domain: sdv shs

text:
Keywords: Farming systems, geo-agronomy, buffer zone management, water resource conservation, biodiversity conservation, farmer typology, typology of parcel management, Colombia

The Colombian environmental policy voted in 1993, which aimed to strengthen the protection of natural resources, particularly biodiversity and water, is totally unfavorable to farming in the strategic pa ´ramo ecosystem. However, many rural development practitioners and researchers believe that integrated management of the pa ´ramo is possible and that farming activities can be part of the solution along this agriculture-conservation frontier. This issue has become particularly acute on the Rabanal pa ´ramo (western cordillera), in Colombia, where the projected expansion of a core protection zone will soon include major areas currently used for agriculture and settlements. Although small-scale farmers have been living there for decades, the environmental authorities are intent on prohibiting farming activities in the entire protection area. A study of local history and aerial photos indicates that this zone has been a dynamic part of local farming systems since at least the 1950s and that the pa ´ramo has evolved from a subsistence farming area to a zone that now includes intensive potato production conducted by external entrepreneurs. The presence of these entrepreneurs is mainly due to small-scale farmers' need for a cost-effective solution to maintain the productivity of their pastures. By interviewing participants in the debate, as well as by mapping agricultural land that will soon be included in the protected area, objectives for action were developed that would result in more sustainable farming practices, thus enhancing the conservation of pa ´ramo biodiversity and water resources.

Integrating Farming and Pa ´ramo Conservation: A Case Study From Colombia

Ophe ´lie Robineau 1 *, Martin Cha ˆtelet 1 *, Christophe-Toussaint Soulard 2 , Isabelle Michel-Dounias 1,2 , and Joshua Posner 3

Conservation of pa ´ramo biodiversity and water resources: a central issue in the Andes

Protected areas, such as national parks and reserves, now cover more than 12% of the world's land area [START_REF] Chape | United Nations List of Protected Areas[END_REF]. However, as the United Nations-convened Rio conference highlighted, because of the failures of strict protection policies, it is crucial to have close links between environmental and development policies (IUCN/ UNEP/WWF 1991). Nevertheless, the ''protection versus development'' viewpoint remains a contentious element in the establishment of protected areas (He ´ritier 2007). This is not surprising, because integrated landscape planning, making specific choices about land use, wildlife protection, and resource development that are acceptable to communities and conservation authorities, remains a difficult task (Slocombe 1993, Galvin and[START_REF] Galvin | People, Protected Areas and Global Change. Participatory Conservation in Latin America, Africa, Asia and Europe[END_REF].

In this context, the Andean pa ´ramo, a unique mountain grassland ecosystem with distinct and very diverse fauna and flora [START_REF] Churio | The biodiversity of the Colombian pa ´ramo and its relation to anthropogenic impact[END_REF], located between the upper forest line (about 3000 m) and the permanent snow line (about 5000 m), is at a crossroads. Although protection of the pa ´ramo is playing a more valuable role in biodiversity conservation, water regulation, and carbon storage [START_REF] Van Der Hammen | Diagno ´stico, cambio global y conservacio ´n[END_REF], there is increasing demand from urban centers for potato and milk production (Figure 1). For decades, in most Colombian pa ´ramos, potato and dualpurpose cattle (meat and milk) production were the mainstay of family farms. More recently, an alternative system has expanded, with land being rented for a year for capital-intensive potato production followed by several years of grazing, which results in more pa ´ramo land being put under cultivation. However, this model of potato production is in direct confrontation with the national environmental policy. Indeed, the use of agrochemical inputs and the aggressive means of soil tillage linked with capital-intensive potato production run counter to the will to protect pa ´ramo biodiversity and water resources. Increasingly, the policy is unfavorable to farming in this ecosystem and is centered on the creation of protected areas free from productive activities.

In the tropical Andes, many researchers have focused on the ecology of these high-altitude tropical grasslands and on human-induced ecological effects on them [START_REF] Etter | Andean forests and farming systems in part of the Eastern Cordillera (Colombia)[END_REF]Cardenas and Vargas 2008). [START_REF] Hofstede | Effects of livestock farming and recommendations for management and conservation of pa ´ramo grasslands (Colombia)[END_REF] has shown that the combination of grazing and burning reduces soil organic matter levels and increases soil bulk density, which markedly reduces soil water retention capacity. More recently, other studies have been conducted to characterize the agricultural and settlement frontiers, which focused on socioeconomic aspects, hence providing new perspectives for integrated management of this fragile ecosystem. Lo ´pez [START_REF] Lo ´pez Sandoval | Agricultural and Settlement Frontiers in the Tropical Andes: The Pa ´ramo Belt of Northern Ecuador, 1960-1990[END_REF], working in the Ecuadorian pa ´ramo, highlighted the complex reasons for expanding or stabilizing agricultural pioneer zones. Llambi et al (2005), working in the Venezuelan pa ´ramo, reported on the necessary implementation of participatory planning to improve the conservation of the pa ´ramo ecosystem by incorporating local communities in land-planning exercises, which requires a deep understanding of pa ´ramo users' objectives (particularly those of farmers) alongside environmental objectives. In Colombia, however, little information is available to date on how to combine farmers' and environmental objectives.

The aim of the field research presented in this article, by using the specifics of 1 case study site, was to investigate how detailed information on the farming system can foster mutual understanding between local communities and environmental authorities, and facilitate negotiations between these 2 groups. The research relied on the hypothesis that, to enhance dialogue between farmers and institutions, it is necessary to give farmers' objectives and strategies due consideration. An analysis of the local farming systems was undertaken to highlight the drivers of land use changes and to identify options for allowing farmers to remain in the pa ´ramo while simultaneously meeting environmental objectives.

Material and Methods

Study site: the Rabanal pa ´ramo in Colombia

The Rabanal pa ´ramo is a key study area of the Andean Pa ´ramo Project. The Rabanal pa ´ramo is located 100 km north of Bogota ´(5u24900N; 73u36900W). It was chosen for inclusion in the project in part because the core protected area had been expanded from 2681 ha to 8600 ha in 2008 (IAvH 2008), which would markedly affect pa ´ramo land management and local incomes in the villages that surround the zone. In all, more than 1500 ha of cultivated land will soon be included in the protected area.

This study was conducted in the hamlet of Firita Pen ˜a Arriba, which belongs to the township of Ra ´quira (Figure 2). It includes an area of 1331 ha, of which 560 ha are now designated as part of the protected area outlined by the Rabanal management plan (IAvH 2008). The zone is divided into 2 parts:

1. A lower hilly part (below 3200 m), home to 90% of the 434 hamlet's inhabitants, including most of the village infrastructure, services, and 27 coal mines. 2. The pa ´ramo area (about 560 ha, above 3200 m) and home to 10% of the population. This is the focal area of the study (Figure 2).

An in-depth analysis of small-scale farmers' strategies and objectives

A 3-step analysis approach that combines agronomy, geography, and management sciences was used. The aim was to identify possibilities for introducing technical and MountainDevelopment organizational changes that would foster the integration of conservation of pa ´ramo biodiversity and water resources with sustainable livelihoods. The core of the research was a spatiotemporal analysis of farming activities to understand the logic of land use, that is, why and how farmers use pa ´ramo land. Spatial and temporal scales were considered, from the pa ´ramo to the cultivated parcel, and from the daily management of farming activities to the life cycle of a farm.

N The first step consisted of key informant interviews, with the objective of understanding the forces driving land use changes on the Rabanal pa ´ramo from the parcel scale to the whole pa ´ramo area used for agriculture. A focus was made on the agrarian history of the study area. In parallel, geographical data in the form of aerial photos (Instituto Geogra ´fico Agustin Codazzi, 1:24,000 scale, 1955, 1985, 2007) was gathered to identify the changes that had occurred in the pa ´ramo landscape.

N The second step was devoted to in-depth interviews with pa ´ramo farmers to understand the range of farm diversity and dynamics. Elements of the farming systems, notably the decision-making process for MountainDevelopment potato production, herd and pasture management, and economic data, were collected by using semistructured interviews. A typology of farmers was built, based on the strategies and objectives of the pa ´ramo agricultural users.

