfarm activities[END_REF]

Primary sector is substantial, but at risk

Over the past two decades, the primary sector (crops, livestock, fishery, and forestry) has played a crucial role in household's income. In cluster 1, crops and livestock contribute 79 percent and 19 percent, respectively, to cluster's income share. In the other two clusters in which livelihood are more diversified and associating to other types of natural resources such as water and forest, the findings indicate a relatively high dependence on environmental income or households seeking to diversify other sources of income for their livelihood. In cluster 2, crops contribute 52 percent to total income share, followed by forestry (26%), fishery (15%) and livestock (6%). On the other hand, the contribution from forestry is as high as 69 percent in cluster 3, while livestock, fishery, and crops make up a share of 13 percent, 12 percent and 6 percent, respectively. The results suggest the importance of land, water, and forest to the majority of the Cambodian population in the post-conflict era especially in rural areas and indicate the high level of vulnerability if there is change in the resource systems. Combined fishery and forestry, the overall contribution of both strategies in all clusters is 31 percent, which includes the aquaculture activities. That is consistent with recent studies in Cambodia and other developing countries. [START_REF] Nguyen | Rural livelihoods and environmental resource dependence in Cambodia[END_REF] shows that the contribution of environmental income to household's total income is 27 percent, in which 19 percent is from capture fishery and 8 percent from forestry resources. Similarly, a study of 24 developing countries of 8,000 households by [START_REF] Angelsen | Environmental Income and Rural Livelihoods: A Global-Comparative Analysis[END_REF] indicates the contribution of environmental income to household total income is 28 percent.

Even though income from wage employment and remittances is not included in this study, the average contribution of forestry income of 31 percent for the entire country and 69 percent in cluster 3 are still much higher than the findings by [START_REF] Nguyen | Rural livelihoods and environmental resource dependence in Cambodia[END_REF]. Further, it may be consistent with other global studies, in which overall contribution of forestry income is 24 percent (20 percent in Asia, 21 percent in Africa and 28 percent in Latin America) [START_REF] Angelsen | Environmental Income and Rural Livelihoods: A Global-Comparative Analysis[END_REF]. As the forestry income share varies across sites, other specific areas constituting high forest income reliance are in Bolivia (64% percent) and Cameroon (59% percent) which have a similar pattern with cluster 3 [START_REF] Duchelle | Smallholder Specialization Strategies along the Forest Transition Curve in Southwestern Amazonia[END_REF].

The nonfarm self-employment is skewed towards cluster 4, comprising 61 percent and livestock constituting 35 percent. This shows that the role of nonfarm activities is still marginal relative to other strategies. On one hand, the study explains the importance of agriculture and natural resources to Cambodian livelihoods. On the other hand, however, it raises uncertainties on the future of the resource-dependent households over the issue of sustainability, especially relevant to natural resource use and extraction.

Similar to other war-torn country, Cambodia is known for weak formal institution and enforcement of rules, particularly when dealing with environmental resources [START_REF] Clements | Payments for biodiversity conservation in the context of weak institutions: Comparison of three programs from Cambodia[END_REF][START_REF] Travers | Incentives for cooperation: The effects of institutional controls on common pool resource extraction in Cambodia[END_REF]. Within the forestry sector, for example, Cambodia is classified as having among the world's highest rate of deforestation. A study by [START_REF] Hansen | High-resolution global maps of 21st-century forest cover change[END_REF] on global forest cover change between 2000 to 2012

showed that Cambodia has one of the world's top forest loss. The overall trend of environmental resource availability is on the decline as confirmed by several recent studies in Cambodia (T. T. [START_REF] Nguyen | Rural livelihoods and environmental resource dependence in Cambodia[END_REF][START_REF] Poffenberger | Cambodia's forests and climate change: Mitigating drivers of deforestation[END_REF][START_REF] Strange | Integration of species persistence, costs and conflicts: An evaluation of tree conservation strategies in Cambodia[END_REF]. The post-conflict population growth, degradation of environmental resources and increasing commercial interest in the resources resulting from the structural transformation may lead to more income vulnerability. That is because the scale of depleting resource extraction by households may not be compatible, particularly in the case of weak enforcement of rules as in Cambodia, with long-term sustainability and it thus would lead to a downward spiral by further reducing income of the households [START_REF] Cleaver | Reversing the Spiral: The Population, Agriculture, and Environment Nexus in Sub-Saharan Africa[END_REF]. The World Bank (2014) also stresses the high density of vulnerability indicating that one-fifth Cambodians are living close to the poverty line and are at risk to be pulled back to under poverty due to simple shocks.

Diversification in natural resources

In the early period of peacebuilding (1999), the livelihoods were primarily associated with crops and livestock. That is because people had been restricted access to other livelihood strategies by landmines. The landmines were often planted in rural areas and undermine the livelihoods of the rural population; limiting access to roads, land, water and forest resources. The National Landmine Impact Survey in 2002 indicates that all provinces or 2.5 percent of the country's surface are contaminated by landmines and cluster munitions (GeoSpatial International Inc, 2002). More than 45 percent of the population is at risk and over 46 percent of Cambodian villages are contaminated, with 23.7 percent rated as very severe, 24.2 percent as severe and 52.1 percent less severe.

The intensive demining efforts in the past decades have shaped the livelihood patterns and impacted the rural poverty challenge.

Second, it is a push factor or coping strategy to diversify income from other sources to overcome livelihood insecurity. Land is an important asset for both crops and livestock. However, arable land per capita has continued decreasing since 1999 (World Bank, 2016). In Cambodia, land is not equally distributed especially among the poor The variation in primary sector especially forestry reveals an important story. In the most recent year ( 2013), the extracting of resources is linked to areas where there is no substantial forest. This implies that households in non-forest zone may engage in forestrelated strategies.

Nonfarm is almost static

There is almost no variation in nonfarm self-employment in terms of overall dependency from 1999 to 2013 despite some geographical patterns of change. During the transformation process, agriculture share will gradually decline and the surplus of resources will flow to facilitate the expanding industrial and service sectors [START_REF] Chenery | Patterns of Development 1950-1970[END_REF][START_REF] Timmer | Chapter 8: The agricultural transformation[END_REF]. Nevertheless, the sectoral shift in Cambodia is a different case. Despite the relationship observed in other countries, such as India [START_REF] Hazell | Rural -urban growth linkages in India. Policy, Research, and External Affairs working papers[END_REF], Nigeria and Malaysia [START_REF] Hazell | Rural growth linkages: Household expenditure patterns in Malaysia and Nigeria[END_REF] and Sub-Saharan Africa [START_REF] Haggblade | Farm-nonfarm linkages in rural sub-Saharan Africa[END_REF], the results give no evidence of impact linkages between nonfarm activities and agriculture-based strategies, even though micro level households may undertake multiple strategies to diversify income.

In Cambodia, the nonfarm is still largely an urban phenomenon and is marginal in rural areas. With the majority of the population undertaking livelihood activities for self-sufficiency and a high poverty incidence, the transfer of surplus resources from agriculture to nonfarm activities is unlikely to substantially take place. The growing role of nonfarm is usually seen in zones of rapid growing agricultural productivity. That is because increased farm income and savings are used by households as capital investment in nonfarm activities. In addition, the increased agriculture income creates demand for agriculture inputs (machinery, fertilizers, seeds, feeds, etc.) and other goods or services, which is the cornerstone of local trade and commerce and ultimately supports the growth and emergence of entrepreneurial activities. In Cambodia, the highest poverty incidence is centered in areas where households are more primarily dependent on agriculture and natural resources such as Tonle Sap, the plateau and mountain areas [START_REF] Varis | Poverty, economic growth, deprivation, and water: the cases of Cambodia and Vietnam[END_REF]World Bank, 2006, 2014). The crops, fish catch, and aquaculture harvests are generally to smooth consumption and address food insecurity. Among the poorest households, food consumption represents two-third of household's total expenditure [START_REF] Van Brakel | Aquaculture development and scenarios of change in fish trade and market access for the poor in Cambodia[END_REF].

No significant variation in nonfarm is associated with low participation in the sector. The agriculture labor share gradually declined since 1999 (FAOSTAT, 2016).

Members of farming families are attracted by higher and more regular pay in garments and construction in urban areas instead of undertaking entrepreneurial activities (World Bank, 2015a). For example, the labor force in the garment sector has increased from 19,000 in the mid-1990s to 564,000 in 2014 [START_REF] Ilo | Growth continues for Cambodia's garment and footwear sector[END_REF][START_REF] Vixathep | Firm Efficiency in Cambodia's Garment Industry on the Eve of the Multi-Fiber Arrangement Termination[END_REF].

Conclusion

This study reveals that livelihood is context specific and suggested four distinct clusters relating to different types of resource dependency. The choice of household's strategies is associated with a range of socio and ecological factors.

The primary sector in Cambodia is substantial for the majority of the population, particularly in rural areas. People now rely more on natural resources than before while the cultivation land per capita continues to decline. Thanks to the uniqueness of the ecosystems and abundance of natural resources. The resource abundance can be both a blessing and a curse. On one hand, it indicates the significant role of environmental income in household livelihoods. On the other hand, it shows a high level of vulnerability of resource-dependent households when resources become depleted or are unsustainably managed. Nonfarm self-employment is still principally an urban phenomenon and rural nonfarm is marginal. The role of rural nonfarm will soon become more significant with continued growth in agriculture and tourism, rapid urbanization and regional economic integration.

The missing element in the peacebuilding process in Cambodia is the absence of protecting property rights and tenure and sustainable management of natural resources, as it can make the peace fragile. Cambodia is now beginning to see the effects of land tenure issues which sometimes turn violent. Even though the poverty has sharply declined in the last two decades, almost a quarter of the population is at risk of returning into poverty because of the high dependency on natural resources and wage employment from the low-skilled labors in very few sectors. In the past decades, Cambodia has put considerable efforts into accelerating growth and attracting foreign investments rather than protecting property rights and improving resource conservation. There is a fear that with increasing commercial interests and development of a market economy, the economic value of products or services is given more weight than the value of ecosystem services. If that pathway continues to follow with the conditions of weak property rights and governance mechanisms, Cambodia might face costly resource conflicts, increasing rural vulnerability, a widening social gap and division, and a poverty situation back where it was in the 1990s.

In crafting policies, it needs to be kept in mind that there are close interactions among different ecosystems. For instance, maximizing one resource system productivity (i.e. crops) may undermine the outputs of other resource systems (i.e. fishery or forestry) or vice-versa. Thus, the people may become more vulnerable through experiencing the downward spiral effects by further reducing their income from this resource system.

The results of this study can be used in several ways. Identifying socioeconomic determinants in livelihood strategies and factors contributing to success or failure of farming or natural resource-based strategies would enable households to better cope with shocks and drivers of change in each ecological zone and provide policy makers with appropriate information to feed into a more targeted poverty reduction strategy.

Furthermore, investigating the governance effectiveness of natural resources would help to prevent overexploitation, maintain the balanced ecosystems and sustainable supply of natural resources.

Introduction

After full restoration of peace in 1998, Cambodia has experienced a rapid economic growth. Between 1999 to 2013, Cambodia's economy has grown at an average rate exceeding 8% per annum. The period from 1999 to 2008 was particularly fast, achieving a two-digit economic growth rate, placing Cambodia among the world's top performers and as one of only 46 countries which have achieved an average 7% annual growth rate for 14 consecutive years [START_REF] Guimbert | Cambodia 1998-2008: An Episode of Rapid Growth[END_REF]. The Cambodian growth rate is one of the fastest among post-conflict and developing economy standards, and only below a few high performance countries such as China, Hong Kong and Singapore for some selective decades since the 1960s [START_REF] Guimbert | Cambodia 1998-2008: An Episode of Rapid Growth[END_REF][START_REF] Hill | Cambodia: Rapid growth in an open, post-conflict economy[END_REF]. Furthermore, Cambodia has tripled income per capita over the past two decades and recently graduated to lower-middle income economy. Meanwhile, the poverty rate has declined sharply from the early 1990s of more than 50% to 20% in 2011 (World Bank, 2014).

The growth rate has resulted in rapid structural change. During the early 1990s, Cambodia was primarily engaged in subsistence agriculture, dominated by rice, and its allied activities such as forestry and fishery. Almost 80% of total labor force is engaged in agriculture [START_REF] Acharya | Off-farm and Non-farm Employment: A Perspective on Job Creation in Cambodia[END_REF]. Although agriculture continues to grow, its share of GDP has been on the decline from over 50% to just about 30% over the past two decades and the share is offset by increasing role of services and industry which is principally dominated by tourism, garments and construction. At the same time, there is a rapid increase in the level of rural-urban migration. [START_REF] Davis | The rural non-farm economy , livelihoods and their diversification[END_REF][START_REF] Deininger | Rural nonfarm employment and income diversification in Colombia[END_REF][START_REF] Smith | Livelihood diversification in Uganda: Patterns and determinants of change across two rural districts[END_REF]. Households decide to diversify their livelihood strategies depending on varying socio-economic factors [START_REF] Eneyew | Determinants of livelihood strategies in Wolaita[END_REF][START_REF] Tesfaye | Livelihood strategies and the role of forest income in participatory-managed forests of Dodola area in the bale highlands, southern Ethiopia[END_REF].

The aim of the study is to use various socio-economic variables taking from the Cambodian Socio-Economic Survey in 2013 to identify the determinants of livelihood choices and total income for households in Cambodia. In this study, we adapted the Sustainable Livelihoods Analysis (SLA) approach as the framework of analysis [START_REF] Chambers | Sustainable rural livelihoods: practical concepts for the 21st century[END_REF]. The Chamber's model emphasized interactions between asset base (human, natural, physical, financial and social) and livelihoods. Poor households are often constrained access to and control of these assets in one form or another (G. M. N. [START_REF] Islam | Social capital, community based management, and fishers' livelihood in Bangladesh[END_REF]. Scholars have used the concept of SLA to study different topics of livelihood in rural development, poverty, fisheries and natural resources management [START_REF] Allison | Putting the principles of the Sustainable Livelihoods Approach into fisheries development policy and practice[END_REF]; C. [START_REF] Barrett | Dynamic Poverty Traps and Rural Livelihoods[END_REF][START_REF] Ellis | The determinants of rural livelihood diversification in developing countries[END_REF][START_REF] Erenstein | Poverty mapping based on livelihood assets: A meso-level application in the Indo-Gangetic Plains, India[END_REF][START_REF] Solesbury | Sustainable Livelihoods : A Case Study of the Evolution of DFID Policy[END_REF].

This study examines livelihood strategies from different resource dependencies.

The linkages between farm/resource-based and nonfarm strategies have recently become more popular among scholars and development practitioners, particularly in a transitional and developing economy [START_REF] Djurfeldt | Seasonality and farm/non-farm interactions in Western Kenya[END_REF][START_REF] Hitayezu | Farm households' participation in rural non-farm employment in post-war Rwanda: Drivers and policy implications[END_REF]; T. T. [START_REF] Nguyen | Rural livelihoods and environmental resource dependence in Cambodia[END_REF]. The detailed analysis of different livelihood strategies, hence, provides a good understanding of the socio and ecological interactions and how different factors might affect household's choices and income. In addition, it adds to existing literature on the role of nonfarm self-employment in rural economies of developing countries. In recent literature, the nonfarm sector is recognized to play a vital role in addressing rural-urban migration and contributing to national income growth [START_REF] Lanjouw | The rural non-farm sector: Issues and evidence from developing countries[END_REF]. Further, this study intends to investigate the relationship between migration income with different livelihood strategies. Empirical evidences from Kenya and China show that migration remittances induce the growth of nonfarm activities in rural areas [START_REF] Francis | Migration and differentiation in western Kenya: a tale of two sub-locations[END_REF][START_REF] Taylor | Migration and Incomes in Source Communities: A New Economics of Migration Perspective from China[END_REF].While some studies focus on a particular area, especially by [START_REF] Nguyen | Rural livelihoods and environmental resource dependence in Cambodia[END_REF] and [START_REF] Rahut | Non-farm employment and incomes in rural Cambodia[END_REF] in the context of Cambodia, here the analysis covers the entire country and thus contributes to the generalization of the findings.

The cross-sectoral analysis taking into account a broader view of multiple capital assets provides a useful framework for better understanding of household's livelihood choices and factors contributing to household's total income. By doing so, it offers policy makers useful information to feed into development initiatives for improving efficiency of policy interventions.

Materials and methods

Data description and study area

Our data was from the Cambodian Socio-Economic Survey 2013 (CSES).

Data analysis

The analysis of livelihood strategies of households involved several steps. In the first stage, household net income from each livelihood strategy was calculated. As evidenced in recent literature in which income share is used to measure standard of living, poverty and livelihood strategies, net income from each livelihood strategy was calculated to gain an understanding of how different socioeconomic factors influencing household's choices of livelihoods and total income [START_REF] Babulo | Household livelihood strategies and forest dependence in the highlands of Tigray, Northern Ethiopia[END_REF][START_REF] De Sherbinin | Rural household demographics, livelihoods and the environment[END_REF][START_REF] Soltani | Poverty, sustainability, and household livelihood strategies in Zagros, Iran[END_REF]. The income share method has been long recognized as an important factor to measure economic performance, especially in evaluation of household's livelihoods and to enable direct and straightforward comparison across several different years. In computing the net income from each livelihood strategy, a standard income method was followed as below:

Net Income = Total Revenue -Total Cost

The value of income or revenue is nominal. Net income in this study is equivalent to net profit accounting for both variable production and selected fixed costs, but not all. Data on some fixed expenses (depreciation) at household level were not available particularly associating with valuation of assets and their cost classification. Total revenue was calculated as Quantity of Production x Selling Price. Total cost was the sum of all cost items of each livelihood strategy.

Crops: Include all types of crops, fruits and vegetables.

Livestock: Include both livestock and poultry and by-products.

Fishery: Include aquaculture and captured fishery.

Forestry and hunting: Associate with resource extracting activities including timber and non-timber forest products.

Nonfarm self-employment: Associate with enterprise and business activities in secondary and tertiary sectors.

All statistical analyses of the data were performed using R 3.2.5. Multinomial logit regression (MNL regression) was used to identify the determinants in livelihood strategy choice because the choice is a polychotomous variable. In the MNL regression, mlogit function in mlogit package [START_REF] Croissant | {mlogit: multinomial logit model}[END_REF] was used to carry out the analysis and crop strategy was set as reference strategy as majority of Cambodian rural labor force engaging crop production strategy. Therefore, data in other strategies were all compared with this reference strategy.

The key strategy means the main livelihood strategy that households choose to earn the maximum income, normally as the resource of pursuing the main income. Therefore, key strategy, used as the response variable, could be explained by a list of explanatory socioeconomic variables. Those explanatory variables provided lots of evidences from different points of view in explaining household livelihood strategy preferences.

Therefore, the coefficients in MLR, effects of each explanatory variable contributing to the probability on choosing the specific livelihood strategy relative to crop strategy, could be observed.

Furthermore, in order to see the determinants in household's total income, ordinary least-squares regression (OLS regression) was carried out using glm function in stats package (R Core Team, 2016).

Table 2. Description of the explanatory variables used in regression analysis.

Note: Riel is the official monetary unit in Cambodia. Second, for the annual household total income, the one in forestry category is the lowest while that in nonfarm category is the highest. See also Figure 5 (upper) for this.

Results & Discussion

Characteristics of livelihood strategy

The density peak for forestry strategy, blue curve, is at the most left side and the nonfarm strategy, purple curve, is at the most right-side. The direction going from left to right side means higher annual income. Besides, from Table 3, we observe that the standard deviation (sd for short in Table 3) in nonfarm category for annual household total income differs a lot from others, performing the highest among all the categories.

Therefore, for households adopting mainly the nonfarm livelihood strategy, the income can be a lot difference across households.

When turning to study independent variables, two of them, land size and land value catch our interest. Both of them have a similar trend in distribution. Let's take land size (Figure 5, the middle one) as an example. From the figure, we can observe three patterns: one pattern works for crop and livestock categories, one stands for fishery and forestry & hunting strategies, and the last one applies to nonfarm strategy.

For the first pattern, from a starting point, the density increases to a peak and slowly decreases after that. Therefore, only few households selecting crop and livestock strategy do not have much land and most of them have large land size, 21,782 m 2 in average (Table 3). Table 3 also shows households in these groups having the largest land size with the highest land value.

In the second pattern, the curve reaches the peak at the very beginning and gradually decreases. Thus, most households adopting fishery and forestry as key livelihood strategy do not have land or own only small size of land, usually lower than 5,500 m 2 .

Households owning large land size is rare.

In the last pattern, for nonfarm dominant households, we notice some small peaks in the density in Figure 5, which means the owning of land size and land value in nonfarm group is of inequality.

Determinants in livelihood strategy choices

Results from MNL regression in Table 4 with crops set as a reference strategy present that among fifteen hypothetical explanatory variables, twelve variables were found to significantly influence the choices of household's head strategy of livestock, fishery, forestry and nonfarm.

Human capital

Overall, the results ( The positive impact of household size on fishery and forestry illustrates that with more available labor resources, households tends to choose natural resource-based activities in contrasting to crop strategy. The tendency to undertake natural resourcebased strategies with available labor resources associates with the land tenure. Land is an important asset for crops. However, arable land per capita has continued decreasing since 1999 (World Bank, 2016). In Cambodia, land is not equally distributed especially among the poor population. It is estimated that about one-third of Cambodia's land is owned by only one percent of the population (UNCDF, 2010). Overall, the average farmland is less than a hectare and with an average household size of five, the majority of the population faces a high level of vulnerability especially in rural areas.

In the case of households primarily dependent on fishery and forestry strategies, the average farmland is even as small as half a hectare. And, therefore, undertaking resource extraction and its related activities and especially among unskilled labor forces who are unable to tape more lucrative opportunities in nonfarm is viable economic option to meet increased consumption demand.

The negative impact of education on fishery and forestry relates to productivity of resource cultivation. Educated members are less willing to allocate time for either fishing or collecting and therefore are less efficient. Instead, the labor input is more allocated to more secured job opportunities such as crops or either nonfarm wage and self-employment. The results correspond with several studies in Africa and Asia confirming the negative effect of education on natural resource harvesting [START_REF] Chen | Energy consumption in rural China: A household model for three villages in Jiangxi Province[END_REF][START_REF] Fisher | Household welfare and forest dependence in Southern Malawi[END_REF][START_REF] Jogo | Determinants of rural household labour allocation for wetland and other livelihood activities: The case of the Limpopo wetland in Southern Africa[END_REF][START_REF] Narain | Poverty and the environment: exploring the relationship between household incomes, private assets, and natural assets[END_REF].

