Marc Benoît

Davide Rizzo

Elisa Marraccini

Anna Camilla Moonen

Mariassunta Galli

Sylvie Lardon

Hélène Rapey

Claudine Thenail

Enrico Bonari

/ D Rizzo

/ M Galli

/ E Bonari

a new field for addressing agricultural landscape dynamics *

Keywords: Conceptual model, Natural resources, Farming practices, Landscape patterns, Landscape

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

This manuscript is a collaborative work that arose from a debate on the role of agronomic concepts and approaches in landscape research. Two challenges underpin this debate. First, landscape research is called on to provide decisionmakers with relevant knowledge on agricultural landscape dynamics, in order to foster a more integrative support for multifunctional landscape design (Council of Europe 2000; [START_REF] Nassauer | Design in science: extending the landscape ecology paradigm[END_REF][START_REF] Conrad | Is research keeping up with changes in landscape policy? A review of the literature[END_REF]. Second, agronomists increasingly have to deal with the positive and negative impacts of the farming systems on these landscape dynamics [START_REF] Thenail | Farm riparian land use management: driving factors and tensions between technical and ecological functions[END_REF][START_REF] Groot | Designing a hedgerow network in a multifunctional agricultural landscape: Balancing trade-offs among ecological quality, landscape character and implementation costs[END_REF][START_REF] Pelosi | The spatial scale mismatch between ecological processes and agricultural management: Do difficulties come from underlying theoretical frameworks? Agriculture[END_REF]Wästfelt et al. 2012). It follows that agronomy needs to join forces with landscape research.

In this perspective paper we discuss how a part of agronomy is widening its focus addressing the landscape dynamics and how this new field contributes to deal with research issues on agricultural landscapes. We consider the landscape as the system where farmers interact with both natural and social resources through the management of their fields and of the associated features such as field margins and semi-natural habitat patches. Landscape research, especially from a landscape ecology perspective, appears to be focused on the characterization and understanding of landscape patterns and related ecological processes (e.g., [START_REF] Farina | Principles and methods in landscape ecology: toward a science of landscape[END_REF]). In the following paragraphs, we argue why and how agronomy can contribute to landscape research with a conceptual model suggesting a new perspective on farming practices as a crucial driver in the pattern-process relationships.

autor-created version on final draft

Why should agronomy contribute to landscape research?

Farming accounts for the majority of human land use: pastures and crops took up 25.8% and 11.8%, respectively, of the earth's land in 2009 (FAOSTAT 2009). It results that more than one third of the land on the planet is managed as farmland.

Agronomy is the main discipline committed to the study of farming. Accordingly, this discipline is challenged to widen its conventional focus on farming practices so as to facilitate agriculture, not only for increasing production, but also to meet new social demands on farmland management (e.g., the protection of the environment and the upholding of cultural features).

Farming practices are performed on and interact with natural resources -mainly soil, water, and biodiversity -either at the field level (van Ittersum and Rabbinge 1997) or at wider scales [START_REF] Veldkamp | Multi-scale system approaches in agronomic research at the landscape level[END_REF][START_REF] Dalgaard | Agroecology, scaling and interdisciplinarity[END_REF]. Great advances in production techniques and the increasing availability of external inputs have replaced the main services that the local agroecosystems used to provide (e.g., soil fertility, water availability and pest control). However, these advances, fostered by a strong emphasis of agronomy on field performances, have resulted in a loss of interest in and knowledge on the interactions between farming practices and the surrounding natural system. In addition, some authors have highlighted that the mainstream agronomic literature have scarcely considered the role of the spatial configuration of the fields in farming [START_REF] Cavazza | Agronomia aziendale e agronomia del territorio[END_REF][START_REF] Veldkamp | Multi-scale system approaches in agronomic research at the landscape level[END_REF][START_REF] Hatfield | Beyond the Edge of the Field[END_REF][START_REF] Osty | Raisonnement à partir de cas et agronomie des territoires[END_REF]). Accordingly, agronomy has been urged for a greater consideration of a spatially explicit approach (White et al. 2002), especially so as to shift analysis from the field/farm scale toward wider levels [START_REF] Leenhardt | Describing and locating cropping systems on a regional scale. A review[END_REF][START_REF] Nesme | Is the plot concept an obstacle in agricultural sciences? A review focussing on fruit production[END_REF]. In brief, modern cropping system design has largely excluded autor-created version on final draft the local context, eventually triggering severe environmental problems. This prompted society to request the following from agriculture and agronomy: first for a reduction of the impact on natural resources (e.g., [START_REF] Sheail | Nature protection, ecologists and the farming context: A U.K. historical context[END_REF][START_REF] Henle | Identifying and managing the conflicts between agriculture and biodiversity conservation in Europe-A review[END_REF], and second for agro-environmental services to be provided (e.g., [START_REF] Viglizzo | Scale-dependent controls on ecological functions in agroecosystems of Argentina[END_REF][START_REF] Bastian | Determining environmental minimum requirements for functions provided by agro-ecosystems[END_REF][START_REF] Brown | Agricultural landscape change (1937-2002) in three townships in Iowa, USA[END_REF]. Recent agronomic approaches, while still seeking to improve crop and forage productions, are redesigning farming practices and trying to foster indeed the sustainable management of natural resources [START_REF] Martin | Systèmes de culture et territoires: cas des questions environnementales[END_REF][START_REF] Acevedo | Interdisciplinary progress in food production, food security and environment research[END_REF]. Nevertheless, to date, few agronomic studies have acknowledged the agricultural landscape as a complex socioenvironmental context that may influence field management [START_REF] Deffontaines | Agricultural systems and landscape patterns: how can we build a relationship?[END_REF][START_REF] Van Mansvelt | An interdisciplinary approach to integrate a range of agro-landscape values as proposed by representatives of various disciplines[END_REF][START_REF] Groot | Designing a hedgerow network in a multifunctional agricultural landscape: Balancing trade-offs among ecological quality, landscape character and implementation costs[END_REF][START_REF] Pelosi | The spatial scale mismatch between ecological processes and agricultural management: Do difficulties come from underlying theoretical frameworks? Agriculture[END_REF][START_REF] Valbuena | Effects of farmers' decisions on the landscape structure of a Dutch rural region: An agent-based approach[END_REF].

Broadly speaking, agronomy is a discipline aimed at delivering operative knowledge to the ultimate landscape managers: the farmers and their organizations [START_REF] Deffontaines | Agricultural systems and landscape patterns: how can we build a relationship?[END_REF][START_REF] Cavazza | Agronomia aziendale e agronomia del territorio[END_REF][START_REF] Benoît | Landscape designed by farming systems: a challenge for landscape agronomists in Europe[END_REF]. Therefore, to enhance landscape research concerning the design and management of sustainable agricultural landscapes, we argue the need for an effective interdisciplinary approach that includes agronomic knowledge and tools. Operatively, this discipline will play a key role in integrating farming practices in the characterization of past landscape dynamics, in the assessment of contemporary landscape patterns, and in the design of future agricultural landscape scenarios. If agronomy fails to contribute its knowledge to agricultural landscape research, there is a real risk of misunderstanding and underestimating the role of farming in these landscape dynamics, which could lead to ineffective management decisions regarding these landscapes.

autor-created version on final draft

The field of agronomy that can make innovative contributions to the analysis of agricultural landscape dynamics is referred to as "landscape agronomy". Landscape agronomy is the emerging perspective of agronomy focusing on the relations among farming practices, natural resources and landscape patterns, which are involved in the dynamics of agricultural landscapes. This new interest of agronomy for landscape issues and the new synergies that can emerge by collaboration with other disciplines involved in landscape research are the only way to develop sustainable agricultural landscapes for the future.

What is our conceptual model?

To explain the heart of landscape agronomy, we propose a conceptual model of the Agricultural Landscape Dynamics: ALaDyn (Fig. 1). This model will support us in discussing, in the next paragraph, how landscape agronomy deals with the characterization, assessment, and modeling of the relationships between farming systems and agricultural landscape dynamics.

We have elaborated this model from certain applications of landscape agronomy in research and education that have been discussed in earlier works [START_REF] Benoît | Landscape designed by farming systems: a challenge for landscape agronomists in Europe[END_REF][START_REF] Rapey | Experiences from a winter school on landscape agronomy: stakes, difficulties, perspectives[END_REF][START_REF] Rizzo | Terraced landscapes characterization. Developing a methodology to map and analyze the agricultural management impacts (Monte Pisano, Italy)[END_REF][START_REF] Lazrak | Landscape regularity modelling for environmental challenges in agriculture[END_REF][START_REF] Moonen | A winter school in landscape agronomy and the synergies it created[END_REF][START_REF] Marraccini | Contribution of agronomy to land management issues -A Comparison of five interdisciplinary PhD theses[END_REF]. From these exploratory landscape agronomy experiences, we have found that there are three key elements that cannot be disentangled in the analysis of agricultural landscape dynamics: farming practices, natural resources, and landscape patterns. (ii) the response of landscape to the farming practices, observed either as direct impacts on it or as disturb to the dynamics of natural resources, as well as incidental or fostered effects of the management. Hence, in the model we insist on the feedback loops between people and land for understanding landscape dynamics, in agreement with the call made by [START_REF] Verburg | Simulating feedbacks in land use and land cover change models[END_REF].