N The third step was the identification of farmers' room for maneuver in implementing more environmentally friendly farming practices. With the aid of a geographic positioning system, pa ´ramo fields were identified and mapped. A typology of parcels was built, based on the logic of land use, which corresponds to a theoretical model of land occupation. Indeed, farmers manage their parcels differently, depending on location and characteristics (size, slope, land tenure), and it was possible to build a typology for parcel management. Propositions for modified land use that fit both the typology of parcels and farmers' strategies were then developed.

Of the 35 users of the contested 506 ha of pa ´ramo, 23 participated in intensive interviewing (each interview lasted for 2-4 hours, most participants were reinterviewed up to 3 times). It took a team of 2 people a period of 6 months (May to October 2009) to collect the necessary information.

A brief history of agricultural use of the pa ´ramo

In the 1950s, the pa ´ramo landscape of Firita Pen ˜a Arriba consisted of a mosaic of agricultural parcels within the native pa ´ramo vegetation. Contrary to the advance of a well-delineated altitudinal frontier observed by [START_REF] Lo ´pez Sandoval | Agricultural and Settlement Frontiers in the Tropical Andes: The Pa ´ramo Belt of Northern Ecuador, 1960-1990[END_REF] in her study in Ecuador, in Firita Pen ˜a Arriba, there does not appear to have been an altitudinal pioneer frontier; rather, the cultivated and grazed area within the already colonized pa ´ramo expanded over time (Figure 3).

The farm territories were organized into 2 sites, in the upper and lower part of the hamlet, so to take advantage of the Andean verticality to diversify agricultural production (Figure 2B). The cultivated area did not exceed 1 ha on the farms. Family farmers mainly grew tubers on plots tilled by animal traction, with the help of children who would eventually inherit the farms.

This traditional scheme was modified in the 1960s with the departure of many of the younger generation to the lower part of the hamlet to work in the newly opened mines and to the cities. Today there are 133 coal mines and 772 coke ovens in the region (IAvH 2008). As a result of these employment opportunities, and migration to urban centers, today nearly 40% of the pa ´ramo land is in the hands of absentee owners and miners, some of whom rent their land to the remaining family farmers, and others have developed low labor-intensive animal production to complement their nonfarm income.

As a partial response to the loss of workforce, smallscale farmers started to put more emphasis on milk production and purchased Normandy dual-purpose cattle in the 1970s. As demand for dairy products increased with an increasingly urban population, the government made efforts to spread these breeds in Colombia. Livestock keeping requires less labor than potato production (the cattle are managed year round on meadows), and livestock keeping has progressively become the main source of income, thus replacing tuber production as the main source of revenue. This shift also coincided with increasing use of agrochemical inputs (especially fertilizer) on potatoes, which enabled farmers to maintain, or even to increase, their tuber production, despite a reduction in the area cultivated.

However, the dairy cows in the herd required higherquality feed; this is primarily found in new-growth pasture after potato production, and the maintenance of the forage quality of the pastures gradually became problematical. With up to 5 milking cows and their progeny, family farmers did not have enough higherquality pasture for their dairy animals. In the 1980s, a new solution presented itself. With the arrival of the Guatemalan potato moth (Tecia solanivora) in Colombia, agricultural entrepreneurs from the plains began looking for cooler land in the pa ´ramo to rent, with fewer pest problems, to produce potatoes on a large scale. Smallscale farmers in the pa ´ramo started to rent out parcels to these commercial potato growers as a way to solve their forage quality problems. Initially, they benefited from the entrepreneurs' tractors to clear the rest of pa ´ramo vegetation on their farm to create more meadows. Nowadays, on a more regular basis, their pastures benefit from the tillage and residual effect of fertilizer inputs associated with this intensive large-scale potato production. Almost all their plots are part of the potatopastures crop rotation: 1 year of potato (2 cycles) followed by 3 years of pasture. The logic of this rotation is (1) to benefit from the positive carry-over effect of potato production on pasture productivity and (2) to maintain a period of time between replanting potatoes on the same plot so to lower the pressure of soil-borne pests and diseases.

In 1993, law 99 was ratified (National decree 1713 of 2002). It affirmed the national will to follow the principle of sustainable development and reinforced the laws that govern management of natural resources and, more particularly, of pa ´ramo ecosystems. The country's biodiversity, considered as a national patrimony, was also considered as a priority for the common good. In the whole country, management plans were designed for all the strategic ecosystems to improve their protection. On the pa ´ramos, these plans have gone together with the design of protected areas free from productive activities so to protect both biodiversity and water resources.

Because of an increased focus on the role played by the Rabanal pa ´ramo in potable and irrigation water provisioning, as well as in biodiversity conservation, local

MountainDevelopment

environmental authorities threatened pa ´ramo farmers with fines for the land they had cleared. This strategy of the environmental authorities backfired, and some farmers, afraid of losing their farmland still covered by pa ´ramo vegetation, quickly cleared it to affirm their property rights.

Results of farming systems' analysis

Small-scale farmers: key managers of the pa ´ramo Based on the surveys and farm mapping, 3 general types of pa ´ramo agricultural users were identified with short-and long-term objectives that generate distinct impacts on the natural resource base:

1. Small-scale farmers of the pa ´ramo, 2. Miners and absentee land owners, 3. Entrepreneurs (commercial potato growers) from the plains.

It is estimated that small-scale farmers manage approximately 60% of the pa ´ramo because of the land they own and rent on a long-term basis from absentee owners. In addition, about 75% of the 80 to 120 ha rented out yearly to the commercial potato growers comes from the small-scale farms. For this reason, small-scale farmers are strategic actors in the management of the pa ´ramo.

Potato and dual-purpose cattle production: 2 complementary farming activities

Small-scale farmers in the pa ´ramo live exclusively from farming activities and have farms of about 20 ha. Based on the household budgets of 10 families, we estimated that their income is about US$ 150/mo, well below the Colombian minimum wage (US$ 230/mo, Decree 4965 of 27-12-2007). The main economic activities of small-scale farmers are dual-purpose cattle and potato production, which contribute 60% of their income for cattle and 25% for potato; 9% of their income comes from subsistence crops (maize, Andean tubers, and broad beans) and 6% comes from land rental.

These farmers generally keep 10 to 12 head of cattle, of which 5 are milking cows, and up to two thirds of the 20 ha of the farm are devoted to grazing each year. The main constraint faced by small-scale farmers of the pa ´ramo is the difficulty of maintaining forage productivity. They find that pastures need to be fertilized every 3 to 4 years, otherwise, pasture quality declines and affects dairy production. But, because of the small surface that farmers can cultivate in annual crops each year (rarely more than 0.2 ha because of the high costs of production), they are not able to renew the pastures as rapidly as they feel is necessary. Furthermore, they do not have the means to pay for directly fertilizing the pastures. To compensate for this, 5 to 7 ha of farmers' land is rented out yearly to be planted by commercial potato growers. These data suggest that the more important advantage of land rental is not the rental income itself, but the positive impact of associated tillage and fertilizer additions on subsequent forage productivity and quality. Indeed, land rental helps to support livestock production, which has become the main economic activity on the farms. Small-scale livestock production is closely linked with large-scale potato production, which constitutes the main activity targeted by the environmental authorities.

Potatoes are primarily cultivated in the pa ´ramo area, rather than in the lower village because of the pa ´ramo's larger fields and flatter terrain. At the lower site, parcels are sloping and rocky, which make cultivation and pasture renovation difficult. Currently, for 100 kg of tubers planted, which corresponds to 1000 m 2 , 200 kg of chemical fertilizer, 200 kg of lime, and 500 kg of poultry droppings are spread. Farmers consider it essential to apply these quantities to ensure a minimum economic yield (25 t/ha on commercial fields and 20 t/ha in farmers' fields). They adhere to a systematic treatment regime. Because growing potatoes is costly and risky, the farmers do not want to take the risk of losing their production because of insufficient soil nutrients and pest and disease incidence.

Somewhat surprisingly, small-scale farmers on their small potato plots follow nearly the same input schedule and the same cropping calendar, and apply the same proportions of agrochemicals that commercial potato growers do. They also do the soil tilling by tractor. However, the real difference lies in the production scale: although small-scale potato production occurs annually on less than 5% of the future protected area, up to 25% of this soon to be core area is annually cultivated by the commercial potato growers.