Finally, the highest poverty incidence in Cambodia is centered in areas where households are more primarily dependent on natural resources [START_REF] Varis | Poverty, economic growth, deprivation, and water: the cases of Cambodia and Vietnam[END_REF]World Bank, 2006, 2014). Therefore, the poor resource or less educated households may have limit ability to improve knowledge and skills and access to various opportunities.

Further to education, the positive relationships between non-formal education and nonfarm show an important story of farm exit. With more members attending non-formal education, it is more likely that households exit crop cultivation into different subcategories of nonfarm employment. Among those attended the programs, only 2.1% participated in agricultural-related trainings contrary to foreign languages accounting for 86.7%. The figure is even lower than vocational training and computer literacy representing 5.9% and 3.5%, respectively. The factors influencing the nonfarm choice associate with income security which has been constrained in crop cultivation.

The significantly negative effect of female percentage on fishery strategy implies that the strategy is more likely to be chosen by households with less female percentage comparing to crops. A number of socio, economic and cultural taboos shape the participation of women in fisheries and its related activities., in the synthesis of 83 global gender fisheries studies, [START_REF] Kleiber | Gender and small-scale fisheries: A case for counting women and beyond[END_REF] showed men are more representative in number and better perform in terms of catch biomass, fishing effort and catch per unit effort (CPUE). Secondly, women are restricted in decision making power in the management of fishery resources and aquaculture activities which therefore deprive access to and economically benefit from the resources [START_REF] Harrison | Fish and Feminists[END_REF][START_REF] Heck | Investing in African fisheries: Building links to the Millennium Development Goals[END_REF][START_REF] Choo | Guest Editorial: Gender and Fisheries[END_REF] .Thirdly, the physicality, dangers and family roles [START_REF] Brickell | The "stubborn stain" on development: gendered meanings of housework (non-)participation in Cambodia[END_REF]) limit women's ability to travel long and far and female fishers likely to choose habitats which are close to home (Arce-Ibarra & [START_REF] Arce-Ibarra | Inland fisheries of the Mayan Zone in Quintana Roo, Mexico: Using a combined approach to fishery assessment for data-sparse fisheries[END_REF][START_REF] Béné | Fish as the "bank in the water" -Evidence from chronic-poor communities in Congo[END_REF]. In addition, women may also be further narrowed by the use of fishing methods and gears as compared to their male counterparts. In Cambodia, different ecological characteristics define the gender participation in fishing and fish farming. Women in Tonle Sap Great Lake are more active in fish processing and fishing in resource grounds nearby their home, and in coastal areas engage in collecting aquatic resources, while those in the Mekong River floodplain region travel along with their husband since the fishing activities are concentrating in a short period between September to December [START_REF] Béné | Poverty in small-scale fi sheries: old issue, new analysis[END_REF][START_REF] Fa/Maff | Gender implication in CBNRM -the roles, needs and aspirations of women in community fisheries[END_REF]. In some areas, where fishing is carried out at night, women do not participate in the fishing.

The positive relationship between age of household head and fishery strategy can also be explained by the willingness to supply labor input to use in resource harvesting.

Fishing requires travelling to resource ground and therefore elder people prefer to stay at or nearby home which enable them to take care home and young children in the family and allow other working age family members to work off-farm. The results are supported by the findings of [START_REF] Shi | Choices between different off-farm employment sub-categories: An empirical analysis for Jiangxi Province, China[END_REF] in China, reporting that older people are more likely to work in agriculture and local nonfarm employment while the younger labors prefer to migrate or work away from home.

Natural and economic capital

For natural and economic measure, land and expenditure on food and non-food items have significantly affect the four livelihood choices (Table 4). For food and non-food expenditure, the positive correlations were found to be associated with nonfarm and livestock while forestry was negatively influenced by food expenditure.

Regarding how expenditure patterns might influence household's choice of key strategy, the positive effect of non-food expenditure on livestock and nonfarm indicates that the two strategies are likely chosen by the better-off households in opposite to crop cultivation. Furthermore, the positive effect of food expenditure on nonfarm also explain the household decision associating own consumption, food expenditure and land constraint. From the food intake perspective, the increased food consumption for nonfarm choice may indicate the level of income which allows households to purchase foods to meet their needs. Other reasons associate with urban areas where households are less likely food producers or in rural areas where households face land constraint and therefore push them to undertake nonfarm as their primary choice. Similarly, the negative relationship between food expenditure and forestry shows that households with sufficient food production may not engage in forestry. The constraint in food production because of limited farmland tenure and the energy requirement to meet their basic needs enable households to choose forestry strategy instead of farming.

The results showing the statically significant correlations between both land size and value and the four livelihood strategies indicate the importance of land tenure in household's choices of strategy in Cambodia. Households with larger farm size are less likely to invest in other strategies such as livestock, forestry or nonfarm. The results correspond to evidence in Nigeria that households with large farm size reduce their participation in off-farm [START_REF] Fabusoro | Forms and Determinants of Rural Livelihoods Diversification in Ogun State, Nigeria[END_REF].

Similarly, there is also similar pattern for land value variable. The total land value reflects both the size and monetary value of the land owned by households. The monetary value indicates the capacity of households to access to credit or convert the assets into financial capital to further invest or expand the existing crop production activities.

The financial capital is important for farmers to access to technology and improve specialization or expand the current production capacity which in turn contributes to generate higher income. Consequently, those with larger farm size are less likely to make a choice in other strategies considering the level of returns derived from crop cultivation. The finding also provides important implication why some household might exit the traditional on-farm job and seek alternative options in off-farm employment.

Social capital

Among the two social capital measures, only remittance was found to be statistically significant associating with fishery strategy and nonfarm (Table 4). Remittance positively correlates with fishery and has negative effect on nonfarm.

The positive relationship between remittance and fishery strategy revealed that the fishery households are more dependent on migration income than those of crops. Fishery-dependent families send more members out for other employment as it can be observed from Table 3 that average migration income receipt was the highest among all other strategies. The declining environment resources and economic uncertainty force members in fishery-dependent households to diversify income sources to support their needs. On the other hand, the pattern is opposite for nonfarm in which households are less dependent on migration income. That is because nonfarm is considered to be more lucrative and secure and less risk than both crop and fishery strategies.

Physical capital

The effects of various physical capital on the choices of livelihood strategies were found to be statistically significant associated with forestry and nonfarm (Table 4). For both livestock and fishery, the influencing factors were similar to crop strategy. The result showing the negative effect of agriculture equipment on nonfarm is as expected.

However, the strong correlation between household durable goods with nonfarm strategy indicates the difference of durable goods consumption behavior and income between crop and nonfarm dependent households. The more ownership of durable goods of nonfarm households reflects the higher income level because the ownership of goods associating with income change or rise which enables households to have more possession of goods as presented in Table 3 and Figure 5.

For forestry households, the result shows a different situation from nonfarm strategy. The negative effect of transportation on forestry strategy highlights that the households making a decision to participate in forestry are short of transportation ownership compared to those in crops.

Determinants of household income

Crops as key strategy

For households following crop strategy, the determinants of household income are various (Table 5). The increase of land size and value, age of household head and agriculture equipment contribute to higher income whereas the increase of remittance and female percentage negatively affect household's total income.

As land is the primary productive capital for crop cultivation, land size indicates the scale of farming operation. The larger farm size enables household to cultivate and produce more and ultimately results in a higher return. Owning a large land size and high land value is also another incentive for farming households. In developing countries, including Cambodia, land-rich households use land as a collateral for loans to finance their farming investment [START_REF] Rahman | Determinants of Livelihood Choices: An Empirical Analysis from Rural Bangladesh[END_REF]. The loans are used for farming operation costs, purchasing tools and machinery or expanding the investment to generate more household income.

The positive relationship between age of household head and total income associate with improved specialization through the number of years engaging in crop production.

Specialization is a key for farming success as it enables households improve productivity and increase production income.

The positive impact of farm machinery on household's total income is not surprising as the mechanical tools increase overall crop output. The reason is because the mechanical system improves crop productivity and efficiency during both pre and postharvest and it is important for Cambodia farmers of which a significant percentage are resource-poor, lacks access to agriculture equipment and still operates manually.

It is surprising to note that remittance negatively affect total income of crop dependent households. The migration income was thought to improve farming productivity and ultimately contribute to increased household income. The migration income may influence the reallocation of labor or resources out of farming. In some cases, the trend may lead to farm discontinuation as it depends on the share of remittance income.

This holds true when the agriculture labor share has gradually declined since 1999 (FAOSTAT, 2016). Members of farming families are attracted by higher and more regular pay in garments and construction in urban areas (World Bank, 2015a).

The reason of negative impact of number of female on total income is related to gender difference in overall productivity and access to resources. Several studies in developing countries reveal that plots managed by females are less productive than those managed by their male counterparts [START_REF] Andrews | Inefficiency of male and female labor supply in agricultural households: Evidence from Uganda[END_REF][START_REF] Kilic | Caught in a Productivity Trap: A Distributional Perspective on Gender Differences in Malawian Agriculture[END_REF]. However, [START_REF] Alene | Economic Efficiency and Supply Response of Women as Farm Managers: Comparative Evidence from Western Kenya[END_REF] stressed that gender difference in productivity is not associated with the technical and allocative efficiencies, but on how female farmers access to various capital assets. A large and growing volume of studies confirmed that women are constrained access to land, education, labor, credit and extension services [START_REF] Bindlish | Evaluation of the Performance of T & V Extension in Kenya[END_REF][START_REF] Birkhaeuser | The economic impact of agricultural extension: A review[END_REF][START_REF] Doss | Designing agricultural technology for African women farmers: Lessons from 25 years of experience[END_REF][START_REF] Quisumbing | Male-Female Productivity: Differences in Agricultural Issues and Empirical Evidence[END_REF] and therefore affect their crop output and income.

Livestock as key strategy

As in the livestock category, land value has a significant positive effect on household total income whereas education has a negative relationship (Table 5). Land ownership does not only provide the production base which eventually turns into higher income, but it offers means to access to capital investment. [START_REF] Samkol | Survey of smallholder beef cattle production systems in different agro-ecological zones of Cambodia[END_REF] high-lights that one of the main constraints in livestock production is financial capital. Therefore, for households owning high land value are more accessible to credit or financial capital for the production. Furthermore, the total high land value also reflects the zones usually situated close to the cities and towns where are fast growing and have higher demand for meat consumption. As majority of Cambodian livestock farms are smallscale, the urban and peri-urban areas accommodate larger and more advanced commercial operation farms with higher economies of scale and therefore enable them to achieve higher rates of return.

Associated with the effect of education on total income, the educated members

Fishery as key strategy

In the case of households whose key strategy is fishery, education affects income negatively and ownership of transportation affects positively (Table 5). Higher education is associated with possibility of higher skilled and more secured employment.

Therefore, fishery income is not considered as the most favorable economic option and households seek employment from other more secured sources. As explained earlier, the overall low output of natural resource collection is associated with more educated households because of job preference, efficiency and labor allocation [START_REF] Chen | Energy consumption in rural China: A household model for three villages in Jiangxi Province[END_REF][START_REF] Jogo | Determinants of rural household labour allocation for wetland and other livelihood activities: The case of the Limpopo wetland in Southern Africa[END_REF].

In contrast, transportation provides mean to better access to fishing ground and market and to less depend on the middlemen and therefore contribute to generation of higher household income. When the availability of environmental resource become scare, the transportation (i.e. fishing boats and other vehicles) plays a critical role to maintain household income as fishers may need to travel further from the normal resource ground for fishing or access inputs for fish farming.

The results are supported by the findings of [START_REF] Nguyen | Rural livelihoods and environmental resource dependence in Cambodia[END_REF] providing evidence that education negatively affect environmental income while fishing boats and proximity to resource ground have a positive impact.

Forestry as key strategy

Turning to households with forestry & hunting as key strategy, the total income is influenced by household size, land size, agriculture equipment, non-food expenditure and durable goods (Table 5). The first three indicators have positive effects whereas the two latter have negative effects on total income.

The positive influence of household size on forestry total income reveals the availability of labor resources engaging in forestry activities which thus enable households to generate more income for the households.

As majority of natural resource based households are still subsistence, diversification into farming is a viable means to ensure household income stability. Especially among the poor households who are unable to seek more other lucrative jobs such as nonfarm. Therefore, land and agriculture equipment enable them to diversify into farming which contribute to increased income especially when the environmental resources become scare. The finding is consistent with global comparative study by [START_REF] Angelsen | Environmental Income and Rural Livelihoods: A Global-Comparative Analysis[END_REF] showing the positive correlation between agriculture land with forest and environmental income. However, it is contrary to evidence found by [START_REF] Nguyen | Rural livelihoods and environmental resource dependence in Cambodia[END_REF] in Cambodia and [START_REF] Kamanga | Forest incomes and rural livelihoods in Chiradzulu District, Malawi[END_REF] in Malawi, in which no correlation were found between land size and forest income.

The negative impact of non-food expenditure and household assets on total income for forestry households reflects how forestry income are influenced by different levels of wealth of households. The higher expenditure on non-food items and more ownership of assets indicate a better human well-being. Therefore, the better-off category of households might not make best use of available labor resources for forestry as earlier explained. The forestry and its related income come from most of the poor households.

Nonfarm as key strategy

For households mainly involved in the nonfarm employment, food and non-food expenditure and durable goods have positive effect on total income while age of household head, non-formal education and illness have the negative relationship (Table 5).

The findings show that human capital plays a key role in influencing income from nonfarm. Households with better human capital and with more assets have better coping (short-term) and adapting strategies (long-term) than those in the opposite situation.

Therefore, they have greater access to nonfarm jobs and earn more income. Nevertheless, education, one important indicator of human capital, shows no significant relationships for both choice and income of households, contrasting previous literature arguing the significant influence of education on nonfarm [START_REF] Corral | Rural Nonfarm Incomes in Nicaragua[END_REF]; [START_REF] Rahut | Non-farm employment and incomes in rural Cambodia[END_REF]).

The positive effect of food and non-food expenditure and durable goods show that wealth is important in the present economic structure of Cambodia in which entrepreneurs are generally constrained by access to investment capital. Even credit can be easily accessible, the interest rate remains high and sometimes limit the opportunity to be competitive.

On the negative relationships, the significant effect of age of household head highlights that younger entrepreneurs might be more successful than the older head in the Cambodian economy which is rapidly developed and changed. While older head might have more experience and better resources, the younger counterparts are more willing to take risk and more responsive to emerging opportunities in the rapidly transforming economy. Associated with non-formal education, the negative impact on total income highlights a gap in the skill building programs to promote non-farm self-employment in which the majority of people took foreign languages ahead of others. This suggests that people prefer the wage employment in foreign countries instead of entrepreneurial activities [START_REF] Mop | Report of Cambodia Rural Urban Migration Project[END_REF]World Bank, 2015a). Finally, the illness variable shows that nonfarm total income is negatively affected by the number of day family members absent from work. Nonfarm is mainly associated with urban areas and the residents suffer more illness and injuries than those in the rural areas.

Conclusion

Our findings mainly reveal two aspects: the determinants of the household's livelihood choices and household's total income derived from such choices in Cambodia.

Using the sustainable livelihood framework, this study contributes to understanding how different household capitals influence household's decision to undertake relevant livelihood strategies and the factors affect the overall household income based on the choice being made.

Household choices of strategy

Various elements of livelihood assets affect household's choices differently comparing to crop cultivation. Household size, food and non-food expenditure, education and female percentage are found to be important human capital which influence or dis- Remittance is found statistically important for forestry and nonfarm but in an opposite situation. The negative effect of migration income on household's decision to participate in non-farm self-employment is as expected because of high returns from the strategy. However, the positive relationship between remittance and fishery choice of strategy reveals an important evidence associating with increasing economic pressure of the households in which more members are being forced to leave home for alternative employment.

The results draw the following important policy implication. First, development interventions with special attention to resource poor households, aiming to improve human capital and asset ownership would enable them to enhance their potential for employment in farm or nonfarm sectors and minimize the potential risks from the environment pressure because higher risk of vulnerability associating with livelihood inequality, lower human capital and productive assets (i.e. land).

Second, land is an important livelihood capital which strongly influence household's decisions to participate every choice of strategy. The missing element in the Cambodia's development process is the absence of protecting property rights and tenure. Cambodia is now beginning to see the effects of land tenure issues which sometimes turn violent. Even though the poverty has sharply declined in the last two decades, almost a quarter of the population is at risk of returning into poverty because of the high dependency on natural resources and wage employment from the low-skilled labors in very few sectors, and low capacity to respond to unexpected environmental events. In the past decades, Cambodia has put considerable efforts into accelerating growth and attracting foreign investments rather than protecting property rights and improving resource conservation. There is a fear that with increasing commercial interests and development of a market economy, the pathway might be continued. With the conditions of weak property rights and governance mechanisms, Cambodia might face costly resource conflicts, increasing rural vulnerability, a widening social gap and division, and a poverty situation back where it was in the 1990s.

Lastly, promoting non-formal education geared towards skill building and entrepreneurial development activities will enable households to diversify non-environmental income (i.e. nonfarm) which is more financially rewarding and secure.

Household's total income

Different policy options apply since household's livelihood strategies are shaped by specific socioeconomic and agro-ecological contexts. We should avoid enhancing a one-size-fit prescription without consideration a wide range of influencing factors.

Of households with crop as a key strategy, improving household's land ownership (land size and value), productive assets (i.e. agriculture equipment) and farmer experience contribute to increased total income. On the other hand, the increased female participation in crop cultivation and remittance negatively affect the household's total income. The findings suggest that the policy should aim to increase farm income (not just for subsistence purposes) by improving specialization, labor efficiency, assets (land), machinery and access to credit. Raising value of land may provide the financial capital for the crop cultivation, but it affects the land accessibility because of increased price.

Improved farm income enables households to less depend on migration income which may contribute to farm exit.

For livestock depending households, land value being significant in influencing total income indirectly suggest that improving access to financial capital would help to address major challenges faced by livestock producers. Access to credit especially among livestock smallholders is crucial in addressing typical production constraints such as animal nutrition and health, which are not only main barriers to profits and improving production process, but also to new entry.

The positive relationship of transportation and negative impact of education on fishery households suggest that improving physical ownership (i.e. fishing boats) is more desirable (perhaps in the short-term) than addressing education. Transportation such as fishing boats provides means to access to resources and market and therefore affect household's income. Nevertheless, education is still important for households to income diversification. Education remains important in enabling households to better adapt to climate variability based on their biophysical and socioeconomic circumstances.

For households with forestry as a key strategy, land and household sizes have positive impact on total income while non-food expenditure and other durable goods have negative relationship. The results clearly suggest that improving more land access would significantly contribute to improving income and livelihood of the households.

With poor resource governance, the increased commercial interest of land would undermine the land accessibility among the poor. We do suggest the targeted poverty reduction strategies should aim to improve land access for those living under the poverty line. Furthermore, measures to improve productivity for non-timber forest products, including post-harvest losses and market effectiveness would not only improve current production, but provide potential opportunities to diversify into farm income and other earning opportunities.

For nonfarm, food and non-food consumption and durable goods were found to be important to household's total income while age of household head, non-formal education and illness were the opposite factors. The results suggest that the success of nonfarm self-employment differs according to household wealth. Richer households are more profitable because of better financial strength. Other actions which contribute to increase nonfarm income include minimizing health risks and non-improving formal education programs as earlier discussed. Furthermore, government should formulate policies aiming to establish precondition for rural nonfarm growth such as effective decentralized decision systems and improved supporting infrastructure, insurance and credits. Promoting growth of rural nonfarm is not only beneficial for the poor and rural economy, but it gradually helps to improve specialization and a large benefit falls on national economy as a whole.

Introduction

Tonle Sap Lake is the largest and most important freshwater lake in the Mekong basin, and the center of Southeast Asia's freshwater biodiversity. It is particularly crucial for supporting livelihoods, food security, and trade for Cambodian society [START_REF] Baran | Cambodia inland fisheries: facts, figures and context[END_REF][START_REF] Cooperman | A watershed moment for the Mekong: newly announced community use and conservation areas for the Tonle Sap Lake may boost sustainability of the world's largest inland fishery[END_REF][START_REF] Keskinen | The Lake with Floating Villages: Socio-economic Analysis of the Tonle Sap Lake[END_REF], where 80% of animal protein consumed by humans is derived from freshwater animals [START_REF] Hortle | Consumption and the yield of fish and other aquatic animals from the Lower Mekong Basin[END_REF], the majority of which comes from the Tonle Sap [START_REF] Baran | Fish resources in Cambodia (2001-2011). In Atlas of Cambodia -Maps on socioeconomic development and environment[END_REF].

Fishing and agricultural activity around the Tonle Sap is driven by the flood pulse from the Mekong River, which inundates the floodplain every year for several months.

Tonle Sap fishery resources have decreased substantially over time due to a growing rural population and illegal and unsustainable fishing activities [START_REF] Nguyen | Rural livelihoods and environmental resource dependence in Cambodia[END_REF][START_REF] Travers | Incentives for cooperation: The effects of institutional controls on common pool resource extraction in Cambodia[END_REF]. Consequently, rural livelihoods have become increasingly impaired, and many fishing households remain entrenched in poverty [START_REF] Johnstone | Tonle Sap scoping report[END_REF]. Climate change and ongoing dam construction in the Mekong River Basin is projected to alter water levels and modulate the river's flood-pulse, thereby impacting fish biodiversity and ecosystem productivity across the entire Basin [START_REF] Arias | Impacts of hydropower and climate change on drivers of ecological productivity of Southeast Asia's most important wetland[END_REF][START_REF] Arias | The flood pulse as the underlying driver of vegetation in the largest wetland and fishery of the mekong basin[END_REF][START_REF] Ziv | Trading-off fish biodiversity, food security, and hydropower in the Mekong River Basin[END_REF]. Livelihoods dependent on the Tonle Sap floodplain ecosystem are thus likely to be adversely impacted by future socio-economic, policy, ecological, and climate change [START_REF] Arias | Impacts of hydropower and climate change on drivers of ecological productivity of Southeast Asia's most important wetland[END_REF][START_REF] Salmivaara | Socio-Economic Changes in Cambodia's Unique Tonle Sap Lake Area: A Spatial Approach[END_REF]. This is of concern given that the Tonle Sap Zone already has a higher poverty incidence than the national average (JICA, 2010).