The majority of landscape research mainly focuses on one or two of the poles, namely natural resources and landscape patterns. The model indicates instead that a full explanation of agricultural landscape dynamics must consider all three poles and therefore that farming practices need to be included if we want explain landscape dynamics appropriately. For example, we stress the need to consider the state of the natural resources and processes together with the spatial pattern in which they are distributed to understand or to improve the way farmers decide upon their farming practices (e.g., [START_REF] Acevedo | Interdisciplinary progress in food production, food security and environment research[END_REF]. Similarly, we consider that the analysis of the state of natural resources needs to account for how they are affected by the farming practices according to the local landscape patterns (e.g., [START_REF] Moonen | Functional biodiversity: An agroecosystem approach[END_REF].

Finally, to be able to explain or to design agricultural landscape patterns, we need to know how they were affected by the interactions between farming practices and natural resources (e.g., [START_REF] Groot | Designing a hedgerow network in a multifunctional agricultural landscape: Balancing trade-offs among ecological quality, landscape character and implementation costs[END_REF].

Therefore, ALaDyn introduces farming practices as the main levers with which to steer landscape dynamics. Farming practices are so pointed out as crucial activities in the management of spatial patterns and environmental processes occurring in agricultural landscapes, although they are rarely analyzed by the other disciplines involved in landscape research, particularly landscape ecology.

autor-created version on final draft

# Figure 1 approximately here # On the one hand farming practices are the activities chosen and performed by farmers, mainly to improve the suitability of land for crops and livestock production.

On the other hand farming practices are the elementary operations that affect the greatest part of the agricultural landscape dynamics through the choice and the allocation of the cropping systems. [START_REF] Sebillotte | Agronomie et agriculture. Essai d'analyse des tâches de l'agronome[END_REF] identified three choices of farmers that define the cropping systems over seasons and years: (i) the land cover, namely, the type of annual and multiannual crops or the type of grasslands; (ii) the temporal sequence of the different land covers and their allocation on the ensemble of farm land units (i.e., the fields, sometimes managed as a cluster), ordinarily over a given time-span; (iii) the crop management defined by the array of technical operations for each land cover, such as the type and timing of tillage, the quantity and type of fertilization, the time and density of sowing and so forth.

Although farming practices are chiefly performed in fields, they affect landscape dynamics through several trade-offs. Firstly, changes in farming practices shape various spatial and environmental characteristics of the landscape. It follows that farming practices can be oriented to design [sensu [START_REF] Nassauer | Design in science: extending the landscape ecology paradigm[END_REF]; see also [START_REF] Gobster | The shared landscape: what does aesthetics have to do with ecology?[END_REF]] new agricultural landscapes and intentionally-created landscape patterns. Moreover, natural resources can be actively managed through farming and are not only passively affected [START_REF] Pelosi | The spatial scale mismatch between ecological processes and agricultural management: Do difficulties come from underlying theoretical frameworks? Agriculture[END_REF]. Secondly, farming practices are responsible for the upholding of characteristic landscape features like hedges, terraces, channels, and roads (e.g., [START_REF] Thenail | Variation of farm spatial land use pattern according to the structure of the hedgerow network (bocage) landscape: a study case in northeast Brittany, France[END_REF][START_REF] Daugstad | Agriculture as an upholder of cultural heritage? Conceptualizations and value judgements -A Norwegian perspective in international context[END_REF][START_REF] Rizzo | Terraced landscapes characterization. Developing a methodology to map and analyze the agricultural management impacts (Monte Pisano, Italy)[END_REF][START_REF] Primdahl | The farmer as a landscape manager: Management roles and change patterns in a Danish region[END_REF] as well as of the overall autor-created version on final draft landscape care (Wästfelt et al. 2012). Therefore, ALaDyn lies at the crossroads between farming management and landscape design (Fig. 1).

From this brief presentation of ALaDyn becomes clear the two main contributions of landscape agronomy to research on agricultural landscape dynamics. On the one hand, this model clarifies that landscape agronomy explains landscape patterns in agricultural landscape as a configuration of fields designed by farming practices interacting with natural resources. On the other hand, it points out that landscape agronomy also considers the landscape patterns and the natural resources as drivers for farming practices. This cross-regard on landscape patterns makes a difference between landscape ecology and landscape agronomy. Landscape ecology mainly characterizes landscape patterns as observed research object to explain associated ecological processes and functions [START_REF] Forman | Land mosaics: the ecology of landscapes and regions[END_REF][START_REF] Farina | Principles and methods in landscape ecology: toward a science of landscape[END_REF]

How can landscape agronomy contribute to agricultural landscape research?

In this section, we apply ALaDyn to analyze the specific contribution of landscape agronomy to crucial issues in agricultural landscape research. The first issue is to enhance the characterization of the relationship between current landscapes patterns and farming practices (4.1); the second issue is to clarify the role of farming practices in assessing landscape patterns (4.2); and the third issue is to improve the design of future agricultural landscapes (4.3).

autor-created version on final draft

Characterizing landscape patterns as a result of farming practices

The structure of an agricultural landscape and its ecosystem services is largely defined by the agricultural practices that have been performed and that are constantly renewed by farmers. Farming practices can be viewed as determinants of the landscape patterns, and their potential impact on natural resources and cultural features has been evaluated [START_REF] Egoz | Tastes in tension: form, function, and meaning in New Zealand's farmed landscapes[END_REF][START_REF] Mignolet | Modélisation de l'organisation spatiale des systèmes agricoles et de son évolution dans des démarches d'appui au développement[END_REF][START_REF] Rizzo | Terraced landscapes characterization. Developing a methodology to map and analyze the agricultural management impacts (Monte Pisano, Italy)[END_REF]Galli et al. 2010;[START_REF] Jacopin | Paysages et pratiques des agriculteurs dans le Sud du Plateau Lorrain: logiques d'organisation et effets sur l'environnement[END_REF]). Farming practices have also been identified as the crucial pivot between the local landscape identity and global agro-industrial trajectories (e.g., [START_REF] Jarosz | The geography of Washington's world apple: global expressions in a local landscape[END_REF]Jackson 2008). These two examples highlight the different ways in which patterns and resources in agricultural landscapes are affected by past and current farming practices. Accordingly, we deem that the systematic inclusion of the study of farming practices into landscape research would help to increase our knowledge of the relationships between landscape patterns and agro-ecosystem services, such as the preservation of functional biodiversity [START_REF] Moonen | Functional biodiversity: An agroecosystem approach[END_REF] or the improvement of spatial heterogeneity [START_REF] Brandt | Landscape practise and key concepts for landscape sustainability[END_REF], and would allow us to steer these services in future landscapes. Recent research on farming practices has highlighted the need to collect a large amount of data in order to characterize the real practices and choices of farmers over long time-spans (to overcome seasonal variability) and wide regions (to skip local specificities) (e.g., [START_REF] Mignolet | Modélisation de l'organisation spatiale des systèmes agricoles et de son évolution dans des démarches d'appui au développement[END_REF][START_REF] Leenhardt | Describing and locating cropping systems on a regional scale. A review[END_REF]. Landscape agronomy, by considering the relationships between landscape patterns, farming practices, and natural resources (see the ALaDyn model in Fig. 1), can help to enhance the relevance of these timeconsuming surveys for interdisciplinary landscape research.

autor-created version on final draft

Understanding farming practices to assess current landscape patterns

Landscape dynamics occurring in today's agricultural landscapes are mainly managed at the field level. Classic agronomy has focused on the field as the space where farming practices are performed, thus identifying it as an interface with ecology and other disciplines [START_REF] Deffontaines | L'agronomie, science du champ. Le champ[END_REF]Le Ber and Benoît 1998;[START_REF] Thenail | The contribution of crop-rotation organization in farms to crop-mosaic patterning at local landscape scales[END_REF][START_REF] Pelosi | The spatial scale mismatch between ecological processes and agricultural management: Do difficulties come from underlying theoretical frameworks? Agriculture[END_REF]. Indeed, the field defined by agronomists seems to give an operational translation to the "landscape unit," which [START_REF] Moss | Interdisciplinarity, landscape ecology and the 'Transformation of Agricultural Landscapes[END_REF] identified as the critical element with which socioeconomic and cultural factors interact across heterogeneous agricultural landscapes.

To improve on the classic agronomic approach, landscape agronomy moves the focus from the field to the spatial configuration of fields as the crucial concept for assessing and managing the three poles of agricultural landscape dynamics (Fig. 1) and thereby meeting new societal demands [START_REF] Benoît | Landscape designed by farming systems: a challenge for landscape agronomists in Europe[END_REF]). The spatial configuration includes both the topological characteristics of an "ensemble" [sensu [START_REF] Antrop | The concept of traditional landscapes as a base for landscape evaluation and planning. The example of Flanders Region[END_REF] of fields (e.g., their shape, size, and location) and their spatial and functional relationship with other landscape features (e.g., irrigation and drainage channels, hedgerows, and field margins). These configurations are further influenced by natural resources and local topographical conditions. For instance, water accessibility or proximity to the farmstead could constrain or enhance farming practices, thus shaping field configurations accordingly [START_REF] Morlon | Étude méthodologique d'un parcellaire d'exploitation agricole en tant que système[END_REF][START_REF] Thenail | Variation of farm spatial land use pattern according to the structure of the hedgerow network (bocage) landscape: a study case in northeast Brittany, France[END_REF][START_REF] Thenail | The contribution of crop-rotation organization in farms to crop-mosaic patterning at local landscape scales[END_REF].