Dual-purpose cattle and potato productions are 2 complementary sources of income and are essential to balancing the family budget; whereas, the regular sale of livestock products provides for basic daily needs, family potato production brings more money immediately and allows investments to be made.

Starting point for designing localized integrated management strategies: a typology of parcel management

The underlying logic of land use is related to the parcels' characteristics, the spatial organization of the farm territory, and the system of land tenure. A classification of fields was made according to the way farmers manage their parcels to enable a spatial approach of the environmental impact of agriculture. Mapping this typology enables one to visualize the overlapping of crucial environmental issues (eg protection of wetlands, of plots with endemic species) and to locate farming practices unfavorable to the conservation of natural MountainDevelopment resources (eg application of agrochemical inputs on potatoes near or on a wetland, tillage of plots of spontaneous vegetation). Thus, mapping is a good basis for initiating a discussion among the stakeholders, formulating specific problems to be tackled, and starting negotiations. It was thought that this would be an important input to the process of designing new practices that result from a compromise between the current constraints encountered by agricultural users and the of environmental authorities. The 3 types of land-use parcels and their management (Figure 4) are:

1. Large (3 to 8 ha) relatively flat parcels that are used for grazing for 3 years and then rented out to commercial potato growers for a year (this kind of parcel represents more than 85% of the 560 ha soon to be incorporated into the core area). From the small-scale farmers' point of view, a key issue in reducing largescale potato production on these parcels would be in finding alternatives to restore their pastures. The low stocking rate, which does not exceed 1 animal unit per hectare, suggests that there are possibilities of land intensification in the livestock system. 2. Parcels around the farmsteads where the restoration of pastures follows family potato production (this kind of parcel represents 10% of the core area). Because potato production is important to the household economy, on this relatively small area, sustainable management practices for potato production could be promoted. Reducing both the costs of production and the impact of potato growing on natural resources, MountainDevelopment through reduction of the use of agrochemical and promotion of less-intensive tillage practices, would fit both environmental authorities' and farmers' objectives. 3. Parcels inaccessible to tractors, where the pastures are not renovated (only 1% of the area). On these areas left as permanent grazing, a compromise could be found between letting the spontaneous vegetation grow again and controlling the grazing so as to keep plots of spontaneous pa ´ramo vegetation within the farms.

The 3 kinds of parcels were mapped at the pa ´ramo scale in the study area (Figure 5), which allows us to consider the potential role of farming practices in having a negative impact on natural resources according to the pattern of these 3 field types at the landscape level. With the priority of improving integrated management of natural resources, one can then identify actions according to the characteristics of the individual site. For example, in the Quebrada Baricha sector (Figure 5), where mostly parcels of type 3 are found; a third of the site is exclusively under intensive potato production each year, which means that the impact of farming activities might be greater in terms of water contamination. Moreover, parcel configuration (large parcels without obstacles) is unfavorable to the maintenance of ecological corridors and hence to the maintenance of pa ´ramo biodiversity within the area used for agriculture.

Future prospects and discussion

One can imagine 3 scenarios over the next decade:

1. Environmental legislation is strictly enforced, which would eventually lead to the disappearance of smallscale farming in the area because a reallocation of activities to the lower part of the hamlet is not possible due to small holding and rough terrain; 2. Environmental legislation is not enforced, so the current dynamics would continue, which results in an increasing percentage of absentee land owners and commercial potato growers on the pa ´ramo, because only a few new small-scale farmers would settle there; or 3. Small-scale farming is supported with the objective of enhancing farmers' incomes and improving their integration with the pa ´ramo environment.

To see the third scenario happen and to build a consensus around protecting the pa ´ramo, negotiations among the stakeholders, support to village organizations, and research are essential.

The geographical approach to farming practices, with its spatial configuration of farming activities, highlights the logic of land use in a space and time perspective, evaluating the impact of farming activities on the environment according to the location of farming activities. However, it allows one to link land use to the farm level, which is where these decisions are taken [START_REF] Soulard | Les agriculteurs et la pollution des eaux. Proposition d'une ge ´ographie des pratiques[END_REF].

The methodology used in this research provides valuable inputs to stimulate dialogue among the different stakeholders of the pa ´ramo's management and to initiate a negotiation process. The results would enable the environmental authorities to better identify the constraints that lead farmers to adopt unsustainable practices and thus to consider the root problem to be tackled, rather than adopt a strict position where any activity is prohibited on the pa ´ramo.

Results from our case study were discussed with farmers in the neighboring hamlets, who generally received them positively. To achieve integrated management of the pa ´ramo, similar studies should be conducted in the other hamlets included in the extension of the protection area. Then multistakeholder platforms could be implemented with the different actors concerned by land use planning, both at the hamlet and at the pa ´ramo scale. Until now, farmers have been excluded from conservation planning. Opening discussion and promoting farm visits with farmers and environmental authorities to have an exchange about conservation issues would improve mutual understanding of each other's objectives, expectations, and constraints. The inclusive design of solutions that suit farmers' strategies and help them to live better on farming activities might then induce a change in farmers' behavior.

However, for this work to be complete and for all the necessary inputs to go to the negotiation table, information is needed on the hydrology of the 3 microwatersheds (Quebradas) outlined in Figure 5, as well as on the distribution of key pa ´ramo plant communities. Then, with the environmental and farming systems information available, the actors (especially small-scale farmers, commercial potato growers, environmental authorities, and research institutes) could join at the table to discuss a micromanagement plan for the different zones. Some of the elements of the compromise will be the following:

N Developing improved pasture management techniques.

Although it remains a difficult task to improve pasture management in an ecologically and economically wise manner [START_REF] Hofstede | Effects of livestock farming and recommendations for management and conservation of pa ´ramo grasslands (Colombia)[END_REF], alternative methods of pasture restoration without frequent tillage and heavy fertilization would have to be identified, as well as grazing management patterns that protect particularly fragile landscapes and maintain pa ´ramo biodiversity.

N Using less chemical inputs. There are discrepancies between actual and recommended practices for potato cultivation (it has been estimated that farmers apply 3 times more nitrogen than recommended by the Secretary of Agricultural and Rural Development of Cundinamarca). Along with efforts to apply best management practices on small-scale farmers' potato plots, hydrological monitoring could take place to estimate the impact of farming practices on surface water quality, by comparing the 3 microwatersheds in Figure 5 (Quebradas El Moral, Seca, and Baricha). This would provide a basis to determine the level of contamination of the streams and the source of contamination, to target the farming practices involved, and to identify margins of progress that could be reached to lower the impact of farming activities on water quality.

N Setting aside key landscape areas (for conservation of biodiversity and water resources), and establishing buffer strips between pastures and potato fields and stream channels. These would protect the streams from both animal excrement and agrochemical residue and would make it possible to keep ecological corridors within and between the farms, thus participating in the maintenance of pa ´ramo biodiversity.

The case studied here illustrates a situation found elsewhere in the Andes, where high input potato production is taking place on the pa ´ramo, thus impacting on the maintenance of the pa ´ramo's biodiversity and on water quality. Moreover, with a warming climate, it is likely that this type of farming will be possible at higher elevations. In other Colombian and Venezuelan pilot sites of the Andean Pa ´ramo Project, the link between potato and livestock production has been observed, raising the same environmental issues.

The Venezuelan agents of the Andean Pa ´ramo Project highlighted the importance of building a consensus among the different participants included in the establishment of a protected area [START_REF] Yerena | Building consensus on biological corridors in the Venezuelan Andes[END_REF] to involve them in the participatory process, from project presentation to the technical evaluation of the action plan designed. Moreover, an integration of spatial scales and disciplines to highlight the links between farmers' strategies, environmental and agricultural policies, and biophysical and socioeconomic environments makes improvements in the integrated management of natural resources possible [START_REF] Castella | Une me ´thode d'analyse multi-e ´chelle des transitions agraires. Application aux zones de montagnes dans le Nord Vie ˆt-Nam[END_REF].