Within the global change literature, the extent to which people are vulnerable to climate and socioeconomic change is dependent on one's exposure (likelihood of being impacted), sensitivity (dependence on natural resources), and capacity to adapt to likely impacts [START_REF] Adger | Vulnerability[END_REF]. Cambodia is classified as being highly vulnerable to the effects of climate change on fisheries [START_REF] Allison | Vulnerability of national economies to the impacts of climate change on fisheries[END_REF]. Poverty, marginalisation, and lack of alternative livelihoods impede fishing communities' ability to cope with changes in fishery productivity [START_REF] Baran | Climate change and fisheries: vulnerability and adaptation in Cambodia[END_REF]. A prior survey of the Tonle Sap Lake area found that up to 90% of respondents were extremely vulnerable to shocks, and 50% of households would fall in extenuating circumstances in the event of heavy rainfall, floods, or local droughts (GFA Consulting Group, 2007). Hence, building up adaptive capacity of natural resource dependent livelihoods is imperative to help reduce this vulnerability. Addressing vulnerability can also incentivize participation in more sustainable resource management [START_REF] Baran | Climate change and fisheries: vulnerability and adaptation in Cambodia[END_REF].

Developing adaptation strategies to overcome vulnerability requires an understanding of how people will respond to future changes. The research directly addresses this issue from an economic perspective by investigating the benefits and costs of Tonle Sap inhabitants' adaptive responses to four scenarios of future socio-economic and climate change. We analyze these economic outcomes by different livelihood groups and village zones in order to understand which groups are most vulnerable and hence have the least capacity to adapt to future change.

Tonle Sap fisheries

Approximately 2 million people participate in the Tonle Sap Lake fishery [START_REF] So | Fisheries management and development in Tonle Sap Great Lake, Cambodia[END_REF], which targets multiple species using a wide variety of gears. The dominant gears are gillnet, cast net, hook line, and small traps, while the main targeted fish species include lesser silver mud carp (Henicorhynchus lobatus), striped snakehead (Channa striata), snail eating barb (Puntioplites proctozysron), and blackskin catchfish (Clarias meladerma) (Bond, 2015). Fisheries in the lake are essentially open access (Ratner, 2006a). Fisheries deregulation in 2012 turned over all commercial fishing lot licenses to community managed fishing areas. Nevertheless, poor enforcement and management capacity has resulted in the persistence of intense competition for fishery resources, leading to intense exploitation and chronic illegal fishing [START_REF] Johnstone | Tonle Sap scoping report[END_REF]. Declining fish size, catch per unit effort, the elimination of large and commercially valuable species and increasing prevalence of less desirable species are all indicators that the sustainability of Tonle Sap Lake fisheries has deteriorated [START_REF] Cooperman | A watershed moment for the Mekong: newly announced community use and conservation areas for the Tonle Sap Lake may boost sustainability of the world's largest inland fishery[END_REF][START_REF] Enomoto | Data mining and stock assessment of fisheries resources in Tonle Sap Lake, Cambodia[END_REF]. Further, a rapidly growing population, up-river dam development, an expanding agro-industry in the upper watershed, and climate change will almost certainly impose further pressures on fish populations in Tonle Sap Lake [START_REF] Cooperman | A watershed moment for the Mekong: newly announced community use and conservation areas for the Tonle Sap Lake may boost sustainability of the world's largest inland fishery[END_REF], posing a threat of fisheries collapse.

Households in the vicinity of Tonle Sap Lake primarily engage in small-scale artisanal and subsistence fishing, with supplemental income from agriculture, raising livestock, aquaculture, off-farm work, and remittances (Bond, 2015;[START_REF] Keskinen | The Lake with Floating Villages: Socio-economic Analysis of the Tonle Sap Lake[END_REF]). Yet, many of the poorest households depend on one livelihood, which is generally fishing [START_REF] Nuorteva | Water, livelihoods and climate change adaptation in the tonle sap lake area, Cambodia: Learning from the past to understand the future[END_REF]. Floating villages are particularly dependent on fisheries resources, and their limited access to land resources, education, and livelihood options make them especially vulnerable to ecological change [START_REF] Nuorteva | Water, livelihoods and climate change adaptation in the tonle sap lake area, Cambodia: Learning from the past to understand the future[END_REF]. Almost 70% of floating households on Tonle Sap Lake were classified as being low-wealth (Bond, 2015), where wealth was an index measuring household location, diet diversity, and livelihood strategy. Lower income Tonle Sap fishers, therefore, exemplify a vulnerable population. In contrast, richer households were typically not as reliant on fishing as their main income source (Bond, 2015). While inhabitants around the Lake have adapted to seasonal changes of the lake, they have poor capacity to react to irregular environmental events [START_REF] Nuorteva | Water, livelihoods and climate change adaptation in the tonle sap lake area, Cambodia: Learning from the past to understand the future[END_REF].

A previous survey of Tonle Sap fishing households found that fish catch was not perceived to be decreasing, but there had been a noticeable decrease in sizes and diversity of the fish caught (Bond, 2015), indicating that fish populations are under stress [START_REF] Mccann | Food webs and the sustainability of indiscriminate fisheries 1[END_REF][START_REF] Pauly | Fishing Down Marine Food Webs[END_REF]. However, most households were not able, or willing to change their livelihood strategy because they did not have the necessary resources to adapt to long-term changes in their livelihoods (Bond, 2015). Based on spatial analysis and qualitative interview data, Bond (2015) showed that many fishing households, especially those in floating villages and at lowest wealth levels, faced uncertain futures because they will not have alternative livelihoods to turn to for income and subsistence in the event Tonle Sap Lake fisheries collapse. We add an economic perspective to these findings by conducting an economic analysis of fishing households' adaptive responses to scenarios of future socioeconomic and environmental change.

Materials and methods

Field interviews

Interview data used in this study were based on field work carried out in Cambodia in 2014, and is detailed in Bond (2015). Briefly, household surveys were conducted in three districts of Pursat province (Krakor, Kandieng, and Bakan). Pursat is located in western Cambodia, and has one of the largest coastlines along Tonle Sap Lake (Figure 6), as well as the third highest density of fishers around the Lake [START_REF] Baran | Fish resources in Cambodia (2001-2011). In Atlas of Cambodia -Maps on socioeconomic development and environment[END_REF].

Poverty is widespread, as 40% of the population in Pursat is below the absolute poverty line (JICA, 2010). This province was chosen because it is an important tributary and fishing location, and remains largely untouched by tourism and development. Fishing is the primary livelihood for a large portion of the Pursat population, making them particularly vulnerable to changes in the flood pulse and degradation of lake resources. As the aim of Bond's (2015) study was to understand peoples' adaptation to changing fish populations in the Tonle Sap, villages in the three districts were selected if they had a Fish Dependency Score 1 (J. [START_REF] Nasielski | Role and value of fish in the welfare of rural communities in Cambodia: Questionnaire development[END_REF]) of 0.5 or higher. Based on this criteria, 26 villages were selected; each village contained households which either fished in the lake, in a main tributary, or in the floodplain during the wet season. Selected villages were all located between the Tonle Sap Lake and National Road #5, which is 4-40 km from the Lake. The selected villages were located along the Pursat River, on the water (floating villages), and in the floodplain. Villages were categorized into 5 zones according to their distance from the National Road (Table 6). The 1 The Fish Dependency Score indicates the probability of randomly selecting a fishing household in a village. It is calculated by multiplying the ratio of fishers: total village population by the village's poverty score (Nasielski et al.2013).

distance range covered by each zone was subsequently allocated to achieve as equal a distribution of villages as possible within each zone. At each selected village, household names were randomly selected from village lists to complete the surveys. A total of 181 households surveys were conducted, based on a sample size requirement of S= N/(n*2), where S = number of households that had to be selected in a village, N = the total number of village households, and n = the number of households needed. In total, 67% (n=122) and 33% (n=59) of surveyed households were located on water and land, respectively.

The surveys aimed at understanding household demographics, livelihood strategies, and perceptions of change around the lake and the adaptive capacity of households.

This study focuses on the questions pertaining to livelihood strategies and future scenarios of the Tonle Sap. As the surveys conducted by Bond (2015) focused on understanding fishing activities on the Lake, we grouped respondents into three groups according to their reliance on fishing: Group 1 = Fishing only; Group 2 = Fishing + Farming and/or Off-farm work; Group 3 = Non-fishing work.

It is noted that this division resulted in unbalanced groups, with 55, 114, and 12 respondents in groups 1, 2, and 3, respectively. In general, respondents involved in farming lived in the floodplain parallel to National Road #5, while non-farming respondents lived closer to the lake, parallel to Pursat River. Those involved in fishing only tended to live in the middle of the lake, whereas those that were involved in both fishing and other work lived on the shoreline of the lake or in the floodplain (Bond 2015).

Economic analysis

We first estimated the net income from respondents' current livelihoods and compared this to net income derived from reallocating their livelihood activities under 4 scenarios depicting future change. We then investigated patterns of respondents' net income under two vulnerability indicators-livelihood diversification and village distance to the National Road. Livelihood multiplicity is a common measure of vulnerability of fishing and other natural resource dependent communities [START_REF] Badjeck | Impacts of climate variability and change on fishery-based livelihoods[END_REF][START_REF] Cinner | Vulnerability of coastal communities to key impacts of climate change on coral reef fisheries[END_REF][START_REF] Hahn | The Livelihood Vulnerability Index: A Pragmatic Approach to Assessing Risks from Climate Variability and Change -A Case Study in Mozambique[END_REF]; M. M. [START_REF] Islam | Vulnerability of fisherybased livelihoods to the impacts of climate variability and change: Insights from coastal Bangladesh[END_REF][START_REF] Mcclanahan | Identifying reefs of hope and hopeful actions: Contextualizing environmental, ecological, and social parameters to respond effectively to climate change[END_REF]. Distance from the National Road was used as a vulnerability indicator because people located closer to the National Road were found to in a better situation than those living closer to Tonle Sap Lake in terms of being able to reduce their vulnerability, i.e., they had more livelihood options, better education, wealth, and agricultural land ownership (GFA Consulting Group, 2007).

Net income from current livelihood activities

To estimate the net income each respondent obtained from their current livelihood activities, revenue and cost data were extracted from the household surveys for 3 nonfishing livelihood activities: i) agriculture (wet rice, dry rice, maize, cassava, beans, other vegetables); ii) raising livestock (cattle, buffalo, pigs, poultry); and iii) aquaculture.

Revenue (R) obtained from each activity was calculated as: R = P x Q, Where P = selling price and Q = quantity; and [START_REF] Kummu | Impact of the Mekong River Flow Alteration on the Tonle Sap Flood Pulse[END_REF]; these flow alterations would likely result in ecological disruptions, as they would affect crucial biological factors such as fish migration and tree seed germination. Meanwhile, future scenarios of water infrastructure development and climate change projected reduced spatial extent of seasonally flooded habitats and forests while favoring rain-fed irrigated agricultural areas [START_REF] Arias | Quantifying changes in flooding and habitats in the Tonle Sap Lake (Cambodia) caused by water infrastructure development and climate change in the Mekong Basin[END_REF].

Hydrological changes were expected to have a drastic impact fisheries production in the Lakefor instance, [START_REF] Sarkkula | DMS -Detailed Modelling Support Project[END_REF] found that there was a high risk that all migratory fish would vanish if mainstream dams were built. Moreover, it was estimated that migratory fish biomass would decline by up to 51% by 2030 under different scenarios of hydrological development [START_REF] Ziv | Trading-off fish biodiversity, food security, and hydropower in the Mekong River Basin[END_REF]. The anticipated decline in fish catches, decreased farm productivity, and landlessness were expected to reduce livelihood opportunities and increase migration from Tonle Sap Lake to urban centers [START_REF] Heinonen | Environmental Impact on Migration in Cambodia: Water-related Migration from the Tonle Sap Lake Region[END_REF], with Phnom Penh being the most sought out destination of both rural and urban migrants [START_REF] Mop | Integration of Demographic Perspectives in Development, Cambodia[END_REF].

To reflect changes in the flood pulse and the potential outcomes from ongoing hydrological development in the Upper Mekong Basin, climate change, and urbanisation, four hypothetical scenarios were developed. Respondents were told that each scenario occurred in the future, although there was no specific time frame associated with the scenarios. The four scenarios were:

Scenario A (Less fish) -A 50% reduction in fish production in Tonle Sap Lake.

Scenario B (More farm land) -An increase in agricultural land due to changes in flood plain habitats.

Scenario C (Urbanization) -The creation of more jobs due to urbanization and increased economic activities in urban centers, particularly in Phnom Penh.

Scenario D (Stagnation) -The status quo is retained, i.e., same situation as today.

3a. Renting new land -Based on literature, an extra 33% was added to total crop farming costs to account for rental cost. This was estimated based on a socio-economic assessment of rice farming conducted in 3 Cambodian provinces (Asian Development Bank, 2012). The study provided average rental cost per area, and average rented areas for well-off, medium, and poor households. We applied the rental data for poor households.

3b. Upland farming -Upland farming costs are expected to be different from lowland farming because average upland farm sizes tend to be larger, and the farming system used also differs from lowland farming [START_REF] Farquharson | Sustainable Livelihoods Approach in tropical coastal and marine social-ecological systems: A review[END_REF]. A 2006 study on improving upland crop technology in 5 districts in Battambang and Kampong

Cham Provinces (close by to Tonle Sap) estimated that on average, the per hectare variable costs for growing non-rice crops accounted for approximately 79% of revenue [START_REF] Farquharson | Sustainable Livelihoods Approach in tropical coastal and marine social-ecological systems: A review[END_REF]. Across all districts, the average gross margin (revenuevariable costs) was 2.4 million Riel. As no fixed cost was provided, we used gross margin as the best estimate of net income from upland farming.

Results

Demographics and current time allocation to livelihoods

The average household size was 5.2, with 62% of households having 5 or fewer members. Group 3 respondents had fewer household members (3.7) than groups 1 and 2, which both had an average of 5.3 household members. The majority of household heads were male, with 41% headed by women. The average age of respondents was 45.

Most respondents (83%) had primary school education, with only 2% having completed secondary school. Three quarters of respondents were ethnic Khmer, 22% were Vietnamese, and the remaining 3% were Cham. Thirty-four percent of respondents undertook one livelihood activity only. Of these, the majority were engaged in fishing only (90%), with the remainder engaged solely in either farming or off-farm work. Across all respondents, the most time (average 47%) was currently allocated to fishing activities, followed by agriculture (31%), off farm work (18%), and lastly to aquaculture (4%).

Net income from current livelihood activities.

Fishing was the livelihood activity with the highest participation rate (93% of all respondents), and provided on average an annual net income of 1.8 million Riel (USD 440). Vegetable crop farming and off-farm work had the lowest participation rates, at 3% and 16%, respectively. Off-farm work also provided the lowest average net annual income. The highest average net income was derived from livestock rearing (about 2.1 million Riel or USD 514 annually), but less than half the respondents participated in this activity (Figure 7). The overall average annual net income from all livelihood activities was 3.6 million Riel (USD 892). Both livelihood groups 1 (fishing only) and 2 (fishing + other activity) had comparable annual net income levels of 3.9±0.6 and 3.7±0.9 million Riel, respectively. Average net income for group 3 (non-fishing livelihood) was only about one third the level of the other two groups (1.3±0.6 million Riel), but the difference between groups was not statistically significant (Figure 8).

Net annual income under future scenarios

Change in livelihood allocation

For all scenarios, the majority of respondents chose to retain their current livelihood allocation. Scenario C (Urbanization) resulted in the highest proportion of respondents (47%) changing their current livelihood allocation; both scenarios A (Less fish) and D (Stagnation) had the least number of respondents changing (25%), while 35% of respondents changed livelihood allocation in scenario B.

Estimated net income

In general, respondents chose options that resulted in fairly similar net income outcomes under each future scenario. Across all scenarios, responses to scenario A (Less fish) resulted in the highest 13 average (± standard error) net income per respondent sponses to all scenarios generated net income that was below current levels. The average net income for different scenarios within each livelihood group did not vary much across scenarios (Table 8). The exception was scenario A (Less fish), which, relative to other scenarios, generated much higher net annual income for livelihood group 2, but resulted in lower net income for group 3 (Table 8).

Estimated economic gains and losses under future scenarios

Relative to current conditions, the greatest loss in net income was expected to occur under Scenario C (Urbanization) for group 1 (fishing only), while the greatest gain was expected under scenario D (Stagnation) for group 3 (non-fishing activities) (Table 8).

Averaged across all scenarios, livelihood group 3 was the least negatively affected, while group 1 (fishing only) was the most negatively affected (Table 8). Scenario D (Stagnation) resulted in the least loss in net income relative to the present (-2%), while Scenario C resulted in the largest loss (-19%). In fact, a much larger number of respondents would potentially experience a decrease instead of increase in net income under each scenario (Figure 10). For all scenarios, only about 7% of all respondents made choices that resulted in a positive gain in net income, whereas the majority of respondents chose to retain the same livelihood allocations (Figure 10). Scenarios A (Less fish)

and D (Stagnation) had the largest proportions of respondents choosing to retain their current livelihood allocations (Figure 9).

Scenario C (Urbanization) had the largest proportion of respondents (39%) who made choices which resulted in net income losses. This was primarily due to group 1 respondents reducing their allocation from 100% fishing to a combination of either fishing and off-farm jobs, or fishing and upland farming. Scenario C was also the scenario that resulted in the largest proportion of decreased 14 benefits among livelihood group 2. Among these respondents, the majority (84%) chose to decrease their fishing allocation while increasing their agricultural or off-farm work, or shifting from lowland to upland agriculture.

Net income by single vs multi-livelihood groups under current conditions and future scenarios

The majority of respondents (66%) engaged in more than one livelihood activity.

Current average annual net income for both single and multi-livelihood groups was almost identical, at 3.6 and 3.7 million Riel (USD 891-916), respectively. When faced with future scenarios, the multi-livelihood group generally made choices that resulted in slightly higher average net annual income, although the differences were not statistically different (Figure 10). The multi-livelihood group experienced the largest net income difference under scenario A (Less fish), while scenario B (More farm land) resulted in almost identical net income for both groups (Figure 10).

The single livelihood group chose responses that resulted in greater net income loss (relative to the present) than those engaged in multiple livelihood activities for all scenarios except scenario D (Figure 11). The difference in percentage loss between single and multi-livelihood groups was significant under scenario A (F 1,179 =5.52, p < 0.05).

Net income under current conditions and future scenarios by village zone

Respondents living in zone a (closest to the National Road) had the highest current average annual net income, while those living in zone b (5-7 km from the National Road) had the lowest (Figure 12). Among the respondents with single livelihoods, the majority (86%) were from either zones e (48%) or a (38%), which were the villages furthest and closest to the National Road, respectively. None were from zone b, while 10% and 5% were from zones c and d, respectively. In contrast, the majority of respondents (74%) with multiple livelihoods were from zones located between 7 and 20 km of the National Road, i.e., zones c (43%) and d (31%). Multi-livelihood groups across all zones and under all scenarios had consistently higher average net annual income than single livelihood groups, but these differences were not statistically significant. Aggregating all respondents, the change in annual net income under each scenario varied widely across zones, although none of the differ- 9).

Table 9. Average percentage change in net annual income (relative to the status quo) for each scenario, broken down by village zone.

Discussion and conclusion

This study aimed to investigate the economic consequences of Tonle Sap inhabitants' current livelihood strategies and their responses to socio-economic and environmental scenarios in order to understand their current and future vulnerability. We found that respondents who were not engaged in fishing, (i.e., group 3) appeared to be the most vulnerable under current conditions, as they had the lowest net annual income among all groups. This could stem from their lack of access to fishery resources. At the same time, group 3 respondents tended to have slightly smaller household sizes than groups 1 and 2, so the impact of a lower income may not be as severe on a per household member basis.

Respondents who only fished (group 1) had slightly higher income than those who fished in conjunction with other activities (group 2). This suggests that based solely on income, it may be a good strategy for fishers to focus on fishing only, as there may be economic gains from specialization. Although this strategy may appear to contradict the push for diversified livelihoods, it may still be beneficial for fishers to switch to secondary livelihood activities when seasonality is taken into account and environmental conditions change. In fact, having additional livelihood sources is an important coping and adaptation strategy for people living in the Tonle Sap Lake area [START_REF] Nuorteva | Water, livelihoods and climate change adaptation in the tonle sap lake area, Cambodia: Learning from the past to understand the future[END_REF]. Thus, there is a trade-off between obtaining higher income from one livelihood activity only, or accepting lower income but diversifying livelihood risk. For instance, both [START_REF] Abson | Landscape diversity and the resilience of agricultural returns: a portfolio analysis of land-use patterns and economic returns from lowland agriculture[END_REF] and [START_REF] Fraser | A framework for assessing the vulnerability of food systems to future shocks[END_REF] found that it made more sense to specialize in times of relative socio-economic and environmental stability, whereas during periods of change it made more sense to diversify.

Access and proximity to roads can generally increase peoples' capacity to respond to environmental and economic shocks(GFA Consulting Group, 2007; T. T. X. [START_REF] Nguyen | Indicator-based assessment of climate-change impacts on coasts: A review of concepts, methodological approaches and vulnerability indices[END_REF], and respondents living closest to the National Road (zone a) indeed had the highest average annual net income under current conditions, an indication of lower vulnerability. This supports a prior study which found that those living closest to Tonle Sap Lake were less well off than those living closer to National Roads [START_REF] Keskinen | The Lake with Floating Villages: Socio-economic Analysis of the Tonle Sap Lake[END_REF]). It also supports other studies which indicated that being closer to well-developed infrastructure provides better market access and hence higher income for natural resource dependent communities (T. T. [START_REF] Nguyen | Rural livelihoods and environmental resource dependence in Cambodia[END_REF][START_REF] Sinh | Value Chain of Snakehead Fish in the Lower Mekong Basin of Cambodia and Vietnam[END_REF]. This is particularly the case for highly perishable goods such as fish, and makes sense since the majority (64%) of respondents living in zone a were from group 1 (fishing only). Zone e respondents (furthest from the National Road) would, therefore, be assumed to have the lowest income and higher vulnerability; however, they had unexpectedly higher annual net income than those in zone b (relatively closer to National Road).

Three quarters of the respondents living in zone e were only engaged in fishing (group 1), while those in zone b engaged in multiple livelihoods (fishing plus other activities). Zone e villages are located on the water, while those in zone b are located further inland. This again suggests an income livelihood diversification trade-off, as zone e respondents may be more restricted in the livelihood options available to them, but are compensated by higher income, whereas zone b respondents have more livelihood options but obtain lower income from the diversified activities. Importantly, zone b respondents tended to allocate the majority of their time to non-fishing activities, with only 10-50% of their time spent on fishing, whereas the majority spent 60-90% of their time on agricultural activities. The lower economic returns associated with farming may be due to low agricultural productivity, as it was previously found that low soil fertility minimized the potential contribution of rice farming to poverty alleviation in the Tonle Sap area [START_REF] Johnstone | Tonle Sap scoping report[END_REF].