The issue at stake is to select the criteria to aggregate fields into landscape patterns when fostering a salient assessment and an improved management of landscape dynamics. A first criterion could be to focus on the environmental autor-created version on final draft resources, such as water, thus characterizing the spatial configuration of farmed fields at the watershed level [START_REF] Vogt | Linking ecological and social scales for natural resource management[END_REF][START_REF] Mignolet | Spatial dynamics of agricultural practices on a basin territory: a retrospective study to implement models simulating nitrate flow. The case of the Seine basin[END_REF]. Another criterion could be the field aggregation designed by a legal framework, such as in the case of regulations for traditional or quality food with a Protected Geographical Status (Vollet et al. 2008). Another criterion could be plot aggregation as a function of recurring crop rotations [START_REF] Thenail | The contribution of crop-rotation organization in farms to crop-mosaic patterning at local landscape scales[END_REF][START_REF] Lazrak | Landscape regularity modelling for environmental challenges in agriculture[END_REF]. The relevance of crop rotations is still poorly considered [START_REF] Leenhardt | Describing and locating cropping systems on a regional scale. A review[END_REF], even though highly consistent with the assessment of farming practices over wide regions. In general, the main advantage of these criteria should be to overcome the vagueness in the definition of single field limits, which change according to seasonally evolving practices [START_REF] Morlon | La dimension spatiale des pratiques agricoles: une approche agronomique[END_REF] and may differ according to the approach used for their definition [START_REF] Nesme | Is the plot concept an obstacle in agricultural sciences? A review focussing on fruit production[END_REF]). In addition the aggregation of fields according to different criteria would tackle the call for an interdisciplinary and multi-scalar approach in agronomy made so far by some authors [START_REF] Moss | Interdisciplinarity, landscape ecology and the 'Transformation of Agricultural Landscapes[END_REF][START_REF] Dalgaard | Agroecology, scaling and interdisciplinarity[END_REF][START_REF] Acevedo | Interdisciplinary progress in food production, food security and environment research[END_REF].

By introducing farming practices as a crucial element for understanding the spatial configuration of landscapes, landscape agronomy complements the knowledge of landscape patterns provided by landscape ecology. In particular, landscape agronomy can help explain patterns as "regularities" shaped by farming practices (e.g., Lazrak 2012). In other words, it is the farmers' decision making when choosing their farming practices that determines the spatial configuration of fields [perceived and measured as landscape patterns]. Shaller et al. (2012) have demonstrated that today's landscape spatial organization can be explained by coupling decision-making process modeling ("rules") and stochastic modeling ("regularities"). In this way, they have shown how the emerging landscape agronomy approach can make original autor-created version on final draft contributions to the interpretation and explanation of agricultural landscape dynamics relating farming practices and landscape patterns.

Improving tools to design future agricultural landscapes

The main contribution of landscape agronomy to improve the design of future landscapes is to integrate appropriate descriptors of the farming practices and their evolutions in the assessment and scenarios of landscape dynamics, so as to meet the increasing societal demands for multifunctional landscapes [START_REF] Beuret | À qui appartient le paysage? (To whom does the landscape belong?)[END_REF][START_REF] Gobster | The shared landscape: what does aesthetics have to do with ecology?[END_REF][START_REF] Gaucherel | Combining process-based models for future biomass assessment at landscape scale[END_REF][START_REF] Pinto-Correia | New roles for farming in a differentiated countryside: the Portuguese example[END_REF][START_REF] Groot | Designing a hedgerow network in a multifunctional agricultural landscape: Balancing trade-offs among ecological quality, landscape character and implementation costs[END_REF][START_REF] Domon | Landscape as resource: Consequences, challenges and opportunities for rural development[END_REF][START_REF] Brandt | Landscape practise and key concepts for landscape sustainability[END_REF].

More generally, landscape agronomy will contribute to landscape research also by integrating the goals of agricultural production into the multiple objectives of the landscape design and management. Such a goal has been identified as a priority for the agricultural policy agenda itself [START_REF] Beddington | What Next for Agriculture After Durban?[END_REF]Wästfelt et al. 2012). For this, landscape agronomy may for instance assess and operationalize future landscape designs on the knowledge about farmers' entrepreneurial goals, in a way they could more easily master and discuss the proposed scenarios with the other local actors.

Recent advances in agronomy have largely taken advantage of the availability of spatial data and improved measurements of crops performances to address spatially attuned practices (such as the precision agriculture approach) at the field/farm level (e.g., [START_REF] Schellberg | Precision agriculture on grassland: Applications, perspectives and constraints[END_REF][START_REF] Oliver | Integrating farmer knowledge, precision agriculture tools, and crop simulation modelling to evaluate management options for poor-performing patches in cropping fields[END_REF][START_REF] Lamanda | A protocol for the conceptualisation of an agro-ecosystem to guide data acquisition and analysis and expert knowledge integration[END_REF]. By mean of ALaDyn (fig. 1) we spur research on agriculture (uppermost the studies focusing on farming practices) to develop tools to stress and integrate the diversity of placebased and contextual challenges/opportunities over larger scales. For example, landscape agronomic methods should address the (re)design of farming systems autor-created version on final draft assessing crop rotations and crop management for the impacts on natural resources given the specific landscape patterns into which they will be proposed. In this regard, few researchers (e.g., [START_REF] Grilli | An area-wide model approach for the management of a disease vector planthopper in an extensive agricultural system[END_REF][START_REF] Groot | Designing a hedgerow network in a multifunctional agricultural landscape: Balancing trade-offs among ecological quality, landscape character and implementation costs[END_REF][START_REF] Lovell | Integrating agroecology and landscape multifunctionality in Vermont: An evolving framework to evaluate the design of agroecosystems[END_REF] have tested an iterative "sketch design" process of agricultural landscape management from the field or feature level to wider field configurations and regional level that means closer to scales at which landscape patterns are designed.

Future agricultural landscape dynamics will likely be driven by conflicts in land use (e.g., energy versus food production) and constrained by the availability of resources (e.g., water shortage due to climate change) (see [START_REF] Acevedo | Interdisciplinary progress in food production, food security and environment research[END_REF]. Accordingly, the relationships between farming practices, natural resources and landscape patterns will be further stressed and even exacerbated on a place-based perspective.

Therefore, the role of agronomists could become crucial to properly elicit and assess the spatial diversity and impacts of farming practices on the overall management of agricultural landscapes.

Conclusions and perspectives

The relationships between farming practices and landscape dynamics are still poorly explored despite the conflicting expectations on land use stressed by land change science [START_REF] Rindfuss | Developing a science of land change: Challenges and methodological issues[END_REF][START_REF] Turner | The emergence of land change science for global environmental change and sustainability[END_REF][START_REF] Rounsevell | Challenges for land system science[END_REF]) and concerns over the loss of agricultural land [START_REF] Dramstad | Landscapes: Bridging the gaps between science, policy and people[END_REF]. In this context, the underpinning idea of landscape agronomy is that research on agricultural landscape should integrate both the influence of the landscape on farming practices, only partly explored by some authors (e.g., [START_REF] Primdahl | Agricultural landscapes as places of production and for living in owner's versus producer's decision making and the implications for planning[END_REF][START_REF] Busck | Farmers' landscape decisions: relationships between farmers' values and landscape practices[END_REF][START_REF] Claessens | Modelling interactions and feedback mechanisms between land use change and landscape processes[END_REF], and the role of the farmer as actor shaping patterns and processes observed from a landscape ecology perspective (e.g., [START_REF] Baudry | Temporal variability of connectivity in agricultural landscapes: do farming activities help?[END_REF][START_REF] Burel | Habitat quality and connectivity in agricultural landscapes: the role of land use systems at various scales in time[END_REF] autor-created version on final draft Baudry 2005). From this viewpoint, we see landscape agronomy as fertile ground for the interaction between agronomy and landscape ecology seeking an agreement on shared concepts (Fig. 1), as well as with the wide range of disciplines classically involved in landscape research such as geography, ecology, planning, and architecture. Landscape agronomy is intended to include issues raised, for instance, in policies, by extensionists and so forth, about the roles of farmers in the management of the landscape. This management concerns the natural resources and the services expected by societies at the landscape level, such as attractiveness for leisure, preservation of cultural features, tourism, etc.

Our knowledge and experience as agronomists allowed us to define a conceptual model of agricultural landscape dynamics (Fig. 1) whose main novelty is the integration of farming practices as a core item with which to understand and consequently steer landscape dynamics. We acknowledge to ALaDyn three roles. In conclusion, landscape agronomy is for us closely related to the research on agricultural landscape dynamics because its principal aim is to deal with the reciprocal influence between the landscape dynamics and the farmers. In addressing this influence we draw attention to some critical questions. How do farmers affect the landscape through their practices? What are the levers of action to support or autor-created version on final draft reorient these practices? Are the policies appropriate? How are farmer practices influenced by landscape features? Are the proposals for new multifunctional landscapes sustainable to combine practices for landscape management and practices for production management? Hence, who is working on this?