FIGURE 1

 1 FIGURE 1 (A) Small-scale farmers planting potatoes; (B) a farmer spraying a potato field; (C) sheep on the pa ´ramo used for agriculture; (D) entrepreneur planting potatoes; (E) herbaceous pa ´ramo. (Photos by Martin Cha ˆtelet and Ophe ´lie Robineau)

FIGURE 2

 2 FIGURE 2 Location and spatial organization of the study site Firita Pen ˜a Arriba. (Graphic design by Martin Cha ˆtelet and Ophe ´lie Robineau)

MountainDevelopment

FIGURE 3

 3 FIGURE 3 Evolution of the agricultural frontier over time in Firita Pen ˜a Arriba (based on an aerial photo interpretation and on-the-ground mapping). (Graphic design by Martin Cha ˆtelet and Ophe ´lie Robineau)

FIGURE 4

 4 FIGURE 4 Example of the territorial organization of a family farm in Firita Pen ˜a Arriba. (Graphic design by Martin Cha ˆtelet and Ophe ´lie Robineau)

Mountain Research and Development http://dx.doi.org/10.1659/MRD-JOURNAL-D-10-00048.1

ACKNOWLEDGMENTS

The research was conducted thanks to grants from the Proyecto Pa ´ramo Andino and from the Institut des Re ´gions Chaudes of Montpellier SupAgro. It was supported locally by the Colombian Alexander von Humboldt Research Institute (IAvH). The two field researchers are grateful to the IAvH for its help and support: Carlos Tapia, Adriana Vasquez, Tatiana Menjura, Maria Isabel Vieira, Maria Antonia Espitia, Diana Duque Marin, and Maria Paula Quiceno. They also thank all the pa ´ramo farmers of vereda Firita Pen ˜a Arriba, especially Campo Elias and Martina, Florencio, Isidro and Maria, Salustinao and Ana Olga, Florinda, Helena, and Feliz and Flor.

MountainDevelopment

Mountain Research and Development http://dx.doi.org/10.1659/MRD-JOURNAL-D-10-00048.1


J Trefan

Jean Pierre Bloom-Hansen

A B Bidanel

Catherine Doeschl-Wilson

Larzul

Keywords: quality, meta-analysis, pig

come

ABSTRACT: Technological meat quality is a significant economic factor in pork production, and numerous publications have shown that it is strongly influenced both by genetic status and by rearing and slaughter conditions. The quality of meat is often described by meat pH at different times postmortem, as well as by color and drip loss, whereas carcass quality is often characterized by lean percentage. A meta-analysis of findings relating to 3,530 pigs reported in 23 publications was carried out to assess the effects of the halothane gene, sex, breed, and slaughter weight of animals on 7 selected variables: pH at 45 min postmortem, ultimate pH, reflectance (L*-value), redness (a*-value), yellowness (b*-value), drip loss, and lean percentage. Two statistical methods were used in the meta-analysis: the method of effect size and the better known random effects model. The method of effect size was associated with Markov chain Monte Carlo techniques for implementing Bayesian hierarchical models to avoid the problems of limited data and publication bias. The results of our meta-analysis showed that the halothane genotype had a significant effect on all analyzed pork quality variables. Between-study variance was evaluated with the [START_REF] Cochran | The combination of estimates from different experiments[END_REF] Q-test of heterogeneity. Meta-regression was used to explain this variance, with covariates such as breed, sex, slaughter weight, and fasting duration being integrated into different regression models. The halothane gene effect was associated with the breed effect only for the following variables: L*-value, b*-value, and drip loss. Slaughter weight contributed significantly only to the explanation of differences in ultimate pH between homozygous genotypes. In response to inconsistencies reported in the literature regarding the difference between the genotypes NN and Nn, results of the meta-analysis showed that the difference between these 2 genotypes was significant for all the analyzed variables except the a*-value.

INTRODUCTION

Pork quality depends on genetic factors, environmental factors, and their interactions. A number of publications [START_REF] Sellier | Genetics of pig meat quality[END_REF] suggest that pork qual-ity is strongly influenced by the effect of overall genetic type, by individual genes (especially the halothane and RN genes), and by rearing and slaughter conditions. Although the mutated halothane "n" allele is considered fully recessive, there is conflicting information regarding the meat quality of heterozygous animals [START_REF] Monin | Effects of the halothane genotype and slaughter weight on texture of pork[END_REF][START_REF] Channon | Halothane genotype, pre-slaughter handling and stunning method all influence pork quality[END_REF][START_REF] Miller | Influence of sire line and halothane genotype on growth performance, carcass characteristics, and meat quality in pigs[END_REF]. Another unresolved debate concerns the effect of the halothane gene on ultimate pH in LM [START_REF] Larzul | Effect of halothane genotype (NN, Nn, nn) on growth, carcass and meat quality traits of pigs slaughtered at 95 kg or 125 kg live weight[END_REF][START_REF] Fisher | Halothane genotype and pork quality. 1. Carcass and meat quality characteristics of three halothane genotypes[END_REF]. In response to these gaps in the scientific literature, we chose to combine existing results in a meta-analysis (i.e., an analysis combining published results in a statistically sound way; [START_REF] Dumouchel | Bayesian meta-analysis[END_REF]. This method is particularly useful when results from independent studies are contradictory because it increases statistical power [START_REF] Cucherat | Manuel pratique de méta-analyse des essais thérapeutiques[END_REF]. The aim of this study was to use meta-analysis to estimate the effect of the halothane gene on 6 of the most important pig meat quality attributes: muscle pH measured 45 min (pH45) or 24 h (ultimate pH; pHu) postmortem, color coordinates (L*, a*, and b*), and drip loss (DL). For carcass quality, we analyzed the difference in lean percentage (lean%) between NN and Nn animals. Statistically, we compared 2 meta-analytical methods: the conventional random effects (RE) regression method and the effect size method. The RE regression method is commonly used in animal production studies, whereas the effect size method refers to the classical meta-analysis approach commonly performed in medical studies. The latter is considered more suitable for meta-analysis of a small number of studies but has the disadvantage that it allows only pairwise comparison between the analyzed factor levels.

Meta-analysis

MATERIALS AND METHODS

Animal Care and Use Committee approval was not obtained for this study because the data were obtained from an existing database.

Data Collection

For meat quality, the criterion for selecting publications was that they reported the effect of the halothane gene on 1 or more measurements of pork quality and compared the 3 halothane genotypes (NN, Nn, and nn). The measurements of pork quality extracted from studies were all taken in LM; they included pH45, pHu, objective color measurements determined with a Minolta Chroma Meter (CIE L* as a score of reflectance, a* as a score of redness, and b* as a score of yellowness; CIE, 1978) measured 24 h postmortem, and DL as a measurement of weight loss determined after 24 or 48 h of storage at 4°C and expressed as a percentage of the initial weight of a muscle sample. For carcass quality, the criterion for selecting publications was that they reported the effect of the halothane gene on lean%. Only the comparison of NN and Nn was retained. The studies had to be published as reviewed papers or conference proceedings, in English or in French, after 1990 for the halothane status to be established through molecular genotyping [START_REF] Fujii | Identification of a mutation in the porcine ryanodine receptor identified with malignant hyperthermia[END_REF]. The search was conducted through the Web of Science bibliographic database (http://www.isiwebofknowledge.com/).

The database included general information (e.g., titles, author names, dates of publication), experimental qualities (e.g., preslaughter treatment, feed composition, breed, sex, and castrate status), and other quantitative data (e.g., slaughter weight, slaughter age, statistics used in the original analysis that were necessary for the present meta-analysis). Only 6 publications were excluded because they compared only the 2 genotypes NN and Nn for all the analyzed attributes except lean%. Publications reporting several experiments were dealt with by assigning a specific code for each experiment. Each observation in the meta-analysis corresponded to the mean of each treatment group. The selected publications were further required to provide intraexperiment variation, expressed either as SEM (or SE) or SD, for the mean of each treatment group. Publications in which this information was missing were excluded. The bibliographic search yielded a total of 55 studies. Selection for an effect of the halothane gene on the 7 analyzed attributes narrowed this number to 23 publications published between 1990 and 2008 and 74 experimental groups (see Appendix Table A1), representing 3,530 pigs. In the sensitivity analysis, the influence of each individual study was evaluated by estimating overall effect size in the absence of one or more studies. Five studies were excluded in the context of sensitivity analysis.