Interestingly, both zones a and e consist of floating villages, and thus contradicts the expectation that floating village inhabitants are the most vulnerable and have lowest adaptive capacity (Bond, 2015;[START_REF] Nuorteva | Water, livelihoods and climate change adaptation in the tonle sap lake area, Cambodia: Learning from the past to understand the future[END_REF]. Indeed, people in floating villages located in other parts of the Tonle Sap Lake have shown adaptive capacity by engaging in seasonal snake hunting as a means of diversifying their income sources [START_REF] Brooks | Sustained by snakes? Seasonal livelihood strategies and resource conservation by tonle sap fishers in Cambodia[END_REF]. However, despite this seasonal adaptive behaviour, people may still be vulnerable to future change because they are not equipped to respond to unexpected or unusual environmental changes, especially to changes related to fish and water resources [START_REF] Nuorteva | Water, livelihoods and climate change adaptation in the tonle sap lake area, Cambodia: Learning from the past to understand the future[END_REF]. In particular, lack of education and access to land and capital may restrict opportunities for the poorest to diversify their livelihoods (Bond, 2015;[START_REF] Johnstone | Tonle Sap scoping report[END_REF]. The relatively higher incomes observed in zones a and e floating villages may also be related to the former's proximity to markets (nearest to the National Road) and the latter's close access to fishing grounds; this pattern is consistent with the finding that environmental income of households in rural northeastern Cambodia was closely linked to distance from natural resource grounds (T. T. [START_REF] Nguyen | Rural livelihoods and environmental resource dependence in Cambodia[END_REF].

Although group 1 respondents (the dominant livelihood group in zones a and e) appear to be doing relatively well economically under current conditions, this may not hold in the future. In fact, across all future scenarios, the biggest losses are likely to be experienced by group 1. Further, those living in zone e (furthest from National Road) are expected to experience the largest losses in net annual income relative to current conditions. In contrast, group 3 (non-fishing activities) and zone d respondents experienced the least losses across all future scenarios. The majority of zone d 18 respondents engaged in two or more livelihoods; thus, although the economic situation for all respondents appears to deteriorate under future scenarios, our results imply that future income losses may be lower for those with diversified livelihoods compared to single livelihoods.

Across all livelihood groups, scenario C (Urbanization) resulted in the biggest income loss relative to current levels. Group 1 (fishing only) experienced the largest losses under scenario C, which was primarily due to the respondents reallocating their time spent on fishing to either off-farm work or upland farming. Off-farm work and upland farming are new activities to group 1, therefore suggesting that respondents may not fully understand the costs associated with switching to new livelihood activities.

Alternatively, they may lack the education and technical skills to take advantage of future economic opportunities, thereby resulting in economic losses. Overall, this indicates low adaptive capacity among respondents at least in terms of their ability to take advantage of off-farm employment opportunities. It is noted that the interviews conducted by Bond (2015) and on which this study is based focused on fishing households. Therefore, switching to agricultural activities may still be economically beneficial for households that are not as strongly fishing oriented as those that participated in this study. condition of fisheries and lake resources, and underlines the urgency for improving the present poor state of Tonle Sap fisheries management [START_REF] Keskinen | Institutional cooperation at a basin level: For what, by whom? Lessons learned from Cambodia's Tonle Sap Lake[END_REF].

This study contributes to the growing body of research that examines the degree to which vulnerable societies in developing countries are likely to be impacted by human and environmental driven change to fisheries resources [START_REF] Allison | Vulnerability of national economies to the impacts of climate change on fisheries[END_REF][START_REF] Cinner | Vulnerability of coastal communities to key impacts of climate change on coral reef fisheries[END_REF]. We find that in the present time, the highest net income was obtained by those involved in fishing only; this surprisingly contradicts the expectation of livelihood diversification as a strategy to reduce vulnerability. However, faced with future uncertainties, Tonle Sap inhabitants are likely to experience a general loss in net income across their livelihood activities under all future scenarios of socioeconomic and environmental change. This is a worrying result given that the Tonle Sap Zone already has the second highest poverty incidence in Cambodia (JICA, 2010).

Those engaged in single livelihood activities are the most vulnerable, especially under a scenario of reduced fish catch, as they have the 20 largest losses while having the least capacity to adapt. Our findings fill an important knowledge gap because while numerous other studies have similarly highlighted the vulnerability and poor adaptive capacity of rural inhabitants in Cambodia [START_REF] Baran | Climate change and fisheries: vulnerability and adaptation in Cambodia[END_REF][START_REF] Nguyen | Rural livelihoods and environmental resource dependence in Cambodia[END_REF], this is one of the few to actually quantify the consequences in terms of income loss. By doing so, our study can help to direct adaptation policies towards minimizing the economic impact of future changes on the most vulnerable segment of society, thereby contributing towards long-term sustainability of human and ecological communities tied to the Tonle Sap Lake floodplain ecosystem.

Introduction

The Tonle Sap and its associated river system is the largest lake in Southeast Asia and one of the most productive freshwater fisheries in the world supporting large numbers of small-scale fishers. Fish from the Tonle Sap provide an essential source of protein and micronutrients critical to the health of families in a country still plagued by high rates of childhood malnutrition, as well as livelihoods [START_REF] Baran | Fish resources in Cambodia (2001-2011). In Atlas of Cambodia -Maps on socioeconomic development and environment[END_REF][START_REF] Hortle | Consumption and the yield of fish and other aquatic animals from the Lower Mekong Basin[END_REF][START_REF] Lamberts | The Tonle Sap Lake as a Productive Ecosystem[END_REF][START_REF] Sunil | Decomposition of childhood malnutrition in Cambodia[END_REF]. The food security and livelihoods of people depending on the lake ecosystems are affected by future social and ecological changes [START_REF] Salmivaara | Socio-Economic Changes in Cambodia's Unique Tonle Sap Lake Area: A Spatial Approach[END_REF].

Over the last decade, there has been substantial fisheries policy reform in Cambodia's inland fisheries involving community fisheries [START_REF] Charles | Community involvement in fisheries management: Experiences in the Gulf of Thailand countries[END_REF][START_REF] Kurien | Factors that drive Cambodia's inland fish catch: what role can community fisheries play? Phnom Penh[END_REF][START_REF] Levinson | An Examination of the Community Fisheries Sub-Decree in Cambodia: Changes and Developments during the Drafting Process[END_REF][START_REF] Mansfield | Advocacy in cambodia: increasing democratic space[END_REF]Ratner, 2006b;[START_REF] Tep | Cambodia: Asserting rights, defining responsibilities[END_REF][START_REF] Thay | Fisheries Policy Reforms and the Current Perceptions about Community Fisheries and Co-management of Fisheries: A Case Study from Selected Fishing Lot Areas of Siem Reap and Battambang Provinces Kingdom of Cambodia[END_REF]. This was largely explained by the need to safeguard fish stocks, ensuring local food security, and the increasing conflict between family-scale fishers and fishing lot operators, who, despite the law, prevented subsistence fishers from accessing the resource through intimidation, violence and false imprison- Community fisheries in Cambodia, as defined by law, is fisheries co-management.

The co-management of community fisheries is a partnership between Cambodian citizens and the government, represented by the Fisheries Administration. The co-management partnership is also seen in the Community Fishing Area Agreement signed between the Fisheries Cantonment Chief and the community fisheries committee, with the local commune/sangkat chief signing as witness. The Fishery Law, Royal Decree, Sub-decree and Prakas on community fisheries all provide legal support for co-management of fisheries in Cambodia and the establishment of a partnership between citizens and government to share responsibility and authority for the management of the community fisheries.

This study presents the results of an investigation of the impacts of Community Fisheries (CFi) and the factors contributing to the impacts, in the Tonle Sap Great Lake of Cambodia on both ecological and human well-being. This study assesses the impacts associated with different ecological zones of the Tonle Sap and the size of the community managed area, seeking to understand the links between management arrangements and the ecological characteristics. The size of community area is important after the 2012 fishery reform in which private fishing lots were converted into conservation areas and for public access. Recommendations are made to improve the governance of these important fisheries.

To address these issues, in 2001 the Community Fisheries Development Office (CFDO) was created in the Fisheries Administration and was put in charge of the process of crafting a sub-decree on CFi. The CFDO is specifically meant to support communities and encourage them to undertake participatory management of the floodplain fisheries in the country. Subsequently, a series of sub-decrees were issued to formalize the release of the fishing lot, and a sub-decree on CFi was formulated and discussed According to the Fisheries Administration's database, the first CFi in the Tonle Sap was established in 2001. As of 2016, 181 CFis have been established around the five provinces of the Tonle Sap Lake with a total community fisheries area of 355,265 hectares. These CFis highly differ in size, ranging between 23 and 19,044 hectares. In 2012, the government abolished the industrial-scale century-old private fishing lot system covering an area of 270,217 hectares, and re-arranged 35% of the Lake area for conservation and the remaining for open access [START_REF] Sithirith | The Patron-Client System and Its Effect on Resources Management in Cambodia: A Case in the Tonle Sap Lake[END_REF]. While the decision provides more benefits to the community, concerns are also raised over the capacity of CFi in effectively co-managing the Tonle Sap fisheries given poor institution arrangements, especially at the local level.

Materials and methods

Community fishery survey

The data used in this study were based on a field survey conducted in the Tonle Sap, Cambodia in 2015. The Tonle Sap is made of the permanent lake and its extensive floodplain. The permanent lake is composed of two major basins. The northwest side of the lake is a large basin while the southeast lake is the smaller one, connecting together by a narrow strait. The lake is surrounded by five provinces: Pursat, Battambang, Siem Reap, Kampong Thom and Kampong Chhnang. The field survey was conducted in Battambang located in the large basin in the northwestern side and in Kampong Thom which situates more on smaller basin of the southeastern lake. The two provinces also exhibit an important fishing-farming ecology in the Tonle Sap and therefore were selected for the field study. While fishing is fundamental in both zones, Kampong Thom reflected a more significant role of farming in which large-scale private irrigation structures were built up to support the rice production systems. In contrast, households in Battambang still largely depend on fishing as their primary livelihood.

The sampling procedure then started with an identification of fish dependent villages in the Tonle Sap. The fish dependent villages were based on fish dependency scores computed as detailed in [START_REF] Nasielski | Fishing dependency in Cambodiamapping and methodology report[END_REF]. Only villages classified as medium, high and very high fish dependency were selected for the next step of the sampling. By doing so, it helped to reduce the heterogeneity in the population.

The next stage of the sampling process involved determining the characteristics of the selected villages. The villages were categorised into either water, water and land, or land based. Water villages are the floating villages situated in the lake for the whole year. Water and land based villages are referred to any villages which are under water for at least three months a year. Finally, the land based villages situate on land, but households still primarily depend on the fishery resources. Water villages are closer to fishing ground while land villages are better connected to National Roads and developed infrastructure. The categorization of village type also reflects proximity and access to resource ground and developed infrastructure, which indicates the levels of economic status and adaptive capacities to respond to environmental or economic shocks [START_REF] Keskinen | The Lake with Floating Villages: Socio-economic Analysis of the Tonle Sap Lake[END_REF][START_REF] Nuorteva | Water, livelihoods and climate change adaptation in the tonle sap lake area, Cambodia: Learning from the past to understand the future[END_REF]. This procedure helped improve understanding of the impact of CFi by accounting for both economic and ecological factors in the Tonle Sap. Then, 45 of 113 villages were randomly selected by sampling proportionally to each village characteristic (water, water & land, and land). Lastly, 26 CFis (Table 10, Figure 13) were identified for the field survey. The lesser number of CFi selected was because there was no existence of CFi in some villages. In some cases, a CFi was composed of members from more than a village, depending on the community arrangements and geographical characteristics. All 26 CFis from the 45 villages were registered and recognized by the Fisheries Administration. In each CFi, 20% and 5% members of CFi Committee (CFC) and CFi, respectively, were randomly selected for the interview with a total of 437 respondents. The interview sought to understand the CFis' perceptions of operation, impact, successes and challenge. The goal was to assess the performance of CFi in managing fishery resources in Tonle Sap lake, in which the survey questions were split into management and operation, roles of CFC and impact of CFi.

Figure 13. Map of Community Fisheries study area.

Data analysis

The analysis of determinants of governance impact of CFi involved two steps.

Figure 14 presented a flowchart of analytical steps in the study. First, the classification and regression trees (CART) analysis [START_REF] Breiman | Classification and Regression Trees[END_REF] was carried out to assess the impact of CFi in association with different zones of the Tonle Sap and the size of the community area. The CART model has been found useful in many fields of natural, social and other applied sciences. The International Food Policy Research Institute (IFPRI) used CART to improve understanding of famine vulnerability at household level and to identify indicators for effective targeting interventions [START_REF] Webb | Vulnerability mapping and geographical targeting an exploratory methodology applied to ethiopia[END_REF]. Further, [START_REF] Thys | Socio-economic determinants of urban household livestock keeping in semi-arid Western Africa[END_REF] also applied CART to assess socio-economic factors influencing urban households in livestock keeping in Western Africa. The tool is considered efficient and effective in handling the complexity of data and practical development issues, and in aiding policy and intervention decisions. For instance, [START_REF] Yohannes | Classification and Regression Trees, CART: A User Manual for Identifying Indicators of Vulnerability to Famine and Chronic Food Insecurity[END_REF] developed a technical manual for setting up CART-based information systems to help identify key indicators of vulnerability to famine, chronic food insecurity and other failure of entitlements, aiming to better address the multifaceted nature of food security. Thus, the outputs from CART provide a list of most significant impact indicators relevant to ecological zones and the size of community area in the Tonle Sap (CART output); these were inputted into a next step of analyses.

In the second step, logistic regression was implemented to find the driving factors of the impact of the CFi based on the CART model results by using a set of explanatory governance variables (management and operation of CFi, and roles of CFC). Thus, management and operation of CFi and role of CFC were used to predict the CART output variables identified in earlier analyses in the regression models. All statistical analyses of the data were conducted in R software, version 3.2.5.

Classification and regression trees (CART)

CART is a non-parametric technique and works well with both categorical (classification) and continuous (regression) variables. Both dependent and explanatory variables can be a mixture of categorical and continuous variables. Table 11 presents a list of dependent and independent variables for the CART analysis. As explained by [START_REF] Breiman | Classification and Regression Trees[END_REF], the CART model first grows a large classification tree according to the splitting rule and then prunes itself to the right size by applying a goodness of split criteria. Each node represents the dependent variable or splits of the independent variable. Through the CART process, the aim is to search for the optimal splits to produce the most homogenous subsamples of the dependent variable.

In the first stage of the CART analysis, a set of impact measures was used to predict the ecological zone to understand the impact associating with each ecological area of the lake. In the second stage, the same set of explanatory variables was applied to determine the impact of CFi in association with the size of the community area.

CART analyses were performed using R function's ctree in package partykit [START_REF] Hothorn | partykit: A Modular Toolkit for Recursive Partytioning in R[END_REF]. In the case of binary prediction (ecological zone), cross validation estimate of error and a confusion matrix were carried out to assess performance of the pruned tree and to examine individual class errors. Kappa Index (KI) was also computed to measure agreement of all elements in CART's confusion matrix, by applying Kappa function in vcd package [START_REF] Meyer | The Strucplot Framework: Visualizing Multi-way Contingency Tables with vcd[END_REF]. The KI value provided an indication of performance of CART model and the interpretation of the value was detailed in [START_REF] Landis | The measurement of observer agreement for categorical data[END_REF]. The Pearson correlation was used to estimate the value of coefficient of determinant in the case of continuous variable (community area), implementing cor function in stats package (R Core Team, 2016).

Logistic regression models

From the CART's results, the five statistically significant variables were identified in association with ecological zone and community area: fishing ground, shared benefits, income, livelihood, and fishery condition. To do the logistic regression analyses, three multinomial response variables were transformed into binomial: fishing ground (larger vs. same/smaller), livelihood (better vs. same/worse) and fishery condition (good/very good vs. same/bad/very bad). Two sets of governance explanatory variables were run separately to predict the above five outcome variables: (i) management and operation of CFi, and (ii) roles of CFC (Table 12).

The regression analyses were performed using glm function in R's stats package (R Core Team, 2016) with "logit" link of binomial family. McFadden's Pseudo-R2 measures were computed applying pR2 function in pscl package [START_REF] Jackman | pscl: Classes and Methods for R Developed in the Political Science Computational Laboratory[END_REF] to test the goodness of fit of the models.

Results

Impact of community fisheries

Ecological attribute

Results from the CART model (Figure 15) show the impact of CFi associated with two ecological zones of the Tonle Sap: Battambang and Kampong Thom. Among the 11 explanatory impact indicators, the CART model retained the following variables in order of influence: fishing ground, fishery condition, and income. The overall cross validation accuracy is 0.77 and class errors were 0.12 for Battambang and 0.44 for Kampong Thom. The Kappa test result was 0.46, indicating the moderate agreement.

The first split was the fishing ground variable, which divided the total samples by two main branchesone on the left accounted for 86% of the total samples, and another on the right made of the remaining 14%. The left branch associates with larger fishing ground and further splits into additional three groups (node 3, 5 and 6), while the right branch links to smaller or unchanged of fishing ground and is composed of two subgroups (node 8 and 9).

The larger fishing ground was further split into subgroups of respondents perceiving fishery condition as poor (node 3) and those considering it as more positive (node 5 and 6). The group perceiving larger fishing ground and poor resource quality represented more than half of the samples (249 respondents) and the patterns were more observed in Battambang than in Kampong Thom. In contrast, the fishing ground in Kampong Thom was generally considered as smaller or unchanged after the CFi's establishment as shown in node 8. Another important variable is income. The positive impact of CFis on member income occurred more in Battambang than in Kampong Thom (i.e. node 6 and 9).

Areas of community fisheries

In association with the size of community fisheries area, the results from the CART analysis (R 2 =0.31) selected five significant variables: fishery condition, livelihood, benefit, fishing ground and income with eight response values on the leaves of the tree (Figure 16). The size of community managed area is an important indicator reflecting the CFi capacity in effective management of fishery resources. The CART results show that the fishery condition was the most important variable, in which the total samples divided into two main groups. On the left branch, the impact on fishery condition was mixed, but generally encompassed more positive attributes (bad, same, good and very good) and it represented 92% of the total sample. In contrast, the remaining 8% perceived the resource quality as very bad and was associated with the right branch of the tree.

Among all the eight groups or nodes, node 8 (35% of the total sample and the largest) produced the most positive impact associating with fishery condition, livelihood, fishing ground and income and with the average community size of 2,310 hectares.

Smaller or larger than this size, the impact of CFi was less favourable, depicted one or more negative attributes. For instance, when the average community size was 2,141 hectares (node 7) or the smallest (684 hectares, node 10), there was no change in income or fishing ground access after the CFi interventions. Similarly, the larger or largest community managed areas (i.e. node 6, 12, 14 or 15) revealed no improvement in income, livelihood or benefit sharing and resource quality was classified as bad or very bad.

Figure 16. Classification and regression trees (CART) with a community area as a target variable: grn: fishing ground, liv: livelihood, bnf: shared benefits, inc: income, cod: fishery condition, B: bad, G: good, S: same, V.G: very good, N: no, Y: yes.

Factors affecting the impact of community fishery

The CART models (Figure 15 & 16) identified five statistically significant variables associated with ecological zones and community managed areas: fishing ground, livelihood, income, benefit, and fishery condition. For management and operation of CFi explanatory variables, the regression analysis predicting each measure explained between 24 to 35 percent (McFadden's R 2 in Table 13). With the CFi committee as the predictive variable, the regression model explained between 25 to 50 percent (McFadden's R 2 in Table 14). Due to low R 2 value, for fishery condition variable, both management and operation and CFi committee variables were run together, which therefore resulted in the same R 2 value for this particular variable.

Results from the regression in Table 13 showed that among 16 management and operation explanatory variables, nine variables were found to significantly influence each impact measure. The variables include number of years CFi established, membership size, institutional support, activity planning, existence of illegal fishing, illegal activities committed by village members, rule enforcement and CFi efforts in reducing illegal activities. The significant effects on the five impact variables primarily associate with functionality of CFi, community mobilization, compliance and experience in fishery management.

The six-month activity plan was found to have a highly significant effect on every impact variable; positive correlations associated with fishing ground, livelihood, income change and shared benefits, while negative impact was on fishery condition. It demonstrated that the organisational planning process improved members' specific fishery concerns, but did not address broader fishery issue such as overall fishery condition. Further, the institutional support in establishment of CFi positively affected livelihood and income. The result showed that institutions supporting CFi successfully contribute to improving members' well-being, but no significant evidence was found for all other indicators.

The finding illustrated that the ability of the community to get organized improved overall benefits for members as it was found that membership size positively correlated with fishing ground, livelihood, income and fishery condition. Among the four statistically significant variables, the effect of number of members on fishery condition was almost non-existent since the regression coefficient value was 0.001. Another interesting result associating with the effect of institutional development and fisheries management experience on resource access and income, in which years of CFi establishment measure was found to have a positive effect on fishing ground and income change.

Associated with compliance, there was a positive sign on the role of the CFi in which the community efforts in reducing illegal activities positively affected livelihood, income and benefits. Moreover, when the CFi did regular patrol, the benefit sharing among community members was improved. However, it was important to note that the existence of illegal activities within the community led to perceptions of improved resource access and income. The illegal activities could be a result of lack of enforcement and therefore create opportunities for illegal fishing practices and poaching. In some cases, income may also be improved through illegal practices. While illegal fishing can be both from people residing in the village and outside the community, the result showed that the fishing ground was negatively impacted by presence of local abusers and no evidence was found associating with outsiders.

Determinants of impact using roles of Community Fisheries Committee (CFC) variables

Associated with CFC (Table 14), 12 of 22 variables were found to significantly affect various impact variables. CFC developing networks with relevant stakeholders was found to be the most statistically significant variable affecting almost all impact indicators except the fishery condition. External linkage provides means to mobilize support and strengthen institutional capacity and therefore has positive effects on fishing ground, income, livelihood and benefit sharing.

Another important aspect is the functioning of community leadership (committee members) in which their specific activities influence differently on fishery access and human well-being. For instance, managing fisheries, transparent management and meeting regularly have positive effects on fishing ground, income, livelihood and shared benefits. The participation of CFC in drafting by-laws and management plans was also found to positively affected livelihoods. However, when the committee members dealt with fishery conflicts and commune councils, there were negative effects on members' income and fishing ground, respectively.

An inclusive and equitable process of fisheries governance brought positive impacts on member well-being. Engaging women in the leadership or working with them in the community improved their livelihoods and equitable share of benefits. Moreover, ensuring their active participation in CFi activities had strong positive effects on income and livelihoods.