We hope to initiate a constructive dialogue between agronomists and other 5 landscape scientists in order to strengthen the agronomic contribution to landscape research and to formulate a shared understanding of the role of agronomy in research on landscape dynamics.

autor-created version on final draft

  These core items constitute the poles of the model. The relationships between the three poles are the major novelty of this model and show at the same time the importance of the development of landscape agronomy. The relationships we point-autor-created version on final draft out are of two main types: (i) the farmers' perception of natural resources and/or landscape patterns, which they use to inform and attune their decision on practices;

  , while landscape agronomy characterizes and explains landscape patterns as a result of specific farming practices, as illustrated by pioneering landscape agronomic research (e.g., INRA-ENSSAA 1977; Sereni 1997) and recently highlighted by Wästfelt et al. (2012).

First

  Fig.1) of landscape dynamics in farmed lands. Third, it could be used as reference

Available at http://ifsa.boku.ac.at/cms/fileadmin/Proceeding2008/2008_WSS_07_Rapey.pdf.Accessed September 2012

Acknowledgments

We are very grateful to our colleagues who contributed their ideas and comments to earlier versions of the paper, in particular to Paolo Bàrberi, Nicola Silvestri, and Patrick Caron. We would also like to warmly thank the students and stakeholders who participated in the two winter schools on landscape agronomy in 2007 and 2009 and the teaching staff and their institutions: the former Land Lab department (now Institute of Life Sciences) of the Scuola Superiore Sant'Anna which financed the schools, and the Science for Action and Development (SAD) department of Institut National de la Recherche Agronomique. We acknowledge the financial support of the French ANR programs COPT, BiodivAgrim, the European FP7 project RUFUS and the Rhin-Meuse Water Agency. The authors also wish to sincerely thank the anonymous reviewers from whom they received useful criticism.


A Favreau-Peigne

R Baumont

C Ginane

Food sensory characteristics: their unconsidered roles in the feeding behaviour of domestic ruminants

Keywords: hedonic value, herbivore, food learning, palatability, sensory cues Implications

When domestic ruminants are faced with food diversity, they can use pre-ingestive information (i.e. food sensory characteristics perceived by the animal before swallowing the food) and post-ingestive information (i.e. digestive and metabolic consequences, experienced by the animal after swallowing the food) to evaluate the food and make decisions to select a suitable diet. The concept of palatability is essential to understand how pre-and post-ingestive information are interrelated. It refers to the hedonic value of the food without any immediate effect of post-ingestive consequences and environmental factors, but with the influence of individual characteristics, such as animal's genetic background, internal state and previous experiences. In the literature, the post-ingestive consequences are commonly considered as the main force that influences feeding behaviour whereas food sensory characteristics are only used as discriminatory agents. This discriminatory role is indeed important for animals to be aware of their feeding environment, and ruminants are able to use their different senses either singly or in combination to discriminate between different foods. However, numerous studies on ruminants' feeding behaviour demonstrate that the role of food sensory characteristics has been underestimated or simplified; they could play at least two other roles. First, some sensory characteristics also possess a hedonic value which influences ruminants' intake, preferences and food learning independently of any immediate post-ingestive consequences. Further, diversity of food sensory characteristics has a hedonic value, as animals prefer an absence of monotony in food sensory characteristics at similar post-ingestive consequences. Second, some of these food sensory characteristics become an indicator of post-ingestive consequences after their initial hedonic value has acquired a positive or a negative value via previous individual food learning or evolutionary processes. These food sensory characteristics thus represent cues that could help ruminants to anticipate the post-ingestive consequences of a food and to improve their learning efficiency, especially in complex environments. This review then suggests that food sensory characteristics could be of importance to provide pleasure to animals, to increase palatability of a food and to help them learn in complex feeding situations which could improve animal welfare and productivity.

Introduction

At pasture, ruminants are faced with varied feeding situations, from monocultures to highly diversified permanent pastures. At pasture, they encounter a great variability of food items that differ in quality and availability, depending on the vegetal species present, their phenological stages and their general state (height, humidity, etc.). In housed systems, ruminants are faced to a lesser extent with food diversity since their diets are generally constituted by one or two types of forages and concentrates. Even when these different components are offered in a complete mixed diet, food diversity can play a role because of animals' abilities to select food [START_REF] Dumont | Diet preferences of herbivores at pasture[END_REF].

As soon as they have choice opportunities, ruminants have to make decisions to select an adequate diet in quality and quantity. Animals can rely on two types of available information to evaluate foods: (i) pre-ingestive information, that is, food sensory characteristics perceived by the animal before swallowing the food, and (ii) post-ingestive information, that is, digestive and metabolic consequences felt by -E-mail: angelique.favreau@agroparistech.fr the animal after swallowing the food. This information is then integrated by the animal to evaluate food's palatability.

Palatability is a key concept to understand how pre-and post-ingestive information interact, but it encounters many definitions in the literature [START_REF] Baumont | Palatability and feeding behaviour in ruminants. A review[END_REF][START_REF] Forbes | Palatability: principles, methodology and practice for farm animals[END_REF]. In Merriam-Webster dictionary, a palatable food is described as agreeable to the palate or taste. [START_REF] Greenhalgh | Relative palatability to sheep of straw, hay and dried grass[END_REF] suggested that palatability reflects those characteristics of a food that invoke a sensory response in the animal. For [START_REF] Rogers | Why a palatability construct is needed[END_REF], palatability is a hypothetical construct which is needed to account for the hedonic value of food sensory characteristics; palatability is influenced by innate factors and can also be modified by learning. Studies concerning the food learning theory have proved that ruminants, as other animals, can associate sensory characteristics and post-ingestive consequences during food learning processes [START_REF] Provenza | Postingestive feedback as an elementary determinant of food preference and intake in ruminants[END_REF][START_REF] Forbes | Integration of learning and metabolic signals into a theory of dietary choice and food intake[END_REF]. They can learn both positive [START_REF] Villalba | Preference for wheat straw by lambs conditioned with intraruminal infusions of starch[END_REF][START_REF] Duncan | Can goats learn about foods through conditioned food aversions and preferences when multiple food options are simultaneously available[END_REF] and negative [START_REF] Zahorik | Taste-aversion learning in three species of ruminants[END_REF] consequences when presented experimentally with simple conditioning procedures (i.e. one pre-and post-ingestive association at a time). Palatability is also influenced by the genetic background of the animal and its internal state (i.e. alliesthesia; [START_REF] Cabanac | Sensory pleasure[END_REF][START_REF] Brondel | Alliesthesia in visual and auditory sensations from environmental signals[END_REF], as well as by environmental conditions and social context [START_REF] Forbes | Palatability: principles, methodology and practice for farm animals[END_REF]. As a result, the concept of palatability integrates various components: (i) an 'intrinsic or pre-conditioned palatability', that is, innate like or dislike attributable to the sensory properties of the food as the result of evolution and/or in utero pre-conditioning, (ii) a 'learned or conditioned palatability', that is, response to food based on prior associations between its sensory characteristics and its post-ingestive consequences and (iii) an 'organismic or reconditioned palatability', that is, acclimatization to a new state, including changes in the physiology of the animal (e.g. deprivation), in the nutritive value of the food or in some aspects of the environment [START_REF] Kissileff | Some suggestions on dealing with palatability -response to Ramirez[END_REF][START_REF] Forbes | Palatability: principles, methodology and practice for farm animals[END_REF]. As there are many methodological difficulties in separating the different components of the whole palatability concept, the term palatability will hereafter refer to the sensory pleasantness of food without any immediate effect of post-ingestive consequences and environmental factors, but with the probable effects of internal-state signals, genetic background and previous food learning.

The concept of palatability, which refers to the hedonic value of food sensory characteristics, appears to be interrelated with the post-ingestive consequences [START_REF] Provenza | Postingestive feedback as an elementary determinant of food preference and intake in ruminants[END_REF] or even totally calibrated by them [START_REF] Garcia | Food for Tolman: coginition and cathexis in concert[END_REF]. In studies on food preferences and aversions, it is normal to consider the post-ingestive consequences as the main force that influences preferences, and to relegate the pre-ingestive stimuli to the simple status of discriminatory agents. Sensory characteristics are actually important for animals to discriminate between various food items as this review will show, focusing on the different senses involved in this essential task.

However, sensory motivation to eat can override postingestive signals in some cases (Baumont et al., 1990a), sensory characteristics can induce preferences in the absence of any immediate post-ingestive consequences (e.g. umami taste; [START_REF] Gherardi | Effect of palatability on voluntary feed intake by sheep. I -Identification of chemicals that alter the palatability of a forage[END_REF], and ruminants show difficulties to learn in complex experimental feeding situation where the food sensory characteristics are just used as discriminating tools. It thus seems that the role of sensory characteristics in ruminants' feeding behaviour have been underestimated and is more important than previously described in the literature. As a consequence, this review aims to emphasize some of the other roles of food sensory characteristics in the feeding behaviour of domestic ruminants.

Sensory characteristics: a way to discriminate between foods

The unique role that is consensually assigned to food sensory characteristics is the one that allows animals to be aware of their feeding environment and to discriminate between different food items using their different senses, either singly or in combination. Animals will use one sense or another depending on its distance with the food. Sight and smell are supposed to help animals in making a first sensory evaluation of food without any direct contact. Touch and taste are in use as soon as there is a direct contact between the lips and mouth of the animal and the plant. Taste and smell are, however, often mixed together resulting in a global stimulation of the oro-pharyngeal area, called flavour.