Statistical Analysis

Effect Size Method. The effects of the halothane gene on pH45, pHu, L*, a*, and b* were evaluated using the mean difference or effect size method described by [START_REF] Whitehead | A general parametric approach to the meta-analysis of randomised clinical trials[END_REF]. For DL and lean%, the standardized effect size was used because the measurement methods for these 2 attributes differed from 1 study to another [START_REF] Whitehead | Meta-Analysis of Controlled Clinical Trials[END_REF]. The effect size method allows the comparison of 2 population groups (i.e., a treatment and a control group). The effect size (θ) was calculated as the difference between the means of 2 genotypes for each attribute. For example, in the comparison NN vs. nn, NN was considered the control group and nn was considered the treatment group. The standardized effect size was estimated by dividing this difference by its pooled SD. Reported SE, and the number of animals in the treatment and control groups, were used to calculate the pooled SD of each effect size [START_REF] Searle | Variance Components[END_REF]. Effect size estimates on data pooled across experiments were obtained with a fixed effects model [START_REF] Mantel | Statistical aspects of the analysis of data from retrospective studies of disease[END_REF].

The general fixed effects model is given by q q e i i  = + , for (i = 1,…,r), where r is the number of studies, q  is the maximum likelihood estimate of the effect size in study i, θ is the common effect size, and ε i is the error term for the ith study. Effects were assumed to be nor-

mally distributed: θ σ i N   q e
, .

( )

Forest plots, showing the point estimate and the 95% confidence interval (CI) of the individual experimentlevel effect size, were used to visualize the data. The plots of the 3 halothane genotype comparisons for each attribute are included as online-only data supplements (http://jas.fass.org/content/vol88/issue9/).

The global null hypothesis that the treatment difference in all studies was equal to zero was tested using the association test U [START_REF] Whitehead | Meta-Analysis of Controlled Clinical Trials[END_REF]. This test was performed by comparing the statistic

U w w i i i r i i r = ae è ç ç ç ç ö ø ÷ ÷ ÷ ÷ ÷ = = å å q  1 2 1
with the χ 2 with 1 df, where w i is the inverse of the variance of the effect size q i . Variation in experiment-level effect size was assessed with a χ 2 test of heterogeneity, denoted as the Q 2 -test. The null hypothesis was that the treatment effect would be the same across all r trials. The null hypothesis was rejected if the heterogeneity test statistic was greater than a critical value that separated the upper 5% of a χ 2 with (r -1) df [START_REF] Cochran | The combination of estimates from different experiments[END_REF]. With heterogeneous data, an RE model was used to estimate effect size by considering study a random factor (Der Simonian and Laird, 1986). The general RE model is given by q q n e i i i  = + + , where ν i is the RE of study i, ν i ~ N(0, τ 2 ), and τ 2 is the between-study variance. It follows that

q q e i N   , ² . σ τ 2 + ( )
The heterogeneity of results among trials was quantified using the I 2 -statistic [START_REF] Higgins | Quantifying heterogeneity in meta-analysis[END_REF]. The I 2 -statistic described the proportion of the total study variance that was due to between-study variation; it was calculated as

I Q r Q ² ² ( ) ² . = --1 100
Where I 2 -values were greater than 50%, a meta-regression was carried out to explore the source of the heterogeneity. Meta-regression formally tests whether there is evidence for different effects in different subgroups of trials. Meta-regression extended the RE meta-analysis by including one or more covariates to explain heterogeneity in treatment effects.

A Bayesian hierarchical model was adopted when data were heterogeneous, especially in the meta-regression of effect size, to estimate the model parameters. The analysis was performed using Markov chain Monte Carlo methods through the Bayesian computation software Winbugs [START_REF] Spiegelhalter | Win-BUGS User Manual[END_REF]. In total, 10,000 iterations were dismissed as burn-in and the following 500,000 iterations were used for parameter estimations. Satisfactory convergence of the simulated Markov chains to the target posterior distribution was assessed using the diagnostics in Winbugs. The Bayesian estimations of the overall and covariate effects were made systematically where the heterogeneity test was significant. Both regression and Bayesian methods were applied in effect size estimations; it was therefore convenient to define the phrase "significantly different from 0" to cover both the situation in which there was a 95% CI that did not include 0, and a Bayesian 95% CI that did not include 0.

Publication bias was investigated using funnel plots [START_REF] Light | Summing Up: The Science of Reviewing Research[END_REF]. In these funnel plots, a measure of study size is shown on the horizontal axis and effect size is plotted on the vertical axis. It was expected that, in the absence of bias, the plot would resemble a symmetrical funnel on its side. If there was bias, for example, because smaller studies showing no statistically significant effects remained unpublished, the plot would be asymmetrical. In these situations, the effect calculated in the meta-analysis might have been overestimated. Unfortunately, the small number of experiments eligible for meta-analysis in this study made interpretation of funnel plots difficult. Publication bias was therefore also investigated statistically using the Egger test [START_REF] Egger | Bias in meta-analysis detected by a simple graphical test[END_REF], which is more appropriate for a small sample size.

RE Regression Method.

This meta-analytical approach involved the application of a regression model to all data. The meta-analytic model included pig genotype, breed, sex (discrete variables), and slaughter weight (continuous variable). Experiment was taken into account as an RE [START_REF] St-Pierre | Invited Review: Integrating quantitative findings from multiple studies using mixed model methodology[END_REF].

The linear mixed model was Y ijk = μ + S i + a j + bX ij + e ijk , where Y ijk is the independent variable; μ is the overall mean; S i is the RE of the ith study, assumed as

 iid s N 0, , 2 s
( ) a j is the fixed effect of the jth level of factor; b is the overall regression coefficient of Y on X (a fixed effect); X ij is the value of the continuous predictor variable; and e ijk is the residual error, assumed as

 iid e N 0, . 2 s ( )
The variables e ijk and S i are assumed to be independent random variables. In view of the limited number of data, interactions between different factors were not included. Covariates that were not significant at a P-value of 0.05 were removed from the model.

To account for unequal variance among studies, all variables were weighed by the reciprocal inverse of their squared SE. In addition, an unstructured variance-covariance matrix was assumed for the random part of the model. The covariance parameter was considered different from 0 if the P-value was less than 0.10. A P-value greater than the traditional P = 0.05 was used because accurate estimations of variances and covariances require a considerable number of observations [START_REF] St-Pierre | Invited Review: Integrating quantitative findings from multiple studies using mixed model methodology[END_REF]. Computation was carried out using the MIXED procedure (SAS Inst. Inc., Cary, NC). All models were evaluated for the assumptions of normality and constant variance. The test for normality used the UNIVARIATE procedure of SAS. A Levene test of the residuals (P < 0.05) was used to test the assumption of constant variance.

To test the robustness of the results, an analysis of interstudy variability was carried out by comparing interstudy variance with intrastudy variance. It was recommended that it be stated, before the analysis, what size of estimated variance attributable to study would be considered negligible [START_REF] Sauvant | Meta-analyses of experimental data in animal nutrition[END_REF]. In our study, the proportion of the total study variance that was attributable to interstudy variation was computed as

r = + σ σ σ s s e 2 2 2 ,
following the method described by Hox and de Leeuw ( 2003), where σ s 2 represents the variation between studies and σ e 2 is the sampling variance. The variances σ s 2 and σ e 2 were estimated using a REML method. As in the effect size method, when the ρ-statistic exceeded 50%, a meta-regression was carried out to explain the between-study variability.

RESULTS

Effect of the Halothane Gene on pH45 and pHu

A significant effect of the halothane gene on pH45 was confirmed by both methods (Tables 1, 2, and3), with differences between the 3 genotypes being significant. Meta-regression may better explain the effect size heterogeneity for the comparison Nn vs. nn because the difference between these 2 genotypes was partly ex-plained by fasting duration (P = 0.008) when it varied between 10 and 24 h. However, the Bayesian estimation of the effect of fasting time failed to confirm the results of the meta-regression; that is, the CI of the fasting time effect estimation included 0, implying that fasting time could not be considered significant (Table 4). Unexpectedly, the regression method showed that the effect of the halothane gene on pH45 was significantly influenced by sex (P = 0.0002), which explained almost 78% of the variability between the combined studies (Table 2).