Table 14. Results of logistic regression analysis for the determinants of impact of CFi using Community Fishery Committee (CFC) as predictor variables.

Discussion

Impact of community fisheries interventions

In the Tonle Sap, the main significant impacts associated with ecological zones were fishing ground, fishery condition and income. The majority of respondents perceived larger fishing grounds in both zones which indicated an effect of the fishery reforms on cancelling the fishing lots for public use. However, while the reforms provide better resource access, fishery quality and income remain less positive. First, fishery condition is considered to be poor by more than half of the respondents. Small-scale fisheries in the Tonle Sap, as well as in developing countries are dynamic, diverse and complex. The dynamism, diversity and complexity are not only associated with the biological aspects but also economic, social, technological, cultural and political dimensions [START_REF] Berkes | Managing Small-scale Fisheries. Alternative Directions and Methods[END_REF]. The healthy aquatic [START_REF] Horlte | An introduction to Cambodia's inland fisheries[END_REF]. The overlapping and conflicting institutional arrangements on management, conservation and development of the Tonle Sap lead to promoting own agendas and interests, and the significance of long-term future of the Lake's fisheries receives less consideration. Additionally, the CFis have often have limited funds and in many cases the community's activities are donor-driven.

Several studies show overall fish catch increases compared to historical data; however, catch per fisherman has drastically declined, indicating a signal of high exploitation rate [START_REF] Baran | Floods, floodplains and fish production in the Mekong Basin: present and past trends[END_REF][START_REF] Baran | Have Fish Catches Been Declining in the Mekong River Basin ? Production[END_REF]. The increase in total catch is mainly linked to underestimation of small-scale and subsistence fisheries in the past records [START_REF] Coates | Inland capture fishery statistics of Southeast Asia: current status and information needs[END_REF][START_REF] Van Zalinge | Where there is water, there is fish? Cambodian fi sheries issues in a Mekong River Basin perspective[END_REF]. The stable or reduced fishing income in the Tonle Sap in general is primarily influenced by declining fish catch per person, decreasing high-valued species and limited capacity to respond to unexpected environmental change [START_REF] Nuorteva | Water, livelihoods and climate change adaptation in the tonle sap lake area, Cambodia: Learning from the past to understand the future[END_REF].

However, it is important to note that in Battambang, where there is the largest fish- The results may pose questions on the performance and functioning of CFis in safeguarding the resources. However, the data further showed that in areas where the communities are able to regularly patrol the resources and enforce compliance, there are positive effects on income, livelihoods and shared benefits (Table 13). Furthermore, a case study from Kampong Pluk commune in Siem Reap province, one of the most successful CFis in the Lake, indicated that the substantial positive impact on improving resource management and community livelihoods was driven by eight years of efforts on building capacity, trust and support of the community and government units [START_REF] Evans | Flood Forests, Fish and Fishing Villages:Tonle Sap, Cambodia[END_REF]. This suggests that the effectiveness of CFis is linked to the degree to which the communities are able to perform their functions and external institutional support. In other words, the performance of CFi primarily depend on a match between the management functions with the scale of resources governed and financial resource in support of the community activities. The CFi or co-management is not an end point, but an evolving and learning process [START_REF] Armitage | Adaptive co-management and the paradox of learning[END_REF][START_REF] Pinkerton | Translating Legal Rights into Management Practice: Overcoming Barriers to the Exercise of Co-management[END_REF]. It may take substantial time for the co-management to evolve in its development process and deliver its promise [START_REF] Pomeroy | Conditions affecting the success of fisheries co-management: Lessons from Asia[END_REF].

A mismatch of scale?

In evaluating the impact of CFi associated with the community area, the findings suggest that the fishery condition is the most important determinant and that the ideal size of the community area is 2,310 hectares. The size of community area should be appropriately defined and take into consideration the ecology of the area (Pomeroy et al., 2001). The size of community boundaries reflects the scale of management arrangements and effectiveness of resource governance. The poor resource governance affects the overall quality of fisheries and therefore reduces members' resource benefits. In some cases, the constrained access, because of poor resource quality, undermines the casual benefit sharing process within the community, as evidenced in this study (Figure 16, node 14).

A too large physical area makes it difficult to manage because the size may not fit with the management structure and organisational resources. One of the major issues facing local communities is the management of fishing, farming and flooded forests in the area. Addressing priorities of different groups within the community is challenging and sometimes creates internal conflicts among resource users or confrontation with neighbouring communities. A case study from Kampong Pluk in Siem Reap province showed that success of the community is attributed to smaller size and more homogeneous objectives and membership [START_REF] Evans | Flood Forests, Fish and Fishing Villages:Tonle Sap, Cambodia[END_REF]. As income, livelihood and sustained benefit sharing are all linked to overall quality of fisheries, a larger physical area in the context of resource poor and weak governance of natural resources [START_REF] Clements | Payments for biodiversity conservation in the context of weak institutions: Comparison of three programs from Cambodia[END_REF][START_REF] Sodhi | The state and conservation of Southeast Asian biodiversity[END_REF][START_REF] Travers | Incentives for cooperation: The effects of institutional controls on common pool resource extraction in Cambodia[END_REF] may provide more negative than the positive outcomes.

Contrary to a larger community area, the smaller size is easier to manage and thus has a better resource well-being. Nevertheless, it is important to note that smaller resource area also limits access to resources and environmental benefits. In defining community size, it is necessary to calculate the number of fish species and economic value of the fish and other environmental benefits along with number of resource users. Otherwise, it poses constraints to members' income and livelihood improvement (Figure 16, node 7, 10 and 11). Other factors which may affect members' income and livelihoods associates with decreasing economically important fish species [START_REF] Enomoto | Data mining and stock assessment of fisheries resources in Tonle Sap Lake, Cambodia[END_REF], and the anticipated effects of growing population, resource availability [START_REF] Ziv | Trading-off fish biodiversity, food security, and hydropower in the Mekong River Basin[END_REF], and policy and ecological change.

Factors contributing to impact of community fisheries

Of the governance indicators, operational planning and developing networks most Addressing fishery issue in the Tonle Sap is challenging especially when trying to balance social, economic and ecological uses of the natural resources. It requires participation of multiple parties. Thus, it is evident that regular planning and meeting within the community have effects on human well-being, but not the overall fishery quality (Table 13 and14). It primarily links to different expectations and understanding of stakeholders. The overlapping and conflicting institutional arrangements [START_REF] Sokhem | The Governance of the Tonle Sap Lake, Cambodia: Integration of Local, National and International Levels[END_REF] and the institutional rivalries in the Tonle Sap lead to promoting own agendas and interests, often at the expense of others [START_REF] Keskinen | Institutional cooperation at a basin level: For what, by whom? Lessons learned from Cambodia's Tonle Sap Lake[END_REF]. Moreover, The political affiliation of some CFC members with the commune councils and imbalance of power may lead to a compromise decision and in some cases making the co-management to become fragile [START_REF] Ngor | Pilot Participatory Policy Impact Assessment: Fisheries Policy Related to Community Fisheries Development in Stung Treng, Kampot/Kep, Koh Kong and Siem Reap Provinces[END_REF][START_REF] Plummer | People matter: The importance of social capital in the co-management of natural resources[END_REF].

The significance of institutional development is further supported by the finding that number of years CFi establishment or length of operational experience has a positive effect on income and fishing ground. The empowerment process gradually builds economic and political power of the community and enables them to have more influence and control over resources. Evidence from Cambodian fishing communities

shows that there are changes in thinking and behavior among CFC and CFi members, leading to a ` more sustainable community [START_REF] Marschke | Learning for sustainability: Participatory resource management in Cambodian fishing villages[END_REF].

Size of community membership is considered influential in promoting the community's policy agenda (i.e. fishing ground). The larger group brings out stronger collective action to better address resource accessibility. However, at the early stage of organisational development, the size of community should not be too large to facilitate and enhance supervision, control and management [START_REF] Pomeroy | Conditions affecting the success of fisheries co-management: Lessons from Asia[END_REF]. Because the close interaction of ecosystems in the Tonle Sap, it is important to include members which are less diverse in terms of resource dependency (i.e. fish, water or forest) to avoid conflicts. Successful communities are from those who are more homogeneous than the heterogeneous ones [START_REF] Evans | Flood Forests, Fish and Fishing Villages:Tonle Sap, Cambodia[END_REF].

Integrating gender perspective, acknowledging women's position and facilitating their full participation in co-management process is critical in uplifting economic conditions of fishers in the Tonle Sap as it proves positive effects on income, livelihood and benefit sharing. The findings advocate for more mobilizing women in natural resource management despite previous studies have found that woman participation was observed to have less impact on project efficiency or success and particularly in a maledominated sector. First, women in the Tonle Sap generally subsidise men in fishing activities and more engage in land-based livelihoods or fish processing and trading.

Second, woman participation is considered additional burden or costs on top of their hectic regular duties due to unequal distribution of responsibility in society and thus results in generally observed passive involvement [START_REF] Narayan | The contribution of people's participation : evidence from 121 rural water supply projects[END_REF][START_REF] Resurreccion | Rules, Roles and Rights: Gender, Participation and Community Fisheries Management in Cambodia's Tonle Sap Region[END_REF]. Finally, [START_REF] Prokopy | Women's participation in rural water supply projects in India: is it moving beyond tokenism and does it matter?[END_REF] found that there was no relationship of female participation with project success in an assessment of water-related projects assisted by the World Bank [START_REF] Prokopy | Women's participation in rural water supply projects in India: is it moving beyond tokenism and does it matter?[END_REF]. Evidence from the Tonle Sap is contrary to the previous notion that promoting gender equality can hardly be achieved due to complex socialcultural context which inhibits their full participation [START_REF] Resurreccion | Rules, Roles and Rights: Gender, Participation and Community Fisheries Management in Cambodia's Tonle Sap Region[END_REF]. Continue encouraging women and their full participation in fisheries management will promise improved economic benefits.

Ninety-eight percent of respondents believe that illegal fishing is still a problem in the Tonle Sap. It confirms that even though there are some levels of enforcement, the effort is still insufficient and more needs to be done. The motives for widespread illegal activities associating with weak enforcement of rule and a trade-off between benefits and risks of violations [START_REF] Pomeroy | Conditions affecting the success of fisheries co-management: Lessons from Asia[END_REF]. If the measured benefit is higher than the calculated risk, therefore there is likely a non-compliance of regulations. More respondents believe that the efforts in reducing illegal activities were more associated with CFis than the government units (91 percent vs. 57 percent). CFis' roles in reducing illegal activities were found to have significant effects on income, livelihood and benefits. This suggests the important role of CFi in fisheries management and should be further strengthened.

Conclusion

The study provides important understanding of the impact of CFi in the Tonle Sap, especially after the 2012 fishery reform and during the significant socio-ecological change around the lake. It further suggests the appropriate scale of the CFi area to be managed and depicts important factors contributing to improving the effectiveness of CFi governance in the Tonle Sap.

The perception of having larger fishing ground in the Tonle Sap is indicative of the effect of fishery reform. Meanwhile, poor fishery condition was also observed in area where there is improved access. This may provide a mixed perception on the performance and roles of CFi in managing and controlling over the resources. This implies that there is an immediate need to redefine the community area to match with community management and resource arrangements. A match between resource scale, management arrangement and level of institutional support is a prerequisite important condition to ensure effective operating performance of CFi. When redefining or rezoning community area, we need to bear in mind that too small area may affect the level of income of members in the community as well. Thus, valuation of environmental benefits in each community areas to match with population is necessary.

Moreover, the role of CFi should be further supported and strengthened and more engagement of government units in community activities are needed especially when dealing with illegal fishing activities and elite groups in the Tonle Sap. The findings from regression results showed that a well-functioning, transparent and gender inclusive CFi have positive effects on fishing ground, income, livelihoods and benefit sharing.

Two indicators which are the most important factors contributing to positive impact of CFi are six-monthly planning and networking with external stakeholders. Amid complexity of Tonle Sap's fisheries as previously discussed and conflicting institutional arrangements, community's capacity to manage planning is critical for the success of CFi, as it can help to improve coordination and harmonise objectives to address multidimensional, multi-level issues in the Tonle Sap. Moreover, the significance of networking indicates the need to continued community capacity and leadership development and for financial resources to support community's activities (i.e. patrolling and rule enforcement).

Co-management is a learning and transforming process. Promised results take time, efforts and continued commitments from all stakeholders. The findings proved that in areas where the communities are able to well function, positive impact exists.

Summary

In Cambodia, fish and fishing activities have been primary sources of nutrition and income. Majority of fish supplies are from the Tonle Sap. The lake provides essential ecosystem services and supports livelihoods of at least 2 million people as well as a large number of small-scale fishers. However, the decades of conflicts and the change in socioeconomic, ecological, policy, climate and fishery governance structures and systems have put the Tonle Sap's inhabitants at high of vulnerability because their low level of capacity to respond to unfamiliar events.

Thus, this study intends to assess the livelihood strategies of fishing communities in the Tonle Sap in the face of change by looking specifically to the following objectives:

1. assess spatial and temporal characteristics of livelihood strategies in Cambodia;

2. analyze the current livelihood strategies and measure the economic impact to future scenario change in the Tonle Sap;

3. assess the impact of community fisheries and the drive factors in the Tonle Sap.

The SLA and co-management principles were proposed as the framework in the analyses and four case studies were developed. First, the study on livelihood dynamics focused on spatial and temporal variations of livelihoods of Cambodian households from 1999 to 2013 by using cluster analysis, NMDS and ArcGIS Mapping visualization of the patterns. Second, multinomial and OLS regressions were applied to identify the determinants of household's livelihood choices and income using the CSES data in 2013. The third case study aimed to measure economic impact of adaptive responses to future scenario change in the Tonle Sap. The four future scenario conditions were established (less fish, more farmland, urbanization and stagnation) and the benefit-cost analysis was carried to identify which groups might be most vulnerable to future change. Lastly, the study on CFis intended to investigate the impact of CFis associated with different ecological zones of the Tonle Sap and the size of community managed area, by seeking to understand the links between management arrangements and the ecological determinants. The CART and logistic regressions models were applied to answer the research questions.

Livelihood dynamics

The results show four distinct livelihood clusters associating with different types of resource dependency: (i) crops and livestock; (ii) dominated by crops and a mixture of forestry, fishery and livestock; (iii) dominated by forestry and a mixture of fishery, livestock and crops; and (iv) nonfarm and livestock. Over the past decades, there has been significant contribution of the primary sector (crops, livestock, fishery and forestry) to the livelihoods of Cambodian population despites some variations of dependency within this sector. There has been a shift from crops and livestock in the 1990s to diversification into natural resource strategies in the present time. The motives relate to both the push and pull factors. The push factor associates with decreased arable land per capita. The pull factor is motivated by improved resource accessibility through landmine clearance, and increasing demand of natural resources as a result of development of market economy. Lastly, nonfarm remains marginal and static over the past decades because agriculture-based households (both crops and natural resource based) are more attracted by wage employment instead of self-employment opportunities.

Determinants of livelihood choices and income

The findings indicate that various elements of livelihood assets influence households' decision to participate in livestock, fishery, forestry and nonfarm differently compared to crops as a reference strategy. Associating with factors influencing households' total income, age of household head, land size and value, and agricultural equipment positively affect total income of crop households whereas female percentage and remittance have negative effects. Income of livestock households can be improved by increased access to financial capital.

To increase income of fishery households, it is imperative to address access to transport assets (i.e. fishing boats) whereas education is unlikely to improve households' income.

Income of forestry households can be increased through more availability of labor force, land size and agriculture equipment while non-food expenditure and durable goods decrease the income. Human well-being (i.e. wealth and health) is an important factor contributing to income of nonfarm households than that of capacity development and experience as this can be observed of negative effects of age of household head and non-formal education on households' total earnings.

Land is found to be most important capital influencing household's decision in livelihood participation and total earnings.

Economic impact to future scenario change

Under current conditions, the group of individuals who do not participate in fishing have the lowest net income. In contrast, individuals who solely fished had higher average net income than those with multiple livelihoods, suggesting that there may be gains from livelihood specialization. The majority of respondents chose to retain their current livelihood strategy under all future scenarios. Of those who did change their livelihood allocation, less than 10% actually experienced a gain in economic benefits. Thus, on average, a loss in net income is expected under all future scenarios, with those engaged in single livelihoods experiencing an average loss of 18% across all scenarios compared to 9% for the multi-livelihood group. Respondents' choices generated the best economic outcome under a status quo scenario. This indicates that respondents were capable of coping with current conditions, but were unlikely to make appropriate decisions when faced with future scenarios that they were unfamiliar with.

Impact of CFis

Overall, the significant impact in Tonle Sap associates with fishing ground, fishery condition and income and with mixed effects. Fishing ground is positive, fishery condition is generally worse and income remains unchanged. Generally, Battambang is observed to have more positive outcomes than in Kampong Thom, especially associating with fishing ground and income. In the Tonle Sap, the ideal size of community area is 2,310 hectares. Larger or smaller size may result in less positive outcome.

In predicting factors influencing fishing ground, livelihood, income, shared benefit and fishery condition, the findings suggest that regular operational planning, developing networks, and ensuring a functioning, transparent and gender inclusive community organizations yield positive outcomes. However, illegal fishing, fragmented objectives and conflicts are roadblocks for the co-management to flourish.

General conclusion and perspectives

The overall outcomes of the study suggest that there is a close relationship between livelihood, natural resources and conflict as evidenced in the literature. Households from post-conflict states largely depend on agriculture and natural resources and their livelihoods are highly vulnerable to many factors. First, it is the damage to livelihood capital which leave households with limited coping capacities to unexpected events. As we can see from the results that even the Tonle Sap's inhabitants have been living and adapting their life to the seasonal events in the lake for many years, they are unlikely to make appropriate decisions about unfamiliar situation. The most imperative loss of livelihood resources is land tenure. The decreased in arable land per capita force households to seek alternative employment, mostly in natural resources and wage employment.

Second, it is the damage to governance systems which generally lead to conflicts and resource depletion. Third, post-conflict development policies may aim to accelerate growth or short-term improvement income but fail to consideration the long-term impoverishment and productivity of resources or social equity in which people have equal access to minimum standard of quality of life. Land, governance system and post-conflict policies have significant impact on resources and user livelihoods. Additional pressure on natural resources can be seen and their livelihoods are likely to be impacted by degrading resources as a result of overexploitation or any combined effects (i.e. climate change). The post-conflict development policies should integrate sustainability perspectives into the agenda which address its four dimensions: economic, socio, institutional and environmental sustainability. As policy reform has always its implications for local livelihoods, continue close monitoring the productivity and performance of livelihood systems is imperative; for example, how they have changed over time and what impact of the policy adjustments have occurred.

The variations of livelihood strategies over time from crops and livestock associate primarily with lower human capital, limited land ownership and constrained financial capital. Therefore, households are forced to more engage in natural resource strategies.

As shown in the case study on livelihood determinants, fishery and forestry households have lower education compared to those from crop families and with average land size of half a hectare. Furthermore, those engage in nonfarm are generally better-off and it is the main reason why there have been almost no variations over the past decades in terms of non-farm self-employment because a significant percentage of population remains resource poor and are unable to diversify into entrepreneurial activities, but instead chose resource-based strategies or non-farm wage employment. This can be further supported by the finding showing significant relationship between remittance and fishery strategy.

Overall, the factors which contribute to improving households' income associates with land access, asset ownerships, availability of labor resource and household's financial capital. Thus, policy implications to improve livelihood participation and maximize the long-term economic and social benefits for household should consider special attention to resource poor households, increase household's wealth and assets, and design and implement effective resource conservation programs.

From the case study on economic impact to future scenario change, the findings show the importance of specialization in Tonle Sap. Under current conditions, households pursuing single fishery strategy have higher average income than those undertaking multiple livelihoods. However, as Tonle Sap is prone to changes occurring around the lake and surrounding systems, it may not be economically sustainable to encourage households' specialization in a single fishery strategy in the Tonle Sap as it can lead to more resource pressure and overexploitation and definitely results in negative economic impact in the long-term. Even majority of the Tonle Sap's inhabitant are likely not to change their current strategies and there is average net income loss in all future scenarios, we can learn that those undertaking multiple livelihood options have lower average income loss compared to those depend a single strategy. This suggests that promoting livelihood diversification in the Tonle Sap is a viable economic option. Understanding which groups are most vulnerable to future change helps to direct adaptation policies to appropriate groups and interventions, thereby minimizing the economic impact of future changes on the most vulnerable households dependent on the Tonle Sap floodplain ecosystem. In developing adaptive responses in the Tonle Sap, the multidimensional SLA approach is considered appropriate which help to improve understanding and address vulnerability and adaptive capacities from multiple angles of problems, such as vulnerability and policy setting, livelihood resources and strategies, and institutional processes.

The impact of CFis in Tonle Sap is mixed across different communities around the lake and the overall outcomes are less satisfactory except fishing ground which may be attributed to the fishery reform in 2012. However, there are significant roles the CFis have played since the 2000s associating with mobilization of community members, rule enforcement, co-managing fisheries resources, developing networks and building institutional capacity. Although there is a variation of the impact of CFis, one should note that CFis vary across years of experience and community size. As previously mentioned, co-management is a learning process which may take time to evolve, develop and deliver its promise. Continue building the CFis' strengths and address their challenges would enable greater impact on fishers' livelihoods and well-being as well as resource quality and sustainability.

Furthermore, community area should be redefined which appropriately reflect the scale of management arrangements, the ecology of specific area, and level of institutional support. This would help to address the remaining challenges associating with existence of illegal fishing and resource conflicts, coordination and strategic planning.

Lastly, co-management can be integrated as an institutional intervention into the SLA to achieve desired community outcomes, such as improved income, livelihoods and resource access, and reduced vulnerability. Co-management can be an effective means to influence policy reform within the broader context of the SLA framework which may impact the livelihoods of the local people/fishers. Further, it can be used to assess how co-management effort might influence various livelihood capitals of households. The integration of co-management principles with sustainable livelihoods enables holistic understanding of household vulnerability and helps to design appropriate interventions to address both present and future livelihood constraints. Part C. This part will ask you about your response to hypothetical change in Tonle Sap fishery.

Views/perceptions under possible policy/future conditions

Some studies show that because of the ongoing development of dam construction in the Upper Mekong Basin, climate change and urbanization, there will be four possible situations in the future: (a) 50% reduction of fish production in Tonle Sap Lake, (b) Increased agricultural land due to changes in flood plain habitats, (c) Creation of more jobs due to the urbanization and increased economic activities in urban centers or, (d) Stagnation (more or less the same situation as today). Assuming one or more of these conditions arise in the future, then how would your livelihood be affected and how would you allocate and manage your resources.