The sense of sight is supposed to be mainly used to orientate herbivores at pasture by a discrimination process at a large scale (Arnold, 1966a). At a smaller scale, sight can also allow them to discriminate between objects of different brightness [START_REF] Bazely | Discrimination learning in sheep with cues varying in brightness and hue[END_REF] and colours [START_REF] Kendrick | The activity of neurones in the lateral hypothalamus and zona incerta of the sheep responding to the sight or approach of food is modified by learning and satiety and reflects food preference[END_REF], swards differing in height [START_REF] Bazely | Rules and cues used by sheep foraging in monocultures[END_REF], plant species (i.e. clover and ryegrass, [START_REF] Edwards | Use of cues by grazing animals to locate food patches: an example with sheep[END_REF] and different clover polymorphisms by recognizing white leaf marks [START_REF] Cahn | The biology of the leaf mark polymorphism in Trifolium repens L[END_REF]. Furthermore, Arnold (1966a) showed that the diets selected by blinkered sheep were of lower quality than those of control sheep. Thus, sight is used by sheep to discriminate and identify foods, and this affects their diet selection to some extent.

The sense of touch is also of importance since grazing animals generally select against rough, harsh, sticky or spiny material [START_REF] Baumont | Palatability and feeding behaviour in ruminants. A review[END_REF][START_REF] Vallentine | Grazing management[END_REF]. Conversely, goats can overcome physical defences of certain trees because they have hard mouth parts that are unaffected by spines and thorns [START_REF] Cheeke | Comparative animal nutrition and metabolism[END_REF]. [START_REF] Krueger | Relationship of taste, smell, sight, and touch to forage selection[END_REF] determined that touch appeared primarily to supplement the sense of taste in selection of plant species, but plants selected, at least in part, on the basis of touch were all categorized as 'low' in coarseness (e.g. mountain knotweed, mountain sorrel). Physical characteristics and the sense of touch play a role in the acceptability of some food items as it is the case for various strains of Bromus grasses (Arnold, 1966b).

Sensory characteristics in feeding behaviour

Taste is the last discriminating sense used by the animal before swallowing a food. It refers to the five basic tastes, namely the sweet, salty, bitter and sour tastes, incremented recently by the umami taste [START_REF] Lindemann | Receptors and transduction in taste[END_REF]. Various behavioural methods have been used to demonstrate that ruminants perceive and discriminate among tastes [START_REF] Ginane | Perception and hedonic value of basic tastes in domestic ruminants[END_REF]. For instance, two-bottle choice tests have shown that sheep, goats and cattle are sensitive to sweet, salty, sour and bitter tastes (Goatcher and Church, 1970c; Krueger et al., 1974). These sensitivities, measured as the lowest concentration discriminated by the animals, differed both between species (e.g. cattle . goats . sheep for the sweet taste) and between tastes within species (i.e. sweet , salty , sour , bitter for all studied ruminant species) (Goatcher andChurch, 1970a and1970c). Sensitivities for bitter taste vary with the grazer/browser dichotomy: grazers (domestic ruminants who eat grass, e.g. cattle and sheep) are more sensitive to bitter taste than browsers (domestic ruminants who also eat forbs, shrubs and trees, e.g. goats; Glendinning, 1994). It was supposed that browsers have evolved to be less sensitive to bitter taste because they commonly encounter toxic plants that have a bitter taste [START_REF] Favreau-Peigne | Is the bitter taste rejection always adaptive?[END_REF]. The umami taste, induced by monosodium glutamate, is perceived by sheep since (i) it increased intake of sham-fed animals [START_REF] Colucci | Factors affecting the voluntary intake of food by sheep. 6. The effect of monosodium glutamate on the palatability of straw diets by sham-fed and normal animals[END_REF] and (ii) it induced preferences when added to hay compared with the same untreated hay [START_REF] Gherardi | Effect of palatability on voluntary feed intake by sheep. I -Identification of chemicals that alter the palatability of a forage[END_REF]. Recent studies, using either a non-caloric flavour or monosodium glutamate to induce the umami taste, showed that lambs are able to perceive umami taste in a feed, as they increased their preference for this feed (Favreau et al., 2010a;[START_REF] Villalba | Feeding behaviour and performance of lambs are influenced by flavor diversity[END_REF][START_REF] Bach | Interactions between mild nutrient imbalance and taste preferences in young ruminants[END_REF].

Compared with taste, the sense of smell is supposed to be of lower importance in diet selection [START_REF] Krueger | Relationship of taste, smell, sight, and touch to forage selection[END_REF]. As it is difficult to differentiate between animals' appreciation of smell (from volatile components of the food) and taste (from soluble components) because they both mix and form a flavour once the food enters the mouth [START_REF] Forbes | Food choice[END_REF], smell is often considered to supplement the sense of taste. Natural or artificial flavours are frequently used in conditioning experiments by adding them to a common food so as to create distinct foods from the animals' sensory perception [START_REF] Provenza | Preference of sheep for foods varying in flavors and nutrients[END_REF]Favreau et al., 2010b). Many experiments have thus shown that sheep discriminate between different artificial flavours, such as between orange and aniseed [START_REF] Kyriazakis | Mild conditioned food aversions developed by sheep towards flavors associated with plant secondary compounds[END_REF], onion and coconut [START_REF] Villalba | Preference for flavored wheat straw by lambs conditioned with intraruminal infusions of starch administered at different times after straw ingestion[END_REF] or between onion flavour at different concentrations [START_REF] Villalba | Roles of flavor and reward intensities in acquisition and generalization of food preferences: do strong plant signals always deter herbivory[END_REF]. Sheep and goats were also shown to discriminate many different flavours (maple, strawberry, onion, etc.) from the same untreated food [START_REF] Robertson | Preferences of sheep and goats for straw pellets treated with different food-flavouring agents[END_REF]. Only a few experiments have used natural odours, such as plant aromatic extract or natural compounds (e.g. tannic acid, cedarwood oil, etc.), and these showed that ruminants are able to discriminate them by comparing intakes of normal v. anosmic sheep [START_REF] Arnold | The influence of odour and taste on the food preferences and food intake of sheep[END_REF] or by submitted goats to cafeteria trials [START_REF] Gd | Influence of flavor on goat feeding preferences[END_REF].

Sensory characteristics: a way to get pleasure

From neuroscientists' point of view, palatability corresponds to the 'liking' or hedonic component of the brain reward system [START_REF] Berridge | Food reward: brain substrates of wanting and liking[END_REF], which deals with affective responses to the food and induces pleasure [START_REF] Berridge | Affective neuroscience of pleasure: reward in humans and animals[END_REF].

How to assess the palatability of food sensory characteristics? A non-invasive and simple way to assess the hedonic value of food sensory characteristics is to observe the animals' behavioural responses to these sensory characteristics, without any immediate effect of post-ingestive consequences.

This can be achieved by (i) measuring short-term preferences and/or intake since it can be assumed that the postingestive consequences of the food have not been felt by the animal yet (Favreau et al., 2010c), (ii) by using an ingredient able to modify the sensory properties of the food without adding any post-ingestive consequence (e.g. a calorie-free sweetener such as saccharin; [START_REF] Hellekant | Sweet taste in the calf: III. Behavioral responses to sweeteners[END_REF], (iii) by offering the different food items simultaneously since it increases the difficulty for the animal to identify which food item is responsible for which consequence [START_REF] Duncan | Can goats learn about foods through conditioned food aversions and preferences when multiple food options are simultaneously available[END_REF]Favreau et al., 2010b), and/or (iv) by checking, with a conditioning procedure, that the intake of the added sensory modifier does not cause any post-ingestive consequence at the dose rate involved in the study [START_REF] Gherardi | Effect of palatability on voluntary feed intake by sheep. I -Identification of chemicals that alter the palatability of a forage[END_REF]Favreau et al., 2010a).

Two methods using fistulated animals could also be used to assess the hedonic value of food sensory characteristics by avoiding any influence of immediate post-ingestive consequences on animals' behavioural responses to the food. The first one is the sham-feeding method which allows the oro-pharyngeal stimulation of the animal while ingesting the food but prevents the food ingested by the animal from entering into the rumen thanks to the presence of an oesophageal fistula [START_REF] Grovum | Factors affecting the voluntary intake of food by sheep. 4. The effect of additives representing the primary tastes on sham intakes by oesophageal-fistulated sheep[END_REF][START_REF] Colucci | Factors affecting the voluntary intake of food by sheep. 6. The effect of monosodium glutamate on the palatability of straw diets by sham-fed and normal animals[END_REF]. The second method consists in controlling both the oro-pharyngeal stimuli and the post-ingestive consequences of the diet. It can be achieved by offering one food to be orally consumed (o) while the same or another food is introduced in the rumen of the animal via a rumen fistula (r) in an equal amount to that of the food orally consumed. The palatability of the two tested food (A and B) could then be assessed by comparing feeding behaviour in reversed situations (i.e. comparison of Ao/Br and Bo/Ar situations), where the food sensory characteristics are different, but the diet composition and the post-ingestive consequences are similar [START_REF] Greenhalgh | Relative palatability to sheep of straw, hay and dried grass[END_REF]Favreau et al., 2010c).