Based on the effect sizes derived from studies examining the effect of the halothane gene on pHu (Table 1), differences between NN and nn (θ = 0.054; P < 0.05) and between NN and Nn (θ = 0.029; P < 0.05) were significant. However, pHu differences between Nn and nn were not significant (θ = 0.015; P > 0.05).

A fixed effects model was used to compare the effect size estimations of the comparisons NN vs. Nn and Nn vs. nn because the corresponding heterogeneity tests were not significant (Table 1). Posterior means, SD, and 95% CI for the overall and covariate effects for pHu and pH45 are listed in Table 4. The existing heterogeneity between effect size for the comparison between NN vs. nn was partially explained by the significant effect of slaughter weight, which explained 25% of the between-study variance of effect size between the NN and nn genotypes. Slaughter weight in the range of 85 to 125 kg had a significant negative effect on pHu differences between homozygous genotypes. Proportion of the total study variance attributable to the between-study variation. Pooled effect size was estimated using a fixed effects model when the Q 2 -test was not significant; conversely, the estimation was made using a random effects model when the Q 2 -test was significant. The significant covariate for pHu was the slaughter weight (P = 0.04), and the significant covariate for pH45 was the fasting time (P = 0.008).

As demonstrated in Figures 1 and2, the overall effect of fit of the model was satisfactory. For the pHu comparison NN vs. nn and the 3 halothane genotype comparisons for pH45, the posterior predictive distributions of the test statistics (overall effect and between-study variance) included the observed value of the statistic in areas of reasonable probability.

The results of the RE regression method showed a significant effect of the halothane gene on pHu (Table 2). The comparison of least squares mean differences between the 3 halothane genotypes showed that, as in the effect size method, differences between NN and nn and between NN and Nn were significant (P = 0.0011 and P = 0.011, respectively), whereas the difference between Nn and nn was not significant (P = 0.24; Table 3). None of the tested covariates was able to explain the increased heterogeneity between studies (Table 2).

Effect of the Halothane Gene on Color Coordinates: L*, a*, and b*

The heterogeneity tests of effect size estimations for the attributes L* and a* were not significant; therefore, the fixed effects model was retained (Table 1). The analysis of L* effect sizes showed that halothane genotype had a significant effect on the 3 halothane genotype comparisons: NN vs. Nn, NN vs. Nn, and Nn vs. nn. However, the analysis of a* effect sizes showed that only differences between the NN and nn genotypes were significant (Table 1). With regard to the b* attribute, comparisons between the 3 halothane genotypes were all significantly different from 0 (Table 1). The estimated effect sizes of the comparisons NN vs. Nn and Nn vs. nn were heterogeneous. The effect of halothane genotype on differences between Nn and nn was associated with a significant effect of breed, which explained approximately 80% of the between-study variance (Table 2). Heterogeneity between the NN and Nn genotypes was not influenced by any of the tested covariates. Posterior means and CI of the overall effect and different breed level effects are listed in Table 5. Predictive distributions of the posterior overall effect and between-study variance for the b* comparisons NN vs. Nn and Nn vs. nn are illustrated in Figure 3.

According to the results of the regression method, the halothane gene had a significant effect on L* and b*; however, its effect on a* was not significant. The increased heterogeneity between studies was explained mainly by breed (P = 0.0002, P < 0.0001, and P < 0.0001, respectively, for L*, a*, and b*; Table 2).

Effect of the Halothane Gene on DL

Significant differences in DL attributable to the halothane gene effect were found for NN vs. nn and for Nn vs. nn (Table 1 andFigure 4). Because the heterogeneity test was significant for the 3 halothane genotype comparisons, meta-regression was used to explain the between-study variance, in particular for the comparisons NN vs. nn and Nn vs. nn, where the overall effect was significant (θ = -1.67, P = 0.008, and θ = -1.303, P < 0.01, respectively). Breed explained 79 and 73% of the between-study variability for NN vs. nn and Nn vs. nn comparisons, respectively.

The Bayesian estimation of the overall effect for the comparison NN vs. Nn did not confirm the effect size method results (Table 5 and Figure 2). The CI did not cover 0, and the null hypothesis of a zero overall effect was therefore rejected.

Drip loss data included in the model of the RE regression method were not standardized because they are weighed by the inverse of their reciprocal variance in the SAS statement. As in the RE model estimation of the effect size method, the RE regression results showed that only the differences NN vs. nn and Nn vs. nn were significant (Table 3). The proportion of between-study variance in total variability was not large in the RE regression method (ρ < 50%), but the determination coefficient R 2 was very small. This apparent

Effect of the Halothane Gene on Lean%

Only a few studies provided data related to lean% of nn pigs. Therefore, the analysis of this attribute was made only between NN and Nn pigs. In this analysis, the results obtained from both meta-analysis methods were consistent (Tables 1 and3). As with DL, the effect size of lean% was estimated as a standardized mean difference. The heterogeneity test of effect size of the combined studies was not significant. The estimation of the overall effect following a fixed effect model showed that the halothane gene had a highly significant effect on differences between the NN and Nn genotypes (P < 0.001).

The combined data in the RE regression method were not standardized. Consequently, heterogeneity between studies was very high (ρ = 99%). None of the tested covariates was significant (Table 2). Comparison between the effect size estimation of lean% between the NN and Nn genotypes and the least squares mean difference between these 2 genotypes revealed similar values for both methods. Indeed, the effect size estimation was -0.975 (-1.248, -0.701) and the RE estimation of the least squares mean difference was -0.983 (-1.33, -0.628). Additionally, both of these values are well within the CI of each other.

DISCUSSION

In this study, 2 meta-analytic methods were used to quantify the effect of the halothane gene on a range of key attributes of pork quality in pig populations. The synthesis of published data in the form of a metaanalysis is increasingly common in the area of animal production. It has been shown to be a useful tool for obtaining precise predictions of the response of a given phenomenon to quantitative or qualitative variations [START_REF] Sauvant | Meta-analyses of experimental data in animal nutrition[END_REF].

Our selection of analyzed attributes was made after an extensive bibliographic research, which indicated that pH45, pHu, color variables (L*, a*, and b*), and DL are the main components or predictive traits for technological and sensory pork quality, and that carcass lean% is an important predictive trait for carcass quality [START_REF] Sellier | Genetics of meat and carcass traits[END_REF]. The data set used in the present study was prepared after a comprehensive search of the internationally published literature. Qualitative comparison of the literature indicated that the effect of the halothane gene on the main attributes of technological pig meat quality is controversial, especially where the 7 attributes listed above are concerned. In- deed, our meta-analysis for each attribute, except for pH45 and lean%, included the results of studies with diametrically opposed conclusions (i.e., that the halothane gene had a significant and a nonsignificant effect on the analyzed traits).

Because the effect of preslaughter conditions, and of their interactions with genotype and breed, on pork quality is already known [START_REF] Mormède | Differences in adaptive abilities of three breeds of Chinese pigs. Behavioural and neuroendocrine studies[END_REF][START_REF] Terlouw | Comparaison de la réactivité au stress des porcs de races Large White et Duroc. Conséquences sur des indicateurs de qualités des viandes[END_REF][START_REF] Hay | Urinary excretion of catecholamines, cortisol and their metabolites in Meishan and Large White sows: Validation as a non-invasive and integrative assessment of adreno-cortical and sympathoadrenal axis activity[END_REF][START_REF] Désautés | Behavior and pituitary-adrenal function in large white and Meishan pigs[END_REF], we limited our selection to studies with a similar experimental design. This helped us avoid any kind of bias in the combined results and, consequently, in the meta-analysis results. Nevertheless, characteristics that differed between studies and that could explain interstudy heterogeneity included breed, sex, slaughter weight, and fasting duration.

The synthesis of the results of the meta-analysis confirmed that the halothane gene had a significant effect on all the analyzed attributes except the color attribute a*. The results of the Egger test [START_REF] Egger | Bias in meta-analysis detected by a simple graphical test[END_REF] for publication bias showed a significant bias for the comparison NN vs. Nn for color coordinates and for the comparison Nn vs. nn for pH45. Given this publication bias, the results from our meta-analysis might slightly overestimate these effects.