Those who are currently only fishing

A a) 50% reduction of fish production in Tonle Sap Lake and everything else remains same

  Dr. TOUCH Visalsok, Under Secretary of State, Ministry of Education, Youth and Sport, and former University of Battambang Rector, for introducing me to the Belmont Project team. My scientific support thank is extended to Prof. Evan FRASER and Dr. Krishna KC from Department of Geography, University of Guelph, Canada for hosting my mobility in Guelph and who are instrumental in my socioeconomic survey design and data collection as well as the livelihood analysis. I am also grateful for my referees and jury members (Prof. Thomas VALLEE, Dr. Phillippe ME-RAL, Prof. Young-Seuk PARK, Assoc. Prof. Jean Michel CAPUIS, Assoc. Prof. Jocelyne NA-POLI and Dr. ITH Saveng) for accepting to review, evaluate and read my thesis as well as providing useful comments on my work and for continuing to inspire me to go on with the research career path. This research would not have been possible without all the amazing team at the University of Battambang. Firstly, I am grateful for H.E Mdm. SIENG Em Totim, Rector, for her continued support on the research activities and make every means possible to ensure the research work a success. Special thanks also go to our colleagues, Dr. CHEA Ratha, Dr. SREAN Pao and our most helpful project administrator, Mr. CHREA Socheat for all kinds of support for my research work and PhD. I am forever grateful for my data collection team led by Mr. IV Channara and inspiring and dedicated students at the Faculty of Sociology and Community Development, including Mr. TEP Langdy, Ms. MOM Lita, Ms. MAO Sotheavy, Mr. REAN Sothea, Mr. SUN Kimseng, Ms. CHHON Sanda, Ms. SOEUM Sreynin and Mr. KIT Singheang. Finally, my appreciation is also to villagers and Community Fisheries leadership and members in Tonle Sap for allowing us to meet and learn about their situation, experience and struggle.

Figure 1 .

 1 Figure 1. The Sustainable Livelihood Framework ......................................................Figure 2. Research Framework for Institutional Analysis of Fisheries Co-Management ................................................................................................................. Figure 3. NMDS ordination of the district data based on the five strategies ...............Figure 4. Temporal and spatial patterns of livelihood strategies. ................................Figure 5: Distribution of total net income, land size and current land value by livelihood strategy clusters. ......................................................................................... Figure 6. Map of Pursat Province showing the location of village sites...................... Figure 7. Current annual average net income of different livelihood activities .......... Figure 8. Current average annual net income for each livelihood group..................... Figure 9. Proportion of responses that resulted in a gain, loss, or no change in average net annual income under each scenario ....................................................................... Figure 10. Average net annual income for single and multi-livelihood groups under Scenarios A to D. ......................................................................................................... Figure 11. Average percentage change in net income relative to current levels under each scenario, broken down by single or multi-livelihood groups .............................. Figure 12. Current average net annual income from all livelihood activities by zone Figure 13. Map of Community Fisheries study area.................................................. Figure 14. A flowchart of statistical analyses. ........................................................... Figure 15. Classification and regression trees (CART) with an ecological zone as a target variable............................................................................................................. Figure 16. Classification and regression trees (CART) with a community area as a target variable.............................................................................................................

Figure 2 .

 2 Figure 1. The Sustainable Livelihood Framework ......................................................Figure 2. Research Framework for Institutional Analysis of Fisheries Co-Management ................................................................................................................. Figure 3. NMDS ordination of the district data based on the five strategies ...............Figure 4. Temporal and spatial patterns of livelihood strategies. ................................Figure 5: Distribution of total net income, land size and current land value by livelihood strategy clusters. ......................................................................................... Figure 6. Map of Pursat Province showing the location of village sites...................... Figure 7. Current annual average net income of different livelihood activities .......... Figure 8. Current average annual net income for each livelihood group..................... Figure 9. Proportion of responses that resulted in a gain, loss, or no change in average net annual income under each scenario ....................................................................... Figure 10. Average net annual income for single and multi-livelihood groups under Scenarios A to D. ......................................................................................................... Figure 11. Average percentage change in net income relative to current levels under each scenario, broken down by single or multi-livelihood groups .............................. Figure 12. Current average net annual income from all livelihood activities by zone Figure 13. Map of Community Fisheries study area.................................................. Figure 14. A flowchart of statistical analyses. ........................................................... Figure 15. Classification and regression trees (CART) with an ecological zone as a target variable............................................................................................................. Figure 16. Classification and regression trees (CART) with a community area as a target variable.............................................................................................................

Figure 4 .

 4 Figure 1. The Sustainable Livelihood Framework ......................................................Figure 2. Research Framework for Institutional Analysis of Fisheries Co-Management ................................................................................................................. Figure 3. NMDS ordination of the district data based on the five strategies ...............Figure 4. Temporal and spatial patterns of livelihood strategies. ................................Figure 5: Distribution of total net income, land size and current land value by livelihood strategy clusters. ......................................................................................... Figure 6. Map of Pursat Province showing the location of village sites...................... Figure 7. Current annual average net income of different livelihood activities .......... Figure 8. Current average annual net income for each livelihood group..................... Figure 9. Proportion of responses that resulted in a gain, loss, or no change in average net annual income under each scenario ....................................................................... Figure 10. Average net annual income for single and multi-livelihood groups under Scenarios A to D. ......................................................................................................... Figure 11. Average percentage change in net income relative to current levels under each scenario, broken down by single or multi-livelihood groups .............................. Figure 12. Current average net annual income from all livelihood activities by zone Figure 13. Map of Community Fisheries study area.................................................. Figure 14. A flowchart of statistical analyses. ........................................................... Figure 15. Classification and regression trees (CART) with an ecological zone as a target variable............................................................................................................. Figure 16. Classification and regression trees (CART) with a community area as a target variable.............................................................................................................

Figure 1 .

 1 Figure 1. The Sustainable Livelihood Framework.(source: modified from UK Department for International Development)

  understand the conditions leading to successful fisheries co-management. The International Centre for Living Aquatic Resource Management (ICLARM) and Institute of Fisheries Management and Coastal Community Development (IFM) developed a research framework for institutional analysis of co-management, adapted from theoretical and empirical work on the Institutional Analysis and Development (IAD) framework (ICLARM & IFM, 1998). The aim of the analytical framework is to enable the systematic and comparative analysis of co-management institutions, which allows generalizations to be made on the conditions of successful co-management. The research framework incorporates the concepts of common property resources, co-management, institutional analysis, and rights and rules. A graphical representation of the institutional analysis framework is given in Figure 2, which has three major components:

  indicates a positive trend associating with both the outcome and process indicators. On the outcome measures, only resource access shows a negative trend while other four indicators, namely resource well-being, fishery yield, household well-being and income, indicates positive change. Associating with co-management process indicators, the top five measures as participation, influence, rule compliance, control over resources and conflict report a positive trend especially across Asian countries for both marine and inland fisheries. Despite some reported challenges, the co-management approach shows more on the success than failure in small-scale fisheries particularly in the Asian context.

Figure 2 .

 2 Figure 2. Research Framework for Institutional Analysis of Fisheries Co-Management. (source: modified from (ICLARM & IFM (1998))

  3. measure the economic impact of adaptive responses to future scenario change in the Tonle Sap; 3.1 analyze the net income from current livelihood strategies of households in the Tonle Sap. 3.2 predict the economic impact under future scenarios in the Tonle Sap (i.e. a. fish decrease, b. more farm land, c. urbanization, and d. stagnation).

  vey conducted by the National Institute of Statistics, Cambodia. The survey was first conducted in 1993/1994 aiming to collect statistical information about living conditions and the extent to poverty of the Cambodian population. It was used to monitor the Cambodian National Strategic Development Plan (NSDP) and to measure progress towards global development goals (i.e. Millennium Development Goals and Sustainable Development Goals). The survey was conducted intermittently between 1993/1994 to 2004 and it was until 2007 that it has been annual. The CSES has experienced a significant development in the first few surveys associating research design, sampling and questionnaire in order to better address the needs of different users and enable comparative studies.

(

  CSES), a nationwide representative survey conducted by the National Institute of Statistics, Cambodia. The survey was first conducted in 1993/1994 aiming to collect statistical information about living conditions and the extent to poverty of the Cambodian population. It was used to monitor the Cambodian National Strategic Development Plan (NSDP) and to measure progress towards global development goals (i.e. Millennium Development Goals and Sustainable Development Goals). The survey was conducted intermittently between 1993/1994 to 2004 and it was until 2007 that it has been annual.

  a b

Figure 4 .

 4 Figure 4. Temporal and spatial patterns of livelihood strategies based on results from NMDS and ArcGIS Mapping; a, temporal trend based on NMDS results; and spatial characteristics of livelihood strategiesin 1999 (b), 2003-2004 (c), 2008 (d) and 2013 (e).

  pointed out the geographical attributes among all other incentive and capacity variables as one of the key elements in driving diversification into nonfarm income by households. The proximity to urban centers drives up demand and consumption for nonfarm products and services stirred up by the growth of other sectors such as wage employment, construction, tourism or industry for the case of Cambodia. Another study in Eastern Africa by Cecchi et al. (2010) also stressed the correlation between agro-ecological attribute with different livestock and farming system. The linkage of environmental resources with the choice of livelihood strategies is also evidenced in recent studies in Cambodia. Nguyen et al. (2015) confirmed the significant impact on the level of environmental income by the distance to the extraction area. Similarly, Rahut & Scharf (2012) revealed the positive and negative correlations of farming and nonfarm strategies with different geographical zones such as Phnom Penh, Coast, and Plateau/Mountain.

  population. It is estimated that about one-third of Cambodia's land is owned by only 1 percent of the population[START_REF] Uncdf | Local development outlook Cambodia: Trends, policies, governance[END_REF]. The failure to address property rights and tenure results in increased land disputes across the country since the early 2000s and 2012 is the peak in the decade[START_REF] Ngof | Statistical Analysis of Land Disputes in Cambodia[END_REF]. The average farmland is one and a haft hectares; 48 percent of rural households own land of less than one hectare, and 20 percent of rural population has no land access(World Bank, 2006, 2015a). With an average household size of five, the majority of the rural population faces a high level of vulnerability. Still as high as 70 percent of the population depend on natural resources, of which almost 60 percent for subsistence,[START_REF] Mckenney | Natural resources and rural livelihoods in Cambodia: a baseline assessment[END_REF]; households, thus, diversify into other income alternatives as an adaptation strategy based on available resources and capacities to maintain income. The resource vulnerability and the strong links between the livelihood strategies and land-based resources are evidenced through increasing cases of land disputes and landlessness since the early 2000s[START_REF] Ngof | Statistical Analysis of Land Disputes in Cambodia[END_REF].Third, it is a pull factor which attracts households to engage more in natural resource-based strategies. The development of market economy increase demand for nat-ural resources. Extracting fishery and forestry products may be strategically complementary to other activities, more lucrative, fast economic return, less risk due to shocks and seasonality, and requires less capital investment for family scale operations. Aquaculture may require access to credit. Other resource extraction strategies are less dependent on loans to operate as compared to crops and livestock. Access to credit in Cambodia is still challenging for the rural population in terms of loan size, collaterals, and interest rates. Furthermore, the natural resource exploitation becomes more convenient in the condition of weak enforcement of rules in the post-conflict setting as evidenced in several countries.

Figure 5 :

 5 Figure 5: Distribution of total net income (upper), land size (middle) and current land value (bottom) by livelihood strategy clusters.

  have a tendency to work outside the farm even though livestock might be the primary income for the household. The tendency holds true among young family members who are attractive to wage employment or nonfarm self-employment. Therefore, educated individuals make less contribution to livestock income compared to those with lower literacy. The finding contrasts with other studies showing that education is instrumental in enabling households to better respond to shocks and is considered one of the key factors for livestock production success[START_REF] Bindlish | Evaluation of the Performance of T & V Extension in Kenya[END_REF][START_REF] Cooper | Rural household vulnerability to climate risk in Uganda[END_REF]

Figure 6 .

 6 Figure 6. Map of Pursat Province showing the location of village sites where interviews were conducted. Map source: Bond (2015), with basemap from JICA & MPWT (2003)

Figure 7 .

 7 Figure 7. Current annual average net income (000 Riel) (± standard error) of different livelihood activities, with the percentage of respondents participating in each activity indicated at the top of each bar. The 2014 average exchange rate was 4037.5 Riel/USD (World Bank, 2015b).

Figure 8 .

 8 Figure 8. Current average annual net income (± standard error) for each livelihood group (1=fishing only, 2= fishing + other activity, 3= non-fishing activities). The dashed line indicates the overall average annual net income across all livelihood groups (3.63 million Riel).

  (3.6 ± 0.6 million Riel or ~USD 892), followed by scenario D (Stagnation, 3.5 ± 0.5 million Riel or ~USD 867), B (More farm land, 3.1 ± 0.5 million Riel or ~USD 768), and scenario C (Urbanization, 3.0 ± 0.6 million Riel or ~USD 743). On average, re-

Figure 9 .

 9 Figure 9. Proportion of responses that resulted in a gain, loss, or no change in average net annual income under each scenario

Figure 10 .

 10 Figure 10. Average net annual income (± standard error) for single (lined bar) and multi-livelihood (grey bar) groups under Scenarios A to D.

Figure 11 .

 11 Figure11. Average percentage change in net income relative to current levels under each scenario, broken down by single or multi-livelihood groups. Asterisk indicates a significant difference between single and multi-livelihood groups(F 1,179 =5.52, p < 0.05)

Figure 12 .

 12 Figure 12. Current average net annual income (± standard error) from all livelihood activities by zone.

  significant. The largest losses in average net annual income occurred most frequently in zones b and e across all scenarios, except for Scenario D (Stagnation), in which zone c respondents had the greatest loss (Table

  ment. The Sub-Decree on Community Fisheries Management No: 25/OrNor Kror/BorKor in Chapter 2: Establishment of Community Fisheries in Article 6 states: "All Cambodian citizens have the rights to form Community Fisheries in their own local area on a voluntary basis to take part in the sustainable management, conservation, development, and use of fisheries resources. A community fisheries as mentioned in this Sub-Decree is a group of physical persons holding Khmer citizenship who live in or near the fishing area, voluntarily established and taking the initiative to improve their own standard of living by using and processing fisheries resources sustainably to contribute to economic and social development and poverty alleviation. The Fisheries Administration and local authorities or Commune/Sangkat councils, shall cooperate together to establish community fisheries."

  with stakeholders. On 29 May 2005, a Royal Decree on the establishment of CFi was proclaimed and on 10 June 2005, the Sub-decree on Community Fisheries Management was approved by the Prime Minister. On 30 March 2006, this sub-decree was given a more solid legal standing with the approval of the new Fisheries Law by the National Assembly. Finally, it was promulgated by the King on 21 May 2006. The Ministry of Agriculture, Forestry and Fisheries is entitled to allocate part of the fishery domain to the CFi that lies inside or around the fisheries domain as CFi area (Article 60). The CFi area is a Territorial Use Right in Fisheries (TURF) (Article 6).

Figure 14 .

 14 Figure 14. A flowchart of statistical analyses.

Figure 15 .

 15 Figure 15. Classification and regression trees (CART) with an ecological zone as a target variable: BB: Battambang, KT: Kampong Thom, Grn: fishing ground, Inc: income, Cod: fishery condition, B: bad, V.B: very bad, N: no, Y: Yes

  ing lot area in the Tonle Sap, there is more observed positive income change given the better access to the resource ground after the reforms. Before 2000, Battambang covered a total fishing lot area of 146,532 hectares (31 percent of Tonle Sap's total fishing lot area) while Kampong Thom had 127,126 hectares (27% of Tonle Sap's total fishing lot area)[START_REF] Johnstone | Tonle Sap scoping report[END_REF] 3 . In 2001, 30 and 45 percent of fishing lot areas were cancelled in Battambang and Kampong Thom, respectively, while the remaining 70 percent for Battambang and 55 percent for Kampong Thom were completely allocated for public use and fish sanctuaries in 2012. The wider access of fishing ground in former fishing lot areas in Battambang may contribute to poorer resource quality as compared to Kampong Thom's zone because of overexploitation. The findings in this study also contrasts with a synthesis study on the impact of fisheries co-management in developing countries by[START_REF] Evans | Assessing the impact of fisheries comanagement interventions in developing countries: A meta-analysis[END_REF] which indicated a more positive trend in resource condition and income.

  strongly correlate with impact measures, showing significant relationship with four of the five impact measures. The effects of other factors are varied depending on the cases, of which more positive relationships are observed than the negative ones. Institutional capacity of CFi in managing resources is crucial. Institutional capacity means an ability of CFi to ensure a functioning and transparent community organization. It involves ability to develop external linkages and mobilise financial resources to support the community's mandate and its policy agenda (i.e. fishing ground, income, livelihood and benefits). The networks formed can also be beneficial in counteracting conflicts and often powerful interests outside the community(White et al., 1994). The external support is critical for the success of Cambodian CFi which often face inadequate budget to operate. The funding supports conservation and patrolling activities and thus enable positive change in benefit sharing, income and livelihoods.

Table 1 .

 1 Cluster composition and share from 1999 to 2013. .......................................

Table 2 .

 2 Description of the explanatory variables used in regression analysis. .......... Table 3. Summary statistics of variables ..................................................................... Table 4. Determinants of livelihood strategies (the multinomial logit regression) ..... Table 5. Determinants of household total income ....................................................... Table 6. Categorization of village zones and the list of study villages. ....................... Table 7. Summary of livelihood options. ..................................................................... Table 8. Average net annual income and percentage change in net income for scenarios A to D according to livelihood groups ......................................................... Table 9. Average percentage change in net annual income ....................................... Table 10. List of 26 Community Fisheries (CFi) in Tonle Sap and sample size. ...... Table 11. Impact predictor and target variables for the CART model. .....................

Table 12 .

 12 Descriptions of explanatory variables used in logic regression ................. Table 13. Results of logistic regression analysis using management and operation of CFi as predictor variables. ......................................................................................... Table 14. Results of logistic regression analysis using Community Fishery Committee (CFC) as predictor variables. .....................................................................................

Table 1 .

 1 Cluster composition and share from 1999 to 2013.

  Asian Development Bank, 2014). A study in 2011 in 375 villages across Cambodia reveals that half of rural migration is to Phnom Penh and one-third is to other countries, mainly Thailand (MoP, 2012).

	2013 (Households in developing countries and in Cambodia in particular pursue a variety
	of livelihood activities like crops, livestock, fishing, forestry, and nonfarm (Babulo et
	al. 2009; Ellis 2000; Nielsen et al. 2013; Soltani et al. 2012) as a way to ensure eco-
	nomic viability and a basis for adaptive strategy to cope with change. As in other de-
	veloping countries, the transformation process to potential nonfarm livelihood option
	has been widely recognized (Davis
	For instance, Phnom Penh's
	population has increased by 70% from about 1 million in the 1998 to 1.7 million in

  Table 2) considered to be the important determination of household's choices and income were identified: (i) human capital (age of household head, household size, female percentage in household, education and non-formal education, illness, food and

	The sur-
	vey was first conducted in 1993/1994 aiming to collect statistical information about living conditions and extent to poverty of the Cambodian population. It was used to monitor the Cambodian National Strategic Development Plan (NSDP) and to measure progress towards global development goals (i.e. Millennium Development Goals and Sustainable Development Goals). The survey was conducted intermittently between 1993/1994 to 2004 and it was until 2007 that it has been annual. CSES 2013 was the social capital (pension, remittance), and (iv) physical capital (values of agriculture, 13 non-food expenditure), (ii) natural and economic capital (land size, value of land), (iii) transportation and durable goods).

th survey of its kind. The sampling procedures and field operations manual were

detailed in NIS (2016)

. The survey was composed of a total of 3,138 households representing entire Cambodia.

Cambodia is divided into four main agro-ecological zones, namely Plateau/Mountain, Plain, Coast, and Tonle Sap

[START_REF] Yu | Rice production response in Cambodia[END_REF]

. The Plateau/Mountain zone includes the northeast Cambodia and Kampong Speu province in southwest bordering the coastal provinces is dense in forests and with low population density. The coastal zone consists of a very small portion of the country located in the Southwest. Crop cultivation, mostly rice, is mainly in the Northwest-Southeast corridor, known for a high population density. Thus, the northwest areas bordering Thailand around the Tonle Sap zone and southeast areas bordering Vietnam in the Plain zone are the main producers of rice. Dry season rice is mostly grown in the Plain zone, accounting for 70% of total land area of the country.

In our study, five household livelihood choices were selected: crops, livestock, fishery, forestry & hunting and nonfarm self-employment. Adapting SLA concept, key variables (

  Table3presents summary statistics for both dependent and independent variables we plan to use in the regression. The statistics of each variable is listed separately by the five main livelihood choices we discussed before and therefore the difference among the livelihood choice categories for those variables could be clearly seen. of key livelihood strategy. One interesting point is that for annual nonfarm income, the distribution among different categories is extremely unbalanced, implying that the income source for those households is quite unique. They are unlikely to have a secondary livelihood strategy apart from nonfarm livelihood strategy.

	Explanatory variables	Definition	Measurement
	Human capital
	Age of household head	Age of the head household member	Years
	Household size	Total number of household members	Number
	Female percentage	The percentage of female adult in the household	Ratio
	Education	The average of the highest education level ever accomplished for	Category
	Non-formal education	adults in household Number of people who received non-formal education in the	Number
	Illness	household Number of day absent from work in the past month	Days
	Natural and economic capital
	Non-food expenditure	Non-food expenditure in the past three months	Riel
	Food expenditure	Food expenditure in the past three months	Riel
	Land size	The area of owned farmland in the household	m 2
	Land value	The current price of the farmland owned in the household	Riel
	Social capital
	Pension	Pension from the government or other sources	Riel
	Remittance	Remittance from other family members	Riel
	Physical capital
	Agriculture equipment	Total value of the agriculture equipment in the household	Riel
	Transportation	Total value of the transportation in the household	Riel
	Household equipment	Total value of the household equipment	Riel
	Let's first focus on the dependent variables. For annual income in each livelihood
	category (the first column), obviously that the income in the corresponding category

(the first row) is the highest among other categories. For example, the mean in annual crop income is the highest in the crop livelihood category. That is natural due to the definition

Table 3 .