Operant conditioning can also be a way to assess food palatability. It consists of positive or negative reinforcements applied to the animal after it performs the appropriate behaviour. The animal thus decides to act or not in order to gain a reward or to avoid a punishment. Then, the amount of work an animal is prepared to perform in order to obtain food is Favreau-Peigne ´, Baumont and Ginane used to assess its palatability. Sheep were thus trained to press a panel to receive a food reward which allowed [START_REF] Hutson | Food preferences of sheep[END_REF] to show that the highest level of response was obtained for barley and wheat over peas, lucerne, lupins and oats. Animals were also trained to walk in order to obtain a good-quality food while a poor-quality food is freely available; the longer distance an animal is prepared to walk, the more the good-quality food is preferred (Dumont et al., 1998). Some studies used the walking distance index to determine how food palatability is increased by food restriction [START_REF] Schu ¨tz | Do different levels of moderate feed deprivation in dairy cows affect feeding motivation?[END_REF][START_REF] Verbeek | Measurement of feeding motivation in sheep and the effects of food restriction[END_REF]. Does the palatability of food sensory characteristics affect intake and feeding pattern? Using two good-quality forages (lucerne and grass hays) with different sensory characteristics, daily dry matter intake did not differ when controlling for post-ingestive consequences (Favreau et al., 2010c; Figure 1). [START_REF] Greenhalgh | Relative palatability to sheep of straw, hay and dried grass[END_REF] found similar results when offering two good-quality forages (dried grass and meadow hay), whereas they demonstrated that sensory characteristics influenced the daily intake of a lowquality forage (oat straw) compared with a good-quality forage (dried grass; Figure 1).

These differences could be explained by an insufficient sensory contrast between the better-quality forages used in the first two studies which cannot influence daily intake regardless of post-ingestive consequences. In return, when the contrast is stronger, and even if previous knowledge about the respective post-ingestive consequences of the foods has surely participated in shaping their palatability, it appears that foods' palatability can affect daily intake.

Food palatability can also influence intake in the short term. It has been shown that satiated sheep ate a substantial meal after a second distribution of a sufficiently palatable hay; this meal was then associated with an increase in rumen fill of up to 10% of the daily maximum observed without this second distribution (Baumont et al., 1990b). The hedonic stimulation induced by the new distribution thus overrode the satiety signals due to rumen fill. In the same way, moderate energy preloads, combined with manipulations of palatability during a test meal, resulted in overconsumption in humans, thus demonstrating that the hedonic value of food sensory characteristics decreased the ability of short-term satiety cues to stop intake [START_REF] Yeomans | Effects of test-meal palatability on compensatory eating following disguised fat and carbohydrate preloads[END_REF]. In sheep, when post-ingestive consequences were controlled, the intake of lucerne hay was higher than that of grass hay just after food distribution, indicating that the motivation to eat was then higher than the negative fill effect of the hay introduced in the rumen (Favreau et al., 2010c). Finally, the physical form (pellets or cubes) and the addition of monosodium glutamate (i.e. umami taste) increased the palatability of straw (a poor-quality food) which induced higher sham intakes in the short term [START_REF] Colucci | Factors affecting the voluntary intake of food by sheep. 6. The effect of monosodium glutamate on the palatability of straw diets by sham-fed and normal animals[END_REF]. On the contrary, a low palatability can decrease the short-term intake of a food in cattle (palm kernel expeller; Spo ¨rndly and A ˚sberg, 2006).

Does the palatability of food sensory characteristics affect preferences?

As soon as ruminants have choice opportunities, they express preferences. These preferences are influenced by the effect of post-ingestive consequences [START_REF] Provenza | Postingestive feedback as an elementary determinant of food preference and intake in ruminants[END_REF], but some results suggest that the relative hedonic value of food sensory characteristics is involved as well. Sensory characteristics were indeed able to induce food preferences by their own, that is, without any immediate positive postingestive reinforcement as it is the case with umami taste [START_REF] Grovum | Factors affecting the voluntary intake of food by sheep. 4. The effect of additives representing the primary tastes on sham intakes by oesophageal-fistulated sheep[END_REF][START_REF] Gherardi | Effect of palatability on voluntary feed intake by sheep. I -Identification of chemicals that alter the palatability of a forage[END_REF]. The umami taste, induced by monosodium glutamate, seems to have a positive hedonic value in sheep, as it induced strong and constant preferences for the treated food over the same untreated food, regardless of the doses [START_REF] Gherardi | Effect of palatability on voluntary feed intake by sheep. I -Identification of chemicals that alter the palatability of a forage[END_REF]Favreau et al., 2010a). In cattle, umami induced such a preference in young animals (e.g. in animals weaned at 3 weeks of age, and from 3 to 6 weeks of age; Waldern and van Dyk, 1971). In the same way, when different flavours are sprayed on the same food (i.e. to ensure similar post-ingestive consequences) and compared in shortterm choice tests with the same unflavoured food, animals often express clear preferences. This was the case for sheep preferring an aniseed-flavoured orchard grass hay, at a rate of 80%, compared with an orange-flavoured orchard grass hay (Favreau et al., 2010b), suggesting that the aniseed flavour has a higher hedonic value than the orange flavour in sheep. However, this result is inconsistent with those of other studies in which sheep did not express any preference between the two flavours [START_REF] Kyriazakis | Mild conditioned food aversions developed by sheep towards flavors associated with plant secondary compounds[END_REF][START_REF] Arsenos | Conditioned feeding responses of sheep towards flavoured foods associated with casein administration: the role of long delay learning[END_REF]. Such variability was also frequently reported in Figure 1 Voluntary intake (mean 6 s.e.) measured in three studies involving the same methodology consists in offering one food at the trough to be orally consumed ad libitum (indicated on the upper part of the bars) while the same or another food is introduced in the rumen of the animal via a rumen fistula (indicated in the lower part of the bars). The first experiment [START_REF] Greenhalgh | Relative palatability to sheep of straw, hay and dried grass[END_REF]) used a good-quality forage (dried grass 5 Dg, 13.9% of CP in dry matter) and a low-quality forage (oat straw 5 Os, 3.9% CP). The second [START_REF] Greenhalgh | Relative palatability to sheep of straw, hay and dried grass[END_REF]) and third (Favreau et al., 2010c) experiments used two good-quality forages (meadow hay 5 Mh, 7.7% CP v. dried grass 5 Dg, 13.9% CP; lucerne hay 5 Lh, 15.6% CP v. grass hay 5 Gh, 7.2% CP, respectively).

Sensory characteristics in feeding behaviour the literature concerning sweet taste (see Ginane et al., 2011 for review). Individual variability in preferences between flavours or tastes in the absence of immediate post-ingestive influence are also widely encountered in different experiments (Goatcher andChurch, 1970a and1970b;[START_REF] Robertson | Preferences of sheep and goats for straw pellets treated with different food-flavouring agents[END_REF]. In the absence of immediate post-ingestive consequences that usually calibrate food preferences, it appears logical to encounter a great individual variability since is known that individual characteristics, such as animal's physiological and emotional states [START_REF] Brondel | Alliesthesia in visual and auditory sensations from environmental signals[END_REF][START_REF] Brondel | Alliesthesia in visual and auditory sensations from environmental signals[END_REF]Tamashiro et al., 2007, respectively) and previous experiences [START_REF] Provenza | Postingestive feedback as an elementary determinant of food preference and intake in ruminants[END_REF] in utero [START_REF] Simitzis | Effect of early dietary experiences on the development of feeding preferences in semiintensive sheep farming systems -a brief note[END_REF] or early in life [START_REF] Miller-Cushon | Effect of early feed type exposure on diet-selection behavior of dairy calves[END_REF], can affect palatability. Experiences in utero and early in life cause neurological, morphological and physiological changes because of the interactions between genome, environment and post-ingestive consequences; this participates in the uniqueness of each individual [START_REF] Provenza | Linking herbivore experience, varied diets, and plant biochemical diversity[END_REF]. These differences in preferences can lead to variability in food selection in the field; as a consequence, it can result in less grazing pressure on individual vegetation species, which can represent an evolutionary advantage for social herbivore species (Goatcher and Church, 1970b).