The effect of the halothane gene on pHu has been the subject of debate. Several studies have shown this gene to have no significant effect on pHu changes in LM [START_REF] Guéblez | Effet du génotype halothane sur les performances d'engraissement, de carcasse et de qualité de la viande du porc charcutier[END_REF][START_REF] Larzul | Effet du génotype halothane sur la texture de la viande de porc[END_REF]. Other research has shown significant differences for pHu attributable to the halothane genotype [START_REF] Klont | Effect of dantrolene treatment on muscle metabolism and meat quality of anesthetized pigs of different halothane genotypes[END_REF][START_REF] Fisher | Halothane genotype and pork quality. 1. Carcass and meat quality characteristics of three halothane genotypes[END_REF]. According to the results of our meta-analysis, the 2-by-2 comparison of pHu differences between genotypes showed that only the difference between Nn and nn was not significant, and that the NN genotype had a greater pHu than the Nn and nn genotypes. Interestingly, results of the effect size method showed that the difference between NN and nn was affected by slaughter weight. The difference between the 2 genotypes tended to decrease with slaughter weight. This can be contrasted with the results of Sather et al. (1991a,b), who found that the effect of the halothane allele in the heterozygous state depended on slaughter weight, but also that the effect of the halothane allele appeared to be recessive in lightweight pigs and became dominant in heavyweight pigs. The apparent contradiction between our results and those of Sather et al. (1991a,b) may be due to breed differences between the sets of studies. However, this halothane genotype × slaughter weight interaction was not confirmed by [START_REF] Garcia-Macias | The effects of cross, slaughter weight and halothane genotype on leanness and meat and fat quality in pig carcasses[END_REF], [START_REF] Leach | The growth performance, carcass characteristics, and meat quality of halothane carrier and negative pigs[END_REF][START_REF] Larzul | Effect of halothane genotype (NN, Nn, nn) on growth, carcass and meat quality traits of pigs slaughtered at 95 kg or 125 kg live weight[END_REF].

Another unresolved issue in the literature concerned the value of heterozygous animals. In keeping with a systematic review based on 13 studies conducted by [START_REF] Sellier | Genetics of meat and carcass traits[END_REF], our results showed that the Nn animals were positioned between NN and nn animals for most meat quality traits, although the corresponding values were closer to those of NN than to those correspond-ing to nn for the attributes pH45, L*, and DL. Despite their proximity, differences between NN and Nn animals were significant for all the analyzed attributes except a*.

In this paper we have compared 2 meta-analytical approaches: the conventional RE regression method based on a frequentist approach [START_REF] St-Pierre | Invited Review: Integrating quantitative findings from multiple studies using mixed model methodology[END_REF][START_REF] Sauvant | Meta-analyses of experimental data in animal nutrition[END_REF] and the effect size method completed with a Bayesian approach when data were heterogeneous (Cusack et al., 1996;[START_REF] Wood | A meta-analytic assessment of a Thyroglobulin marker for marbling in beef cattle[END_REF]. Both methods are well established in animal production research, although the first is predominantly used in cases where the numbers of data are large, whereas the effect size method tends to be used when data are limited. The effect size method therefore appeared to be better suited for our meta-analysis (with a small number of combined studies and discrete variables). However, this method allows only pairwise comparison between the analyzed factors. Our use of Bayesian methods was facilitated by Markov chain Monte Carlo algorithms, which allowed for more flexibility in the formulation of prior information and models and for a wider range of inferences and comparisons through simulation. Whatever the method, the differences estimated between genotypes for L*, a*, and lean%, and also for some comparisons of pHu (comparisons NN vs. Nn and Nn vs. nn) and b* (comparison NN vs. nn), were very close. This consistency is explained by the data homogeneity for these comparisons proved by the [START_REF] Cochran | The combination of estimates from different experiments[END_REF] test of heterogeneity. In the RE regression method, heterogeneity that was due to between-study variance remained greater even after considering breed as a covariate in the models. It should be noted that the slight differences existing between the effect size estimations and the least squares mean differences between genotypes for the above-mentioned attributes were most likely because, in the effect size method, the estimation assumed a fixed effects model, whereas, in the RE regression method, estimations assumed a mixed model.

With pHu, the effect size method enabled us to reduce heterogeneity between studies. This reduction in heterogeneity was mainly due to the possibility, allowed by this method, of showing the significant effect of slaughter weight on pHu differences between the homozygous genotypes. By contrast, the RE regression method did not reveal any significant effect of the tested covariates, even though the heterogeneity between studies was very high.

With DL and lean%, the possibility of standardizing data when measurement methods were different was an advantage of the effect size method. The standardized effect size method allowed us to reduce the variability considerably between studies for DL, except for the comparison NN vs. Nn. Variability between studies for the DL comparisons NN vs. nn and Nn vs. nn was mainly explained by the significant effect of breed, which is known to be one of the most important factors influencing technological and sensory pig meat quality [START_REF] Bout | Lipides et qualités des tissues adipeux et musculaires de porc-Facteurs de variation. 2ème partie: Lipides et qualités du tissu musculaire-Facteurs de variation[END_REF][START_REF] Sellier | Genetics of pig meat quality[END_REF].

Discrepancies between methods were found for DL. The overall effect of the halothane gene on the DL difference between NN and Nn was not significant when considering the results from the effect size method as well as the RE regression method. Bayesian estimation of the overall effect between these 2 genotypes was significant, however. To explain this inconsistency, we should mention that in a classical, non-Bayesian approach to the effect size method using a fixed or RE model, the effect size θ and the variances σ e 2 and τ 2 are considered fixed variables and the between-study variance τ 2 is mostly estimated via an approximation proposed by [START_REF] Dersimonian | Meta-analysis in clinical trials[END_REF]. In a general hierarchical Bayesian scheme [START_REF] Dumouchel | Bayesian meta-analysis[END_REF], σ e 2 and τ 2 are assumed to be random variables. The distributions of these quantities are specified a priori. It is standard practice to assume a "flat" or "uninformative" prior for θ, as was done in the present study, because even with a small number of studies, the combined data become relatively informative regarding the location of the prior distribution of the effect size [START_REF] Carlin | Meta-analysis for 2 × 2 tables: A Bayesian approach[END_REF].

The imposition of distributions on θ, σ e 2 , and τ 2 allows a more explicit description of any underlying variability in the way the study outcomes are distributed. This in turn allows considerable flexibility in application. Moreover, it can be viewed as a Bayesian generalization of the RE model of effect size. The present study showed that there was a considerable indication of heterogeneity between studies and that moving to a Bayesian approach could provide more accurate estimates of effect size.

Meta-analysis was a useful tool with which to address existing controversies about the halothane gene effect generated by existing studies in a statistically robust way. Our study confirmed the significant effect of the halothane gene on all the analyzed attributes except a*. It also confirmed the intermediate position of Nn animals between NN and nn animals for most quality traits. By and large, the 2 methods investigated here yielded similar conclusions. However, discrepancies appeared when heterogeneity between studies was increased, which was the case with DL between the NN and Nn genotypes. In this case, the Bayesian approach, implemented in the effect size method, emerged as the most appropriate form of meta-analysis.

APPENDIX

  3 ph45 = pH at 45 min postmortem; pHu = ultimate pH; L* = reflectance; a* = redness; b* = yellowness; DL = drip loss.

  4

  at 45 min postmortem; pHu = ultimate pH; L* = reflectance; a* = redness; b* = yellowness; DL = drip loss; lean% = lean percentage.

Figure 1 .

 1 Figure 1. Posterior predictive distributions from the meta-analysis model for the overall effect and τ 2 (between-study variance) of pH at 45-min postmortem comparisons between the 3 halothane genotypes.

Figure 2 .

 2 Figure 2. Posterior predictive distributions from the meta-analysis model for the overall effect and τ 2 (between-study variance) of ultimate pH comparison between the NN and nn genotypes.

Figure 3 .

 3 Figure 3. Posterior predictive distributions from the meta-analysis model for the overall effect and τ 2 (between-study variance) of yellowness comparisons between the genotypes NN vs. Nn and Nn vs. nn.

Figure 4 .

 4 Figure 4. Posterior predictive distributions from the meta-analysis model for the overall effect and τ 2 (between-study variance) of drip loss comparisons between the 3 halothane genotypes.

Table A1 .

 A1 Summary of the 23 references used to construct the final

Table 1 .