 3 Summary statistics of variables (by household key livelihood strategy clusters)

		Overall samples			Livestock			Forestry	Nonfarm
		(n = 3138)	Crop (n = 821)	(n = 231)	Fishery (n = 157)	(n = 578)	(n = 1351)
	Variables	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd	mean	sd
	Dependent variables
	Annual crop income ('0000 riels)	129	473	400	837	85	102	20	54	17	42	32	173
	Annual livestock income ('0000 riels)	35	166	15	92	335	431	5	33	2	17	15	104
	Annual fishery income ('0000 riels)	26	135	23	31	18	24	265	541	14	21	6	27
	Annual forestry income ('0000 riels)	39	60	48	33	48	34	40	23	79	111	15	28
	Annual nonfarm income ('0000 riels)	725	4404	16	87	23	87	5	29	1	21	1669	6594
	Annual household total income ('0000 riels)	954	4412	501	875	509	502	336	554	113	150	1737	6599
	Independent variables
	Human capital
	Age of household head	47.2	13.3	47.5	13.2	49.9	13.8	43.8	14.0	46.3	15.0	47.3	12.3
	Household size	4.6	1.7	4.7	1.7	4.5	1.6	4.8	1.7	4.4	1.8	4.6	1.7
	Female percentage	0.4	0.2	0.4	0.2	0.4	0.2	0.3	0.1	0.4	0.2	0.4	0.2
	Education	6.9	2.9	6.2	2.5	6.5	2.7	5.2	2.1	5.7	2.5	8.2	3.0
	Non-formal education	0.2	0.6	0.1	0.4	0.1	0.4	0.0	0.3	0.1	0.4	0.4	0.7
	Illness	1.1	5.1	1.0	4.5	1.6	6.9	1.0	4.0	1.5	6.2	0.8	4.6
	Natural and economic capital
	Non-food expenditure ('0000 riels)	595	651	472	436	511	519	394	242	383	368	799	827
	Food expenditure ('0000 riels)	871	400	761	319	761	311	751	268	698	281	1044	444
	Land size (m 2 )	9811 27871 21782 48805 12960 18077	5265	9512	5732	9180	4271 11268
	Land value ('0000 riels)	1916	6719	4161	9839	3161 12300	772	2203	860	1870	923	3650
	Social capital
	Pension ('0000 riels)	6	46	3	32	7	56	1	11	4	40	8	55
	Remittance ('0000 riels)	53	342	63	333	83	791	102	637	51	170	37	193
	Physical capital
	Agriculture equipment ('0000 riels)	86	452	186	582	88	196	32	118	28	116	55	496
	Transportation ('0000 riels)	449	1127	261	626	272	969	149	220	109	237	775	1527
	Household equipment ('0000 riels)	131	328	65	164	70	125	36	40	37	79	233	458

  Table 4) suggest five variables which have significant association with different livelihood strategies, namely household size, education, percent-age of female adults, non-formal and age of household head. Household size has positive association with fishery and forestry and negative relationship with nonfarm. The study further reveals that age of household head and female percentage negatively affects fishery strategy. Education was found to negatively correlate with natural resource-based strategies (i.e. fishery and forestry) in opposite to non-formal education which negatively affects nonfarm strategy.

Table 4 .

 4 Determinants of livelihood strategies (the multinomial logit regression)

	Dependent variables	Livestock	Fishery	Forestry	Nonfarm
	Independent variables
	Human capital
	Age of household head	1.605	-2.230 *	-1.281	-0.613
	Household size	0.147	1.982 *	2.716 **	-2.019 *
	Female percentage	0.218	-3.496 *** -1.072	0.734
	Education	0.807	-4.441 *** -2.835 **	-0.441
	Non-formal education	0.663	-1.885	1.325	2.638 **
	Illness	0.160	0.573	1.910	-1.773
	Natural and economic capital
	Non-food expenditure	2.121 *	1.560	-0.380	5.968 ***
	Food expenditure	-0.386	-1.143	-1.976 *	3.887 ***
	Land size	-2.179 *	-1.285	-3.751 *** -5.313 ***
	Land value	-5.099 *** -5.343 *** -6.280 *** -6.149 ***
	Social capital
	Pension	0.226	0.252	0.520	0.098
	Remittance	0.721	2.423 *	1.896	-2.223 *
	Physical capital
	Agriculture equipment	0.458	-1.660	-1.906	-2.939 **
	Transportation	0.738	1.302	-2.179 *	1.208
	Household equipment	0.826	0.433	0.071	7.913 ***
	McFadden's R 2	0.2951

Note: Crop strategy is the reference category; * , * * , * * * mean statistically significant at 10%, 5% and 1% level, respectively.

Table 5 .

 5 Determinants of household total income

Note: * , * * , * * * mean statistically significant at 10%, 5% and 1% level, respectively.

Table 6 .

 6 Categorization of village zones and the list of study villages within each zone.

	Zone	Distance from Na-	No. of villages Village names
		tional Road
	A	0-5 km	5	Chong Khlong, Kampong Thkoul, Phum Bei, Phum Pir,
				Phum Pram
	B	5.1-7 km	5	Chey Chumneah, Kbal Romeas, Peak Trabeak, Pou Pir,
				Samrong Pok
	C	7.1 -10 km	6	Boeng Chhuk, Chrab, Kampong Prak, Ou Preal, Srah
				Run, Trang
	D	10.1 -20 km	6	Kanchor, Kbal Peam, Samraong Prey Khiev, Tamao
				Leu, Trapeang Thma, Kampong La
	E	> 20 km	4	Charaoh, Kaoh Kaev, Kaoh Krak, Reang Til

Table 7 .

 7 Summary of livelihood options that respondents could reallocate labor and time resources to.A different set of options was presented to each respondent depending on the type of livelihood activities they were currently engaged in.

		Current livelihood activities respondent is engaged in
		Fishing only	Fishing & farming	Fishing & off farm activities
		a. Start farming ac-	a. Increase farming/	a. Changing the proportion of
		tivities	fishing activities	fishing and off-farm activities
	Livelihood op-	b. Start off-farm ac-	b. Start off-farm activi-	b. Start farming activities
	tions for reallo-	tivities	ties	c. Increase farming activities
	cating labour	c. Change to farming	c. Change to farming	d. Increase off-farm activities
	and time re-	only	only	e. Move to off farm jobs only
	sources	d. Move to off farm	d. Move to off-farm	f. Change to farming only
		jobs only	jobs only
			e. Rent farm land

Table 8 .

 8 Average

net annual income and percentage change in net income for scenarios A to D according to livelihood groups (1=fishing only, 2=fishing + other activity, 3=non-fishing activities)

Table 10 .

 10 List of 26 Community Fisheries (CFi) in Tonle Sap and sample size.

	Battambang CFi	N	Kampong Thom CFi	N
	Ang Cheung	13	Anlong Kahach	7
	Ansang Sak	12	Anlong Lat	9
	Bak Prea	17	Beoung Pralit	47
	Boeng Tuem	19	Beoung Spong	15
	Doun Tri	30	Beung Chang Beung Prang	9
	Kach Roteh	27	Doun Sdaeng	4
	Kampong Prahok	20	Neang Sa Ngeach	7
	Kampong Preah	24	Phat Sanday	10
	Kaoh Chiveang	14	Prek Kampong Cham	14
	Kouk Doung	14	Samaki Kampong Kor	20
	Preaek Toal	29	Sampoar Meanchey	6
	Rohal Soung	16	Ta Mun Mean Leap	4
	Svay Sa	22
	Thvang	28
	Battambang Total	285	Kampong Thom Total	152

Table 11 .

 11 Impact predictor and target variables for the CART model.

	Variables	Descriptions
	Dependent variables
	Ecological zone	Battambang (Northwest), Kampong Thom (Southeast)
	CFi area	Hectares
	Independent impact variables
	Fishing ground	Current fishing ground. Bigger, Same, Smaller.
	Livelihood	Overall livelihood since the CFi. Better off, Same, Worse off.
	Benefits	Benefit from CFi. Yes, No.
	Shared benefits	Benefits shared by all people in the CFi. Yes, No.
	More fish	More fish since the CFi. Yes, No.
	More income	More income since the CFi. Yes, No.
	More market	More fish market since the CFi. Yes, No.
	Alternative livelihood	Provide alternative livelihood since the CFi. Yes, No.
	Improved access	Improved fishery access since the CFi. Yes, No.
	Fishery condition	Current fishery condition. Very bad, Bad, Same, Good, Very Good.
	Living standard	Impact of CFi on standard of living, Yes, No.

Table 12 .

 12 Descriptions of explanatory variables used in logistic regression analyses. Community Fishery Area Management Plan? Yes, No. Rules and regulatiuon for fisheries management Are there rules and regulations for fisheries management? Yes, No.Six-month activity planCFi has an activity plan for the next six months? Yes, No.

	Variables	Descriptions
	Management and operation of CFi
	Years of CFi establishment	Number of years.
	Members	Number of CFi members.
	Institutional support for establishment of CFi	Has some organization or government supported the establishment
		of community fishery? Yes, No.
	CFi Area Agreement	Is there a Community Fishery Area Agreement? Yes, No.
	CFi Area Management Plan Is there a Conservation area CFi has a conservation area? Yes, No.
	CFi resolves conflict	CFi helps to resolve conflict in the fisheries? Yes, No.
	Illegal fishing	Is illegal fishing a problem? Yes, No.
	Persons committed illegal fishing	Who conducts the illegal fishing? Inside village, outside village,
		both inside and outside village.
	Rule enforcement against illegal fishing	Yes, No.
	Govenrment reduces illegal fishing	Government's effective action to reduce illegal fishing. Yes, No.
	CFi reduces illegal fishing	CFi works to reduce illegal fishing. Yes, No.
	CFi's regular patrol	Does the CFi do regular patrolling? Yes, No.
	Community Fisheries Committee (CFC)
	CFC drafts by-law and management plan	Yes, No.
	CFC represents CFi in conflict management	Yes, No
	CFC manages finance	Yes, No
	CFC participates in consultations	Yes, No
	CFC reports violations	Yes, No
	CFC manages fisheries	Yes, No
	CFC coordinates with commune council	Yes, No
	CFC develops network	Yes, No
	CFC engages with women in community	Yes, No
	CFC develops capacity of members	Yes, No
	CFC manages community development projects Yes, No
	Open and transparent election	Yes, No
	Transparent fisheries management	Yes, No
	Transparent decisions	Yes, No
	Represent all affected groups	Yes, No
	Accountable decision making	Yes, No
	Women participate in CFC	Yes, No
	Women actively participate in CFi activities	Yes, No
	CFC regularly meet	Yes, No
	Members consulted decisions	Yes, No
	Members informed decisions	Yes, No
	Members can examine finance	Yes, No

Table 13 .

 13 Results of logistic regression analysis for the determinants of impact of CFi using management and operation of CFi as predictor variables.

	Dependent

variables Independent variables: management and operation of CFi

	Years of CFi establishment	5.186 ***	1.909	4.013 ***	-0.138	-0.037
	Membership size	2.405 *	2.782 **	2.432 *	0.167	0.001 *
	Institutional support for establishment of CFi	-0.019	2.256 *	2.153 *	0.648	-2.404
	CFi Area Agreement	0.274	0.545	0.644	-0.013	-2.228
	CFi Area Management Plan	0.906	0.023	0.025	0.194	3.404
	Rules and regulatiuon for fisheries management	0.201	-0.024	-0.027	-0.502	14.258
	Six-month activity plan	4.322 ***	6.482 ***	8.834 ***	0.999	-1.177 **
	Conservation area	0.780	-0.657	0.155	0.393	17.609
	CFi resolves conflict	-0.141	0.842	1.348	1.894	1.542
	Illegal fishing	2.297 *	0.423	2.116 *	0.575	-2.885
	Persons committed illegal fishing -inside village	-2.735 **	0.114	1.567	-0.655	0.589
	Persons committed illegal fishing -outside village	-0.879	1.893	1.661	-1.516	-0.939
	Rule enforcement against illegal fishing	2.442 **	-0.130	1.408	0.476	19.224
	Govenrment reduces illegal fishing	-0.451	1.785	0.737	1.444	0.691
	CFi reduces illegal fishing	-1.607	2.242 *	3.172 **	3.648 ***	15.766
	CFi's regular patrol	-1.029	1.679	1.378	2.227 *	0.303
	McFadden's R 2	0.3513	0.2413	0.3342	0.2425	0.2493

Larger Fishing Ground Better Livelihood Income Change Shared Benefits Better Fisheries Condition

Better Livelihood Income Change Shared Benefits Better Fishery Condition environment

  in the Tonle Sap associates with the quantity and quality of water and habitat. However, the Fisheries Administration has little or no direct jurisdiction over the aquatic environment. Other sector development and priorities for water and land use such as irrigation, water supply, hydroelectricity or agriculture affect the overall resource quality

	Dependent variables	Larger Fishing
		Ground
	Independent variables: Community Fisheries Committee (CFC)
	CFC drafts by-law and management plan	1.718	2.035 *	1.954	-1.136	-0.820
	CFC represents CF in conflict management	0.042	-1.410	-2.622 **	-0.582	-0.776
	CFC manages finance	0.502	0.274	-0.670	-0.642	1.717
	CFC participates in consultations	-0.971	-0.877	-1.064	-1.174	0.749
	CFC reports violations	0.695	0.234	-0.634	0.087	-0.012
	CFC manages fisheries	2.856 **	2.034 *	-0.015	0.599	-0.029
	CFC coordinates with commune council	-2.236 *	-1.405	-0.803	-1.597	-1.000
	CFC develops network	4.682 ***	2.643 **	4.216 ***	2.715 **	1.399
	CFC engages with women in community	-0.286	-1.088	-1.182	2.125 *	-0.638
	CFC develops capacity of members	1.018	-1.575	-0.013	-1.095	-0.238
	CFC manage community development projects	0.662	0.064	1.107	-0.151	0.010
	Open and transparent election	-0.642	1.241	1.523	1.189	1.197
	Transparent fisheries management	0.733	3.274 **	2.859 **	-0.419	0.417
	Transparent decisions	-1.515	1.275	0.696	1.454	0.550
	Represent all affected groups	1.167	-0.653	0.795	2.647 **	0.865
	Accountable decision making	-0.294	-1.165	0.816	1.620	0.140
	Women participate in CFC	-1.091	2.573 *	1.653	-1.057	-0.014
	CFC regularly meet	1.104	3.747 ***	4.854 ***	0.441	0.873
	Women actively participate in CF activities	-1.552	3.361 ***	3.194 ***	0.831	-0.796
	Members consulted decisions	-1.629	-1.385	-1.254	-0.584	-1.800
	Members informed decisions	1.484	-0.418	1.486	1.049	-1.095
	Members can examine finance	1.191	1.312	0.790	3.676 ***	1.051
	McFadden's R 2	0.3132	0.2507	0.3030	0.5946	0.2493

  The decision to participate in livestock is positively influenced by human capital (i.e. non-food expenditure) and is discouraged by increased availability and value of land (natural and economic capital). Within the human capital, age of household head, female percentage and education discourage households' participation in fishery livelihoods. Moreover, households with higher total land value are less likely to depend on fishery. In contrast, the availability of labor force (human capital) and remittance (social capital) encourages the fishery participation. For forestry strategy, household size, education, and total land value have similar patterns and influences as on fishery livelihoods. Furthermore, food expenditure (human capital), land size and transportation (physical capital) encourage the participation in crop instead of forestry strategy. Lastly, nonfarm is influenced by all livelihood cap-

itals. Food and non-food expenditure, non-formal education (human capital), durable goods (physical capital) have positive relationship with nonfarm employment. On the other hand, household size, land size and value, and agricultural equipment discourage households' participation in this strategy.

Crop production volume and associated cost

  How many people live in your house? Number of people ...................... Please list the FIVE most important skills or training programs for the improvement of your household socioeconomic conditions and we would like you to indicate the competence of your household in general to perform the skill. .....................

	Car/truck/van Harrow/rake/hoe/spade/axe…
	Motorbike Insecticide sprayer 11.12 Do you think your children will also be in fishing business?
	3. Household composition Bicycle Semi-tractor (Kou Yon) YES__________NO_________
	TV/Radio/Other electronics Rice mill
	3.1 Sewing machine Water pump If NOT, why_______________________________________________________
	Electric fan Other (specify)
	3.2 Big pieces of furniture (i.e sofa, valuable bed, etc) What is your household ethnicity? _____________ ........................
	Generator for electricity Other (specify) 11.13 Production and associated cost
	1= Khmer, 2= Vietnamese, 3= Cham 4= Mix, 5 =Others (specify………………) Solar panel ........................ Fish Aquatic animals Other products
	Other assets........................ Total	Wet	Dry	Wet		Dry	Wet	Dry
	3.3 Other assets........................ Details of each individuals Amount caught/collected (kg)
	S.N Gender (1= M, 0=F) Total Part B. This part of the questionnaire we would like to ask you about the management of your re-Age (Enter "NA" if don't Marital Status (code) Relat'ship to HH head (code) Education ( code) 1st Oc-cup. (code) 2nd Oc-cup. (code) Total value of catch (riel) Operational/maintenance cost (i.e 8.7 Wet season Dry season Maize Cassava Beans Other veg-gear, boat) (Riel) Other: know) sources (farming, fishing, family labor etc.) Rice Rice etables ______ Consumption amount (kg) 1* 4 6 7 8.2 Production cost When did you start doing farming? YEAR__________ crops (Riel) 5 8.1 Total value of Do you do farming? YES_________NO________ Production (kg) 3 8. Farming activities Size (m2) 2 Barter/
	8 Consumption 8.3 What is the reason you started farming? 9 _______________________________________________________________ amount (kg)
	10 *Household head 8.4 What are you plating/growing in your farm? Barter/given _________________________________________________________________ away (kg)
	4. Training Sell amount (kg)
	8.5 Sell price ( ) Descriptions of the land property rights and land use
	4.1 Have you or any household members received any train-	YES_________NO________
	ings over the past years? 4.2 If answer YES, details of training Plot Num-ber Size of Property rights/land title 9. Livestock plot in Types of Trainings Crop grown 1 sq.m a. Permanent right with certificate Annual 9.1 Do you do livestock production? YES_________NO________	Perennial
	2 3 4 5 4.3 9.2 9.3 9.4	b. Permanent right with-When did you start? ______________________ a. Wet season Rice out certificate b. Dry season Rice c. Rented in c. Maize What is the reason you started livestock production? d. Rented out e. Public land f. Others d. Cassava _________________________________________________________________ a. Litchi b. Mango c. Orange d. Others e. Beans What type of animals are you raising? f. Other vegetables _________________________________________________________________
	Plot 1
	Plot 2 9.5	Competence to Perform the Skill Livestock production and associated cost
	Plot 3	1 = Not at all Competent, 2 = Little Competence, 3 = Moderately Competent, 4 = Fairly Competent Cows/ Buffa-Pigs Chickens Ducks Other (specify)
	Plot4	5 = Very Competent	loes
	Herd size (no.)
	Skills/Trainings Total quantity (Kg) Plot 5		Scale (1 to 5)
	a. ___________________________: b. ___________________________: Total value (Riel) c. ___________________________: 8.6 Do you own any of the following farming equipment? How many or how much? Can you ____ ____ Production cost (Riel) ____ d. ___________________________: ____ e. ___________________________: Consumption amount please estimate the approximate worth? (number/kg) ____ Farming Equipment Number Worth (total value) Barter/given away (kg)
	Cart (pulled by animal) Sell price (Riel/kg )
	Tractor 5. Resources and ownership Bulldozer 10. Aquaculture
	Plough
	Threshing machine 10.1 Do you do aquaculture? YES_________NO________

given away (kg) Sell amount (kg) Sell price (Riel) 12. Access to common property resources

  How large is the area of common property resources within your commune in which you or your family go for above products and benefits? Do you or any of your household members belong to any groups or associations involved with any of the following? If so, what is the group? Why did you join the group ?

	13. Off-farm activities, income, migration
	13.1 Of your family members, who are permanently and temporarily absent?
	S.N.	Name	Causes of absence	Occupation	Since when the	Money sent per
			(code)		(code)		job was started?	month (Riel)
	1
	2
	3
	4
	5
	14. Borrowing and lending activities
	14.1	Does your household have outstanding loans or debts to other households or institutions?
		YES__________NO_________
	14.2	Details of loan
	LN	How old is the	From whom did	What was the primary	What was the total	How much is	If interest is
		debt?	you obtain the	purpose for which	amount borrowed?	the outstanding	charged, what is
			loan?	your household bor-			loan now (this	the monthly rate of
	12.1	Do you have access to common property resources located within/outside your com-mune? (Month, put rowed the money? month)? interest? (Riels) "0"if <1 month) (Enter code) (Enter code) (Riels) (% or write "0" if
		YES__________NO_________				no interest is charged)
	12.2 1	If YES, what type of common property resources?
	2
	3		a. inundated forest
	4		b. big river/lakes
	5		c. flooded rice field
			d. bank/bed of river/lake
	14.3	e. irrigation canals/dike/small river If you borrowed money, you are obliged to sell fish to your money lender?
		f. others (Please specify):______________________ YES__________NO_________
	12.3 14.4	What kind of product and benefits do you get from these common property resources? If yes, do you get the market price for your fish from fish trader?
		YES__________NO_________
			Inun-	River/	Flooded	River	Irrigation/ca-	Oth-
	14.5	dated If no, how much less per kg in %? __________ lake ricefield	bank	nal/dike	ers
			forest
	a) Firewood 14.6 Over the past 12 months?), has your household lent money (or rice) to someone?
	b) Feed (animal, livestock, YES__________NO_________
	aquaculture etc)
	c) Bamboo/canes 14.7 If yes, how much? __________Riels
	d) Fish 14.8 e) Wild animals/birds Do you have any cash deposits in a banking institution, community saving group or micro-f) Irrigation water finance scheme? YES__________NO_________
	g) Transportation facilities h) Fruits/vegetables col-14.9 If yes, how much? ____________________Riels
	lection
	i) Snails/crab collection 15. Social network
	j) Fish-cage culture facili-
	ties 15.1
	k) Others
	12.4		Group/ associations				Name/Type	Why?
	related to main economic activity (fishing, farming,
	trade, manufacturing, etc)

Would you still be fishing only? YES_________NO________ If NOT, what do you see as possible options

	?
	a. Start farming activities
	b. Start off-farm activities
	c. Changing to farming only
	d. Moving to off farm jobs only
	e. Others (Please specify):_______________________________________

Compared to your current situation of 100% family resources in fishing, how would you manage your family labor resources? a

  . ____________________% for fishing activities b. ____________________% sending for off farm job c. ____________________% will go for upland cultivation d. ____________________% will rent the neighbouring farm land e. ____________________% Others (Please specify):__________________ B 50% reduction of fish production in Tonle Sap Lake and increased agricultural land due to decrease flood plain

	Would

you still be fishing only? YES_________NO________ If NOT, what do you see as possible options? a. Start farming activities b. Start off-farm activities c. Changing to farming only d. Moving to off farm jobs only e. Others (Please specify):_______________________________________ Compared

to your current situation of 100% family resources in fishing, how would you manage your family labor resources? a

  . ____________________% for fishing activities b. ____________________% sending for off farm job c. ____________________% will go to newly available agricultural land d. ____________________% will go for upland cultivation e. ____________________% will rent the neighbouring farm land f. ____________________% Others (Please specify):_____________________ A e) 50% reduction of fish production in Tonle Sap lake and everything else remains same

	6.2	Those who are currently fishing and farming
		( ________% fishing ________% farming)

Would you still continue with the same proportion of fishing and farming? YES_________NO________ If NOT, what do you see as possible options? a

  . Increase farming activities b. Start off-farm activities c. Change to farming only d. Moving to off farm jobs only e. Others (Please specify):_______________________________________

Compared to your current situation of________% fishing ________%farming, how would you manage your family labor resources? a

  . ____________________% for fishing activities b. ____________________% for current farming activities c. ____________________% sending for off farm job d. ____________________% will go for upland cultivation e. ____________________% will rent the neighbouring farm land f. ____________________% Others (Please specify):_____________________ B f) 50% reduction of fish production in Tonle Sap Lake and increased agricultural land due to decrease in flood plain

Would you be interested to do farming activities in newly available agricultural land? YES__________NO_________ If YES, Compared to your current situation of ________% fishing ________% farm- ing, how would you manage your family labor resources? a

  . ____________________% for fishing activities b. ____________________% for current farming activities c. ____________________% will go to newly available agricultural land d. ____________________% will go for upland cultivation e. ____________________% will rent the neighbouring farm land f. ____________________% Others (Please specify):______________________ C g) 50% reduction of fish production in Tonle Sap lake and increased agricultural land due to decrease in flood plain and increased jobs in cities

Would you be interested in diversifying your livelihood options and reallocating your family resources? YES__________NO_________ If YES, what do you see as possible options

	?
	a. Increase farming activities
	b. Start off-farm activities
	c. Change to farming only
	d. Moving to off farm jobs only
	e. Others (Please specify):_______________________________________

Compared to your current situation of ________% fishing ________% farming, how would you manage your family labor resources? a

  . __________________% for fishing activities b. __________________% for current farming activities c. __________________% sending for off farm job d. __________________% will go to newly available agricultural land e. __________________% will go for upland cultivation f. __________________% will rent the neighbouring farm land g. __________________% Others (Please specify):______________________ D h) Stagnation (more or less same situation as today)

Would you be interested to diversify your livelihood option and reallocate your family resources? YES__________NO_________ If YES, Compared to your current situation of ________% fishing _______% farming, how would you manage your family labor resources?