The hedonic value of food sensory diversity When ruminants are offered a choice between foods that differ in how long they have not been eaten, they generally prefer the one that was not consumed recently. This was true for sheep preferring the flavour presented first within a conditioning period over that presented second [START_REF] Arsenos | Conditioned feeding responses of sheep towards flavoured foods associated with casein administration: the role of long delay learning[END_REF], for ewes preferring the opposite species (i.e. white clover or ryegrass) to the one they had previously grazed [START_REF] Newman | Not all sheep prefer clover: diet selection revisited[END_REF][START_REF] Parsons | Diet preference of sheep: effects of recent diet, physiological state and species abundance[END_REF], and for heifers temporarily increasing their preference for the hay that had not been offered during the previous period [START_REF] Ginane | Feeding behaviour and intake of heifers fed on hays of various quality, offered alone or in a choice situation[END_REF]. The authors suggested that the preference for the 'new' hay could be explained by (i) the animal's need to select a balanced diet that best meets its homeostatic requirements or (ii) the animals' search for rarity for functional purposes, such as maintaining gut flora diversity or (iii) an attractive effect of novelty, considered as a search for diversity. On that last point, [START_REF] Scott | Variety of foods and flavors affects selection of foraging location by sheep[END_REF] demonstrated that a variety of flavours is preferred relative to monotony by lambs when food nutrient content was constant between the different food items available. Similarly, sheep always preferred in the short term the hay they were not used to eating, whatever its nature (lucerne or grass hay), even when the post-ingestive consequences associated with animals' diet were similar (Favreau et al., 2010c). This preference for diversity suggests the existence of a hedonic dimension for food sensory characteristics. This is consistent with the concept of sensory specific satiety, which assumes that the hedonic value of food sensory characteristics will decrease as it is consumed [START_REF] Rolls | Sensory-specific satiety[END_REF]. This is also consistent with recent findings showing that lambs receiving a monotonous diet had higher cortisol levels 1 h after food presentation than lambs receiving a diverse diet, indicating a stressing effect of monotony [START_REF] Villalba | Relationships between early experience to dietary diversity, acceptance of novel flavors, and open field behavior in sheep[END_REF]. Ruminants thus appear to search for diversity for their pleasure as well as for their needs. As a consequence, the absence of food diversity, encountered when animals are conducted outdoors on monoculture or fed indoors with the same diet over several weeks or months, may have negative implications on animal welfare. Does the palatability of food sensory characteristics affect food learning? As mentioned above, sheep showed a higher initial preference for aniseed-flavoured orchard grass hay compared with orange-flavoured orchard grass hay (Favreau et al., 2010b). After conditioning, the preference for the flavoured hay associated with the negative post-ingestive consequence was still influenced by these initial preferences, that is, sheep negatively conditioned on aniseed expressed a lesser avoidance than sheep negatively conditioned on orange (0.53 6 0.04 v. 0.25 6 0.03, respectively; Favreau et al., 2010b). Similar results were found with a higher initial hedonic preference for fenugreek flavour over garlic flavour which then influenced the conditioned responses of sheep [START_REF] Arsenos | Conditioned feeding responses of sheep towards flavoured foods associated with casein administration: the role of long delay learning[END_REF]. Therefore, it appears that the initial palatability of a food influences its evaluation by sheep in a learning context. It then affects the animals' propensity to make an associative learning between sensory characteristics and post-ingestive consequences. It may be easier for animals to associate a food initially preferred with a positive than with a negative consequence.

Sensory characteristics: a way to indicate the nature of the post-ingestive consequences of the food

The condition for a food sensory characteristic to become an informative signal is that animals are able to give it a meaning via evolution and/or by using individual learning processes. When animals encounter a new food and have no knowledge about it, they hesitate or even refuse to eat it. This neophobic response is considered as adaptive, as it helps animals to avoid eating harmful foods at the first encounter, and give them the opportunity to learn about their post-ingestive consequences [START_REF] Birch | Development of food preferences[END_REF]. At the individual learning level, it has been largely demonstrated that ruminants, such as sheep [START_REF] Du Toit | Conditioned taste aversions: how sick must a ruminant get before it learns about toxicity in foods?[END_REF][START_REF] Burritt | Lambs form preferences for nonnutritive flavors paired with glucose[END_REF], cattle [START_REF] Ralphs | Conditioned food aversions: principles and practices, with special reference to social facilitation[END_REF] and goats [START_REF] Duncan | Can goats learn about foods through conditioned food aversions and preferences when multiple food options are simultaneously available[END_REF], are able to associate food sensory characteristics with post-ingestive consequences when the experimental learning procedure is simple (i.e. one association between sensory characteristics and post-ingestive consequences to learn at a time), and modify their diet selection accordingly. However, animals show difficulties to learn when the experimental learning procedure becomes more complex and closer to natural situations, which could be achieved experimentally either by offering several different foods simultaneously during the conditioning procedure [START_REF] Duncan | Can goats learn about foods through conditioned food aversions and preferences when multiple food options are simultaneously available[END_REF], by increasing the number of consequences associated with each food [START_REF] Ginane | Herbivore diet selection in response to simulated variation in nutrient rewards and plant secondary compounds[END_REF] or by modifying Favreau-Peigne ´, Baumont and Ginane the length of feeding bouts and the rate of nutrient delivery (Duncan et al., 2007). In these studies designed to test foodlearning abilities in ruminants, food sensory characteristics can only be used as discriminating tools because they are meaningless for the animals at the very first association, that is, they do not indicate to the animal the post-ingestive consequences associated with the food. Diverse sensory characteristics of plants could, however, act as crude indicators of their nutritional and toxic values in the field. For instance, several secondary plant compounds have a bitter taste and are toxic to herbivores [START_REF] Garcia | The evolution of bitter and the acquisition of toxiphobia[END_REF][START_REF] Rogosic | Potential mechanisms to increase shrub intake and performance of small ruminants in mediterranean shrubby ecosystems[END_REF], and a young green plant is generally more nutritious than a mature plant (Ku ¨hnle and Mu ¨ller, 2011). Further, other species use food sensory characteristics as indicators of their potential toxic or nutritive values, as shown with birds avoiding invertebrates' aposematic colouring [START_REF] Aronsson | Domestic chicks primarily attend to colour, not pattern, when learning an aposematic coloration[END_REF][START_REF] Skelhorn | Colour biases are more than a question of taste[END_REF]. Edwards et al. (1997) demonstrated that sheep could use visual and smelling cues (in turves of perennial ryegrass or white clover) to find rewards (highly preferred pelleted food). Sheep expressed an aversion for a familiar food when added with a cue, that is, a novel odour, which was previously associated with toxicosis; this was true for both artificial flavour (coconut) and natural odour (the odour of Astragalus bisulcatus; [START_REF] Provenza | Roles of odor, taste, and toxicity in the food preferences of lambs: implications for mimicry in plants[END_REF]. In that study, it appears that the sensory characteristic has acquired a meaning, indicating a probable toxicity to the animal which, as a consequence, reduced its preference for the food associated with that cue. Conversely, sensory characteristics can be a positive cue. Food neophobia can be overcome by adding a familiar flavour or odour on a novel food [START_REF] Launchbaugh | Overcoming food neophobia in domestic ruminants through addition of a familiar flavor and repeated exposure to novel foods[END_REF][START_REF] Van Tien | Grass odor and flavor overcome feed neophobia in sheep[END_REF]. Familiarity can be considered as a cue indicating that the food is safe [START_REF] Burritt | Food aversion learning: ability of lambs to distinguish safe from harmful foods[END_REF].

Further, a recent study demonstrated that the use of food sensory characteristics (flavours experimentally associated with negative or positive post-ingestive consequences) as indicators of the value of the food allowed sheep to improve their learning efficiency in a subsequent complex learning task compared with naı ¨ve sheep (Favreau et al., 2010b). This also underlines their ability to generalize their knowledge about flavours to different situations varying in complexity and confirms previous results [START_REF] Launchbaugh | The effect of flavor concentration and toxin dose on the formation and generalization of flavor aversions in lambs[END_REF][START_REF] Ginane | Generalization of conditioned food aversions in grazing sheep and its implication for food categorization[END_REF]. So sheep can rely on sensory cues, which provide an essential help in learning about food especially in complex environments. [START_REF] Howery | Cattle use visual cues to track food locations[END_REF] demonstrated that cattle can learn to associate visual cues (traffic barricades and traffic cones) with disparate food qualities and use this information to forage more efficiently in environments varying in complexity (fixed or variable locations of foods in the field).

Plants encountered in the field by animals differ in many sensorial characteristics and notably in their taste profiles; some of them are supposed to reveal the value of the food. Thus, they constitute an interesting natural cue to study the potential role of food sensory characteristics as an indicator of post-ingestive consequences. Hence, several plant secondary compounds that are toxic to herbivores have a bitter taste [START_REF] Garcia | The evolution of bitter and the acquisition of toxiphobia[END_REF][START_REF] Rogosic | Potential mechanisms to increase shrub intake and performance of small ruminants in mediterranean shrubby ecosystems[END_REF], whereas sweet and umami tastes are supposed to be associated with energy [START_REF] Swithers | A Role for sweet taste: calorie predictive relations in energy regulation by rats[END_REF] and protein [START_REF] Naim | Interaction of MSG taste with nutrition -perspectives in consummatory behavior and digestion[END_REF] contents, respectively. A recent study demonstrated that the umami taste would have a positive value, expressed by a high initial preference, whereas the bitter taste would have a negative value as shown by the reluctance of sheep to increase their preference for this taste once it is associated with positive consequences (Favreau et al., 2010a). Thus, herbivores seem to attribute a priori values to natural basic tastes. Consequently, it is suggested that ruminants could use primary tastes as cues to anticipate food consequences and then to forage both more efficiently and more safely, although this still needs to be tested.

Conclusion

This review brings to light that the roles of food sensory characteristics have been previously underestimated or simplified, and underlines three important roles of food sensory characteristics on ruminants' feeding behaviour (Figure 2). First, all sensory characteristics can be considered as discriminating characteristics that allow animals to distinguish between different food items. Second, some of these sensory characteristics possess a hedonic value that influences ruminants' intake, preferences and food learning independently of any immediate post-ingestive consequences. Third, for some of them, the initial hedonic value has acquired a positive or a negative value either via previous individual Figure 2 Diagram of the interrelated roles of food sensory characteristics and post-ingestive consequences in the feeding behaviour of domestic ruminants and its control. The post-ingestive consequences play a major role in ruminants' feeding behaviour because of their fill effect and/or their nutritive/toxic effect. All sensory characteristics are discriminating characteristics (i.e. they help animals to distinguish between different food items). Some of them possess a hedonic value that influences food learning, intake and preferences at least on the short term. Then, some of them have acquired a positive or a negative value through individual learning or evolutionary processes. This value could play an indicator role that allows ruminants to anticipate the post-ingestive consequences associated with the food consumed, and then improve their food learning efficiency especially in complex environment.

food learning or via evolutionary processes. This value then makes possible for a sensory characteristic to become an indicator that allows ruminants to anticipate the postingestive consequences of a food and to improve their learning efficiency, which could be of interest for animals, especially in complex environments.

Perspectives and significance

This review suggests some avenues to follow in order to improve animal welfare and productivity by taking into account these multiple roles of food sensory characteristics. For instance, food sensory characteristics could be used to improve palatability of poor quality or new foods, so as to increase their acceptability, at least in the short term. Further, animals seem to search for an absence of monotony in food sensory characteristics. This could represent an easy way to enrich their environment and improve their welfare. Sensory cues could also be created by animal managers to help animals anticipate the post-ingestive consequences of some toxic plants so that they avoid them in the field.

Acknowledgements

The authors are grateful to INRA and the Auvergne Region for their funding.


T Cavalié

F Billebaud

E Lellouch

N Biver

M Dobrijevic

J Brillet

A Lecacheux

Å Hjalmarson

A Sandqvist

U Frisk

M Olberg

The Odin Team

CONTRIBUTION OF THE ODIN SPACE TELESCOPE TO THE UNDERSTANDING OF THE ORIGIN OF WATER VAPOR IN THE ATMOSPHERE OF JUPITER

published or not. The documents may come

Introduction

The Infrared Space Observatory has detected water vapor in the stratospheres of the giant planets and Titan as well as CO 2 on Jupiter, Saturn and Neptune (Feuchtgruber et al. 1997;[START_REF] Feuchtgruber | The Universe as Seen by ISO[END_REF][START_REF] Lellouch | The Universe as Seen by ISO[END_REF]. The presence of the atmospheric cold trap implies an external origin for H 2 O, which could be the permanent infall of interplanetary dust particles (IDP), the sputtering from the rings and/or satellites or the impact of kilometer-sized comets. In the case of Jupiter, the sources of water could either be IDP (Bergin et al. 2000) or the Shoemaker-Levy 9 (SL9) comet impacts in 1994 (Lellouch et al. 2002).

The submillimeter satellite Odin has been launched in 2001 and carries out a long lasting monitoring of Jupiter's water vapor line (110-101) at 557 GHz. As an example, the high resolution H 2 O spectrum obtained on November 8 th 2002 is presented and discussed here. Both the IDP and the SL9 origins have been modeled with our photochemical model (Ollivier et al. 2000, adapted to Jupiter).

A description of the observations is given in Sect. 2. Our photochemical and radiative transfer models are briefly described in Sect. 3. Some preliminary results are presented in Sect. 4.

Observations

The Odin space telescope detected the water vapor 557 GHz line on Jupiter in November 2002. The resulting brightness temperature spectra have a high signal-to-noise ratio (∼12). The spectral band is 1 GHz and the spectral resolution is about 1 MHz.

The Odin observations were carried out with the Acousto-Optical Spectrometer (AOS) in a classical position switching mode. As Jupiter has a strong continuum emission at this frequency, stationnary waves are generated within the instrument, causing ripples on the spectrum (Fig. 1). The subtraction of the ripple is the source of an uncertainty of 10% on the line contrast and some uncertainty on the line wing shape.

1 Université Bordeaux 1, CNRS, OASU, LAB, 2 rue de l'Observatoire, 33270 Floirac, France 2 (the same as T. Cavalié listed above) 3 LESIA, Observatoire de Paris, France 4 (the same as E. Lellouch listed above) 5 (the same as T. Cavalié listed above) 6 (the same as T. Cavalié listed above) All the observed features correspond to the emission of the whole planet as the beam size (2.1' for Odin) is greater than the planet size (∼35-40"). The line width is almost entirely due to the smearing effect because of limb equatorial velocity ∼12.6 km.s -1 of the planet (Bergin et al. 2000). As no absolute calibration has been done, all results are discussed in terms of line-to-continuum ratios.

Modeling

We performed our data analysis in three steps: first, we used our photochemical code to provide a water vapor vertical profile and then used this profile to compute the resulting spectral line. Finally, comparing the synthetic spectrum with the data allowed us to fix the input parameters of the photochemical code (input of water vapor).

Photochemical modeling

We used a time-dependant photochemical model, which derives from the model established for Saturn by Ollivier et al. (2000) and which has been adapted to the case of the atmosphere of Jupiter. For each altitude and each chemical compound i, the continuity equation (3.1) is solved.

dn i dt = P i -n i L i -div (φ i ) (3.1)
n is the concentration, P the chemical production, L the chemical loss and φ the vertical flux. This is a one dimension model since only the vertical transport is considered.

The model includes 46 oxygen compounds and hydrocarbons and 593 reactions (photolysis processes and chemical reactions). Condensation near the tropopause is also considered. The eddy diffusion coefficient profile we took comes from Moses et al. (2005). We chose their nominal eddy profile called "model C". Feuchtgruber et al. (1997) and Moses et al. (2000) showed that an IDP source is more likely than a ring/satellite source since there is a difference of two orders of magnitude in the estimated fluxes. This is the reason why we chose to compare the results of two models: an IDP source model and a IDP+SL9 source model. The lack of spatial resolution of the observations allowed us to use disk-averaged abundance vertical profiles for water, even if the SL9 impacts were all located in the southern hemisphere. The only input parameter we had to fix to test the IDP source hypothesis is the external flux of infalling water Φ IDP H2O . In order to test the SL9 source hypothesis, we have built vertical profiles at the time of the impacts (July 1994) and let them evolve with the photochemical model until the time of the observations (November 2002 for the Odin data). The initial water vertical profiles have been built on the base of a low stationnary external flux and a sporadic external flux, due to the comet. The low stationnary input flux is modeled via an IDP model with a flux Φ IDP H2O =4 10 4 cm -2 s -1 (Lelluch et al. 2002). This value is 2 orders of magnitude lower than a pure IDP model (see Sect. 4). The sporadic input of water due to the impacts was modeled via two parameters: the deposition pressure p 0 and the initial mixing ratio q 0 above the p 0 level (see Lellouch et al. 2002 for more details). The value of q 0 was set to a constant value. Thus, we have two possibilities for the SL9 models. The first one consists in fixing the value of p 0 and adjusting the value of q 0 with the data. In the second case, we fix q 0 and adjust p 0 . Some constraints exist on both p 0 and q 0 . The most reliable constrain is probably the fact that the deposition level that was observed for CO during the SL9 impacts is 0.2±0.1 mbar (Moreno 1998). The other constrain lies on the observed column density of water vapor. Lellouch et al. 2002 inferred that the H 2 O/CO ratio is equal to 0.07 in mass to explain the entire ISO data set, thus fixing the H 2 O column density to (2.0±0.5) 10 15 cm -2 . We kept these numbers in mind in order to constrain our SL9 source models. An example when fixing p 0 is shown on Fig. 2 as well as the profile, at the time of the observations, computed by the photochemical model.

Radiative transfer modeling

We modeled the observed submillimetric radiations with a line-by-line non-scattering radiative transfer model. We computed synthetic spectra of the H 2 O 557 GHz line. The program respects the approximate spherical geometry of the planet so that planetary disk and limb contributions are taken into account. We assumed an uniform distribution of all other opacity sources and we adopted mean thermal profile of the atmosphere of Jupiter (Fouchet et al. 2000a) since our beam size is larger than the observed planetary disk. Continuum opacity is dominated by H 2 -He-CH 4 collision-induced absorption (Borysow et al. 1985(Borysow et al. , 1986(Borysow et al. and 1988)). Following Moreno (1998), the opacity due to the far wings of ammonia and phosphine lines was also included. We used the Fouchet et al. (2000b) ammonia and phosphine mixing ratio vertical profiles. Spectroscopic parameters for NH 3 , PH 3 and H 2 O were taken from Pickett et al. (1998).

The rapid rotation of Jupiter (9.9 h) induces the smearing of the disk-averaged line on the spectrum, because of the Doppler shifts due to the gas rotation velocity (12.6 km.s -1 at the eastern and western limbs). The way this effect is taken into account is described in Bergin et al. (2000).

Preliminary results

The best fit models we obtained are displayed in Fig. 3. We derived an external flux of water, originating from an IDP source, of Φ IDP H2O =4.5 10 6 cm -2 s -1 . This value is greater than the one derived by Bergin et al. (2000) by a factor of less than 2. Nevertheless, their model did only include vertical transport (no chemical processes). Fig. 3. Brightness temperature spectrum of Jupiter at 557 GHz with the best fit models for each external origin hypothesis. The IDP source fit (dashed lines) results in too broad wings compared to both SL9 source fits. The dotted lines corresponds to the couple of parameters (p0=0.45 mbar; q0=6 10 -8 ) and the solid line to the couple (p0=0.2 mbar;

q0=1.5 10 -7 ).

Taking photolysis and