 1 Summary of effect size, Q 2 -test, 1 and I 2 -statistic 2 for the halothane genotype comparisons

							Heterogeneity
	Outcome 3	θ i	4 (95% CI)	P-value	Q 2 -test	df	P-value	I 2
	NN vs. nn
	pH45	0.536 (0.377, 0.695)	<0.001	135.59	10	<0.0001	92.62
	pHu	0.054 (0.007, 0.100)	<0.05	34.31	10	<0.001	70.84
	L*	-3.386 (-3.996, -2.776)	<0.0001	15.29	12	>0.05	21.51
	a*	-0.318 (-0.547, -0.089)	<0.05	20.8	12	>0.05	42.55
	b*	-0.965 (-1.162, -0.768)	<0.001	20.41	12	>0.05	41.22
	DL	-1.668 (-2.711, -0.626)	<0.01	43.05	12	<0.001	72.12
	NN vs. Nn
	pH45	0.188 (0.139, 0.238)	<0.001	25.07	10	<0.01	60.10
	pHu	0.029 (0.0001, 0.058)	<0.05	19.46	10	>0.05	48.61
	L*	-0.732 (-1.259, -0.204)	<0.05	15.16	12	>0.05	20.87
	a*	-0.136 (-0.336, 0.063)	>0.05	16.76	12	>0.05	28.39
	b*	-0.467 (-0.754, -0.179)	<0.001	35.69	12	<0.001	66.38
	DL	-0.389 (-1.279, 0.500)	>0.1	45.35	12	<0.001	73.54
	Lean%	-0.975 (-1.248, -0.701)	<0.001	14.21	10	>0.05	29.63
	Nn vs. Nn
	pH45	0.333 (0.221, 0.446)	<0.001	90.71	10	<0.001	88.97
	pHu	0.015 (-0.003, 0.034)	>0.05	11.85	10	>0.05	15.68
	L*	-2.497 (-3.092, -1.902)	<0.0001	20.4	12	>0.05	43.94
	a*	-0.088 (-0.318, 0.140)	>0.05	18.19	12	>0.05	34.03
	b*	-0.405 (-0.765, -0.045)	<0.001	45.49	12	<0.001	72.41
	DL	-1.303 (-2.162, -0,444)	<0.01	33.01	12	<0.001	63.70

1

Chi-square test of heterogeneity. 2

Table 2 .

 2 Least squares means ± SE of the analyzed meat quality traits according to halothane genotype estimated using the random effects regression model, and P-values of the tested covariates for meta-regression

			Halothane genotype				P-value
	Outcome 1	NN	Nn	nn	P-value	Breed	Sex	Slaughter wt
	pH45	6.40 ± 0.06	6.24 ± 0.06	5.92 ± 0.07	0.0001	0.060	0.0002	0.520
	pHu	5.63 ± 0.05	5.59 ± 0.05	5.57 ± 0.05	0.0036	0.538	0.529	0.583
	L*	50.08 ± 0.72	50.69 ± 0.70	53.39 ± 0.71	0.00008	0.0002	0.300	0.990
	a*	7.50 ± 0.26	7.67 ± 0.25	7.93 ± 0.26	0.1672	0.0001	0.080	0.209
	b*	10.99 ± 0.4	11.42 ± 0.4	12.11 ± 0.4	0.0001	0.0001	0.310	0.510
	DL	3.77 ± 0.34	4.12 ± 0.36	5.16 ± 0.42	0.0146	0.172	0.807	0.382
	Lean%	57.8 ± 1.12	58.78 ± 1.12	-2	0.0004	0.07	0.059	0.040
	1 ph45 = pH at 45 min postmortem; pHu = ultimate pH; L* = reflectance; a* = redness; b* = yellowness; DL = drip loss; lean% = lean per-
	centage.

2

Comparison was not made.

Table 3 .

 3 Difference (least squares mean ± SE) of the analyzed meat quality traits according to halothane genotype estimated using the random effects regression model

	Outcome 1 and
	genotypes compared	Difference	P-value	R 2 , %	I 2 , %
	pH45			86.48	49.1
	NN vs. nn	0.481 ± 0.0642	<0.0001
	NN vs. Nn	0.162 ± 0.048	<0.01
	Nn vs. nn	0.319 ± 0.063	<0.0001
	pHu			93.12	95.4
	NN vs. nn	0.061 ± 0.016	0.0011
	NN vs. Nn	0.043 ± 0.015	<0.05
	Nn vs. nn	0.017 ± 0.015	>0.1
	L*			96.91	84.34
	NN vs. nn	-3.315 ± 0.473	<0.0001
	NN vs. Nn	-0.607 ± 0.469	>0.1
	Nn vs. nn	-2.707 ± 0.468	<0.0001
	a*			97.71	78.58
	NN vs. nn	-0.432 ± 0.220	>0.05
	NN vs. Nn	-0.170 ± 0.219	>0.1
	Nn vs. nn	-0.262 ± 0.221	>0.1
	b*			99.73	95.93
	NN vs. nn	-1.120 ± 0.170	<0.0001
	NN vs. Nn	-0.430 ± 0.150	<0.01
	Nn vs. nn	-0.680 ± 0.170	<0.001
	DL			49.36	41.32
	NN vs. nn	-1.388 ± 0.439	0.0042
	NN vs. Nn	-0.345 ± 0.373	>0.1
	nNn vs. nn	-1.043 ± 0.447	<0.05
	Lean%			97.92	98.53
	NN vs. Nn	-0.981 ± 0.180	<0.001

Table 4 .

 4 Summary of posterior distribution of pooled effect size and effects of significant covariates for pHu and pH45 obtained from Bayesian meta-regression

	Outcome 1 and	Intercept	Covariate 3 coefficient	Between-study	Intrastudy
	genotypes compared	(95% CI 2 )	(95% CI)	variance	variance	I 2 , %
	pH45
	NN vs. nn	0.536 (0.358, 0.717)		0.0817	0.0041	95.15
	NN vs. Nn	0.189 (0.133, 0.247)		0.0054	0.0020	73.02
	Nn vs. nn	0.341 (0.216, 0.472) -0.064 (-0.186, 0.067)	0.0341	0.0044	88.49
	pHu
	NN vs. nn	0.061 (0.016, 0.104) -0.054 (-0.101, -0.006)	0.0033	0.0012	72.37

1 ph45 = pH at 45 min postmortem; pHu = ultimate pH. 2 CI = confidence interval.

3

Table 5 .

 5 Summary of posterior distribution of pooled effect size obtained from Bayesian meta-regression by considering of breed as a covariate for b* and DL

	Outcome 1 and	Intercept	Between-study	Intrastudy
	genotypes compared	(95% CI 2 )	variance	variance	I 2 , %
	b*
	NN vs. Nn	-0.461 (-0.778, -0.165)	0.184	0.093	0.664
	Nn vs. nn	-0.622 (-0.894, -0.349)	0.057	0.131	0.303
	DL
	NN vs. nn	-0.608 (-0.887, -0.331)	0.078	0.109	0.417
	NN vs. Nn	-0.184 (-0.653, -0.264)	0.529	0.102	0.838
	Nn vs. nn	-0.485 (-0.744, -0.226)	0.060	0.112	0.349

1 b* = yellowness; DL = drip loss. 2 CI = confidence interval.

Table A1 (

 A1 Continued). Summary of the 23 references used to construct the final database

at INRA Institut National de la Recherche Agronomique on August 29, 2013 www.journalofanimalscience.org Downloaded from

The authors gratefully acknowledge financial assistance provided by the European Community under the Sixth Framework Programme for Research, Technological Development and Demonstration Activities (Brussels, Belgium), for the Integrated Project Q-PORKCHAINS FOOD-CT-2007-036245. The views expressed in this publication are the sole responsibility of the author(s) and do not necessarily reflect the views of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for any use that might be made of the

information. 2 Corresponding author: btissam.salmi@jouy.inra.fr Received September 21, 2009. Accepted March 11, 2010.

Meta-analysis of the halothane gene at INRA Institut National de la Recherche Agronomique on August 29, 2013 www.journalofanimalscience.org Downloaded from

This article has been cited by 3 HighWire-hosted articles: at INRA Institut National de la Recherche Agronomique on August 29, 2013 www.journalofanimalscience.org Downloaded from