	If respondent'
	a. __________________% for fishing activities
	b. __________________% sending for off farm job
	c. __________________% for current farming activities
	d. __________________% will go for upland cultivation
	e. __________________% will rent the neighbouring farm land
	f. __________________% Others (Please specify):_____________________
	i)
	In the future, how do you think you will you manage your land?
	Same as today:___________ Differently:___________
	How would you manage your land resources?
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_____
	j)

s views does not match any options above then please use the space be- low to note down the response:

	16.3
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	____________________________________________

Those who are currently doing a combination of fishing and off farm activities ( ________% fishing and________% off farm jobs)

  A k) 50% reduction of fish production in Tonle Sap lake and everything else remains same

Would you still continue with the same proportion of fishing and off farm jobs? YES__________NO_________ If NOT, what do you see as possible options? a

  . Changing the proportion of fishing and off farm activities b. Start farming activities c. Moving to off farm jobs only d. Others (Please specify):_______________________________________

Compared to your current situation of ________% fishing ________% off farm jobs, how would you manage your family labor resources? a

  . ____________________% for fishing activities b. ____________________% sending for off farm job c. ____________________% will go for upland cultivation d. ____________________% will rent the neighbouring farm land e. ____________________% Others (Please specify):____________________ B 50% reduction of fish production in Tonle Sap Lake and increased agricultural land due to decrease in flood plain

Would you be interested to do farming activities in newly available agricultural land? YES__________NO_________ If Yes, compared to your current situation of ________% fishing________% off farm jobs, how would you manage your family labor resources?

  a. ____________________% for fishing activities b. ____________________% sending for off farm job c. ____________________% will go to newly available agricultural land c. ___________________% will go for upland cultivation d. ___________________% will rent the neighbouring farm land e. ___________________% Others (Please specify):______________________ C 50% reduction of fish production in Tonle Sap lake and increased agricultural land due to changes in flood plain habitats and increased jobs in Phnom Penh

Would you be interested to diversify your livelihood option and reallocate your family resources? YES__________NO_________ If YES, what do you see as possible options?

	a. Increase off-farm activities
	b. Start farming activities
	c. Moving to off farm jobs only
	d. Changing to farming only
	e. Others (Please specify):_______________________________________

Compared to your current situation of ________% fishing ________% off farm jobs, how would you manage your family labor resources? a

  . __________________% for fishing activities b. __________________% sending for off farm job c. __________________% will go to newly available agricultural land d. __________________% will go for upland cultivation e. __________________% will rent the neighbouring farm land f. __________________% Others (Please specify):________________________ D l) Stagnation (more or less same situation as today)

Would you still continue with the same proportion of fishing and off farm jobs? YES__________NO_________ If NOT, what do you see as possible options

  ? a. Start farming activities b. Increase farming activities c. Increase off-farm activities d. Change to farming only e. Moving to off farm jobs only f. Others (Please specify):_______________________________________

Compared to your current situation of ________% fishing and________% off farm jobs, how would you manage your family labor resources? a

  . __________________% for fishing activities b. __________________% for farming activities c. __________________% sending for off farm job d. __________________% will go for upland cultivation e. __________________% will rent the neighbouring farm land f. __________________% Others (Please specify):________________________ m)

	If

respondent's views does not match any options above then please use the space be- low to note down the response:

	16.4
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	_________________________________________________________________________
	____________________________________________

Those who are currently doing a combination of fishing, farming and off farm activi- ties ( ________% fishing ___________%farming and________% off farm jobs)

  A n) 50% reduction of fish production in Tonle Sap lake and everything else remains same

Would you still continue with the same proportion of fishing, farming and off farm jobs? YES__________NO_________ If NOT, what do you see as possible options

  ? a. Changing the proportion of fishing, farming and off farm activities b. Moving to farming activities c. Moving to off farm jobs only d. Others (Please specify):_______________________________________

Compared to your current situation of ________% fishing ________% farming ______% off farm jobs, how would you manage your family labor resources

  ? a.____________________% for fishing activities b.____________________% for current farming activities b.____________________% sending for off farm job c.____________________% will go for upland cultivation d.____________________% will rent the neighbouring farm land e.____________________% Others (Please specify):____________________ B 50% reduction of fish production in Tonle Sap Lake and increased agricultural land due to decrease in flood plain

Would you be interested to do farming activities in newly available agricultural land? YES__________NO_________ If Yes, compared to your current situation of ________% fishing________% farming __________% off farm jobs, how would you manage your family labor resources?

  a.____________________% for fishing activities b. ___________________% for current farming activities c.____________________% sending for off farm job d. __________________% will go to newly available agricultural land e.___________________% will go for upland cultivation f.___________________% will rent the neighbouring farm land g.___________________% Others (Please specify):______________________ C 50% reduction of fish production in Tonle Sap lake and increased agricultural land due to changes in flood plain habitats and increased jobs in Phnom Penh

Would you be interested to diversify your livelihood option and reallocate your family resources? YES__________NO_________ If YES, what do you see as possible options

	?
	a. Increase off-farm activities
	b. Start farming activities
	c. Moving to off farm jobs only
	d. Changing to farming only
	e. Others (Please specify):_______________________________________

Compared to your current situation of ________% fishing ________farming _________% off farm jobs, how would you manage your family labor resources

  ? a.__________________% for fishing activities b.__________________% for current farming activities c.__________________% sending for off farm job d__________________% will go to newly available agricultural land e__________________% will go for upland cultivation f__________________% will rent the neighbouring farm land g__________________% Others (Please specify):________________________ D o) Stagnation (more or less same situation as today)

Would you still continue with the same proportion of fishing, farming and off farm jobs? YES__________NO_________ If NOT, what do you see as possible options

  ? a. Start farming activities b. Increase farming activities c. Increase off-farm activities d. Change to farming only e. Moving to off farm jobs only f. Others (Please specify):_______________________________________

Compared to your current situation of ________% fishing _________% farming and________% off farm jobs, how would you manage your family labor resources

  ? a. __________________% for fishing activities b. __________________% for current farming activities c. __________________% sending for off farm job d. __________________% will go for upland cultivation e. __________________% will rent the neighbouring farm land f. __________________% Others (Please specify):________________________

If respondent's views does not match any options above then please use the space be- low to note down the response:

		What type of illegal fishing occurs?
		Is there any enforcement of rules against il-
		legal fishing?
		How many are outsiders coming into your
		fishing area?
		Only small fishing gear should be allowed	Agree________ Disagree________
		on the lake?
		Is the government taking effective action to	YES__________NO_________
		reduce illegal fishing?
		Does the Community Fisheries Committee	YES__________NO_________
		work to reduce illegal fishing?
		Does the CF do regular patrolling?	YES__________NO_________
		Have illegal activities	Increase________ same________ or de-
			creased_______ compared to last year?
		Have illegal activities	Increase________ same________ or de-
			creased________compared to five years
			ago?
	C	Community Fishery Committee (CFC)
		Are you a member of the Community Fish-	YES__________NO_________
		ery Committee?
		If yes, what is your position?
		Does the CFC engage in the following du-
		ties:	YES__________NO_________
		Draft by-laws and management plans	YES__________NO_________
		Represent CF in conflict management _________________________________________________________________________ YES__________NO_________ Manage finances YES__________NO_________ _________________________________________________________________________ Participate in consultations YES__________NO_________ _________________________________________________________________________ Report violations YES__________NO_________ _________________________________________________________________________ Manage fisheries YES__________NO_________ _________________________________________________________________________ Coordinate with commune council _________________________________________________________________________ Develop networks with other CFs and or-YES__________NO_________ _________________________________________________________________________ ganizations YES__________NO_________ _________________________________________________________________________ Engage with women in the community YES__________NO_________ _________________________________________________________________________ jects _____________________________________________________ Engage in community development pro-_________________________________________________________________________ Training and capacity building of members YES__________NO_________
		Were elections for the CFC open to every-	YES__________NO_________
		one and transparent?
		Do you feel that the CFC operates in trans-	YES__________NO_________
		parent manner in fisheries management?
		If NOT, do you feel that the CFC represents	YES__________NO_________
		your interests in fisheries management?
		Is the CFC open, clear and transparent in	YES__________NO_________
		the way it makes decisions?

In this study, the Tonle Sap consists of five provinces of Battambang, Kampong Chhnang, Kampong Thom, Pursat and Battambang. The total fishing lot area in Tonle Sap, excluding Banteay Meanchey before 2000 was

474,975 hectares.

Special thanks also go to National Institute of Statistics, Cambodia, for sharing Cambodian Socio Economic Survey data and Mr. SOK Sotheavuth for being so helpful and patience in answering any questions or providing clarifications to the data.

Thank you to the Belmont Forum, Agence Nationale de la Recherche, Erasmus Mondus -Techno 1 Project and the Open Society Foundation for funding this research and my mobility in France, Canada and US. I would also like to extend my thanks to

CHAPTER I: INTRODUCTION CHAPTER II: MATERIALS AND METHODS

CHAPTER IV: LIVELIHOODS DURING THE ECONOMIC TRANSFORMATION: DETERMINANTS OF HOUSEHOLD CHOICES AND INCOME

Ratha Seng [1,2] , Tongtong Fang [1] , Krishna KC [3] , Evan Fraser [3] , Sovan Lek [1,2] 1. Laboratoire Evolution & Diversité Biologique, Université Paul Sabatier -Toulouse III, 31062 Toulouse, France. Net income Nt,a, at time t (0 for current, 1 for future), and for livelihood activity a was calculated as:

Nt,a = Rt,a -Ct,a, Where C was the production cost associated with each livelihood activity (e.g., seed, fertilizer, transportation, labor).

Note that no fixed costs were collected in the survey; therefore, net income in this study is equivalent to net revenue. An exception was off-farm income, which was represented by the annual salary reported by respondents during interviews. Net fishing income was calculated differently because no fishing cost data were collected. First, fishing revenue was calculated by multiplying the average annual fish catch by the average selling price (Riel/kg) provided by each respondent who fished. If a respondent did not provide price information, an overall average price (i.e., average of all respondents' selling price) was applied.

We first checked a global fishing cost database [START_REF] Lam | Construction and first applications of a global cost of fishing database[END_REF] for Cambodia specific data, but none were available. Subsequently, we estimated fishing costs from Cambodian case studies, in which total fishing costs ranged from approximately 55% to 59% of fishing revenue (Hap & Bhattarai 2006 2 ; [START_REF] Sinh | Value Chain of Snakehead Fish in the Lower Mekong Basin of Cambodia and Vietnam[END_REF]. The midpoint of this rate was applied to fishing revenue to obtain net fishing income.

Economic impact of future scenarios to the Tonle Sap Lake

Hydropower development, climate change, and urban migration were identified as major drivers of change to the future of Tonle Sap Lake's ecosystem and inhabitants.

Increased development of hydropower dams, reservoirs, and irrigation schemes was expected to result in higher dry season water levels and lower flood peaks (Matti 2 [START_REF] Hap | Economic Assessment of Small-Scale Inland Fisheries and Wetland Livelihoods in Cambodia[END_REF] conducted an analysis of fishing profitability for 3 Cambodian studies. We used the results for Kampong Chhnang, which is adjacent to Pursat and located next to Tonle Sap Lake. The other two provinces were located in northern and southern Cambodia, away from Tonle Sap Lake.

Estimating net income for future scenarios

The following process was used to estimate the net income derived from livelihood activities under each future scenario:

1. For every scenario A-D, each respondent provided: a) whether they would continue with their current livelihood strategy; and b) how they would reallocate their time (t) to different livelihood options (Table 7). If in (a) the respondent did not change their current livelihood allocation, their current livelihood net income (N0,a) was assigned to that scenario.

2. The net income of each livelihood activity the respondent chose under each future scenario (N1,a) was calculated as: N1,a = Σ (N0,a * t1,a), where t is the proportion of time allocated to each future activity.

If an individual chose a new livelihood that he/she did not currently participate in (i.e., no current net income data was available for that activity), then a net income averaged across all respondents who currently participated in that activity was assigned. For example, if a group 1 respondent who currently only fishes chose to start farming, then his/her future farming income would be equivalent to the current average farming income obtained by group 2 and 3 respondents. Although we recognise that future scenarios will involve cost of living increases and price fluctuations, we did not account for these adjustments when estimating future net income because there was no explicit timeframe associated with our scenarios.

3. There were 2 scenario options for which no current benefits and costs data were availablerenting land to farm, and upland farming. Subsequently, the economic benefits from these activities were calculated as follows: Among all scenarios, respondents' choices generated the best economic outcome under scenario D (Stagnation). This may indicate that respondents were capable of coping with conditions similar to the present, but were unlikely to make appropriate decisions given future scenarios that they were unfamiliar with. This reinforces the concern expressed by Bond (2015) about households' lack of ability or willingness to change, especially if fisheries collapse. This inability to anticipate and consider the long term reflects myopic behaviour which likely stems from respondents' poor socioeconomic conditions and daily struggle to meet present needs [START_REF] Pauly | Small-Scale Fisheries in the Tropics: Marginality, Marginalization, and Some Implications for Fisheries Management[END_REF]. Their focus on the immediate and short term horizon is equivalent to having a high time preference [START_REF] Teh | Time preference of smallscale fishers in open access and traditionally managed reef fisheries[END_REF] ,which is not conducive for conservation outcomes [START_REF] Clark | The Economics of Overexploitation[END_REF][START_REF] Sumaila | Intergenerational discounting: A new intuitive approach[END_REF]. This suggests that future policies for increasing adaptive capacity will have to focus on strengthening the welfare and socio-economic conditions of local residents.

A consistent pattern across all future scenarios is that the majority of respondents chose to retain their current livelihood strategy. Of those who did change their livelihood allocation, a very small proportion (< 10% under every scenario) actually experienced a gain in economic benefits. This again suggests that respondents may not have the capacity to adapt to future conditions, or cannot anticipate the costs associated with changing their present livelihood practices in the future. Indeed, lack of knowledge and skills about farming and livestock raising practices were already among the main problems faced by farmers in the Tonle Sap area (Asian Development Bank 2012, p. 52); hence, it is not surprising that they would be reluctant to switch to entirely new livelihood activities. While fishers, who are the major livelihood group in this study, can make changes to their current fishing practices (e.g., using different gear, targeting different species, fishing at different locations), this still ties their future well-being to the

CHAPTER VI: DETERMINANTS OF IMPACT OF COMMUNITY FISHERIES IN THE TONLE SAP GREAT LAKE OF CAMBODIA

Ratha Seng [1,2, *] , Robert S. Pomeroy [3] , Peng Bun Ngor [1,4] , Di Yang [3] , Sovan Lek [1,2] 1. Laboratoire Evolution & Diversité Biologique, Université Paul Sabatier -Toulouse III, 31062 Toulouse, France.

Research and

Context

The Tonle Sap Lake ecosystem extends into the central plains, covering about 5 to 8 percent of Cambodia's total land area (MRC, 2003). Connected to the Mekong River by the 120 km long Tonle Sap River, the Tonle Sap Lake's surface area annually fluctuates from 2,500km 2 to over 15,000km 2 driven by seasonal flood pulse from the Mekong River accounting for 53.5 percent of total water inflows into the lake system (M. [START_REF] Kummu | Water balance analysis for the Tonle Sap Lake-floodplain system[END_REF].

The lake provides essential ecosystem services and supports livelihoods of at least 2 million people. In Cambodia, more than 80% of animal protein intake comes from fish [START_REF] Hortle | Consumption and the yield of fish and other aquatic animals from the Lower Mekong Basin[END_REF], of which the majority are from the Tonle Sap [START_REF] Baran | Fish resources in Cambodia (2001-2011). In Atlas of Cambodia -Maps on socioeconomic development and environment[END_REF].

Due to its unique flood pulse system and huge fish productivity, the Tonle Sap has significant social, economic and cultural values to local people for centuries. People have been adapting their life and livelihoods to the annual variations of the lake's water level and have closely connected themselves and ways of living to the lake and its natural resources. Rice and fish have been fundamental to local residents in the Tonle Sap region. Despite having traditionally adapted to the seasonal changes of the lake, the fishing communities have weak capacity to respond to unusual environment events and are among the poorest and most vulnerable in the Tonle Sap [START_REF] Nuorteva | Water, livelihoods and climate change adaptation in the tonle sap lake area, Cambodia: Learning from the past to understand the future[END_REF].

The Tonle Sap is also highly vulnerable to the changes in the Mekong River and the lake itself. Upstream dam development [START_REF] Arias | Impacts of hydropower and climate change on drivers of ecological productivity of Southeast Asia's most important wetland[END_REF]M. Kummu et al., 2014); private irrigation structures in the Tonle Sap [START_REF] Keskinen | The Tonle Sap Lake, Cambodia: waterrelated conflicts with abundance of water[END_REF]; and climate change, increasing population and other drivers [START_REF] Cooperman | A watershed moment for the Mekong: newly announced community use and conservation areas for the Tonle Sap Lake may boost sustainability of the world's largest inland fishery[END_REF] have ecological effects on the Tonle Sap fisheries and the sustainability of the resources at risk. Some researchers validate the immediate impact highlighting decreasing high-valued fish species [START_REF] Enomoto | Data mining and stock assessment of fisheries resources in Tonle Sap Lake, Cambodia[END_REF] and resource conflicts [START_REF] Keskinen | The Tonle Sap Lake, Cambodia: waterrelated conflicts with abundance of water[END_REF].

CHARPTER VII: CONCLUSIONS AND PERSPECTIVES APPENDIX A: QUESTIONNAIRE

Household Survey

Maintaining productivity and income in Tonle Sap fisheries in the Face of climate change This survey looks at the livelihood strategies of fishing dependent household in and around Tonle Sap Lake. We want to understand the household assets and how they make decisions in allocating their family resources. The goal is to identify ways in which the inhabitants in and around Tonle Sap Lake may be affected due to the changing fishery resources and also identify the voices of residents in managing fishery resources. We are very interested in your opinions, concerns, and ideas. To accomplish this, we need your help in completing this questionnaire. All households were randomly selectedall responses will be confidential. You are able to withdraw at any point during interview. If you choose to withdraw, your information will not be used. Your assistance is greatly appreciated. Do you have any questions about the survey? Do we have your agreement to proceed?

Participant understands role and has given verbal consent (please check)

Questionnaire for Household Survey

Part A. This first part of the questionnaire we would like to ask you about yourself, your family and your local residency. a. We changed from fishing to farming b. We changed from fishing to a combination of fishing and farming c. We changed from fishing to a combination of fishing, farming and off farm jobs d. We changed from farming to a combination of farming and off farm jobs e. We changed from farming to a combination of farming fishing and off farm jobs

Identification

Community Fishery Survey

The survey looks at the ways members of the community fishery groups participate in managing fishery resources and decision-making. We want to understand the perceptions of operation, impact, successes and challenges of community fishery. The goal is to assess the performance of community fishery in managing fishery resources in Tonle Sap lake. We are very interested in your opinions, concerns, and ideas. To accomplish this, we need your help in completing this questionnaire. You were randomly selectedall responses will be confidential. You are able to withdraw at any point during the interview. If you choose to withdraw, your information will not be used. Your assistance is greatly appreciated. Five years ago_____ Today ______ Overall quality of fish 1 -An area with no fish, where the water is so foul that nothing can live 2 -Some fish and the water is adequate 3 -Fish are abundant and the water is clean and productive Five years ago_____ Today ______ Compliance with fisheries rules 1 -No one obeys the fisheries rules 2 -Some people obey the rules 3 -Everyone obeys fisheries rules Five years ago_____ Today ______ Ease of collective decision making on community problems 1 -Very difficult for your community to decide on solutions to community problems (illegal fishing, peace and order) 2 -Some decisions are made 3 -Very easy for your community to decide on solution to community problems Five years ago_____ Today ______ Knowledge of fisheries management 1 -Fishers in your community have very little knowledge of fisheries management 2 -Fishers have some knowledge 3 -Fishers have adequate knowledge of fisheries management Five years ago_____ Today ______ Quickness of resolving community conflicts on fisheries related issues 1 -Your community takes a very long time to resolve fisheries related conflict 2 -Your community takes some time to resolve fisheries related conflict 3 -Your community resolves fisheries conflicts very quickly Five years ago_____ Today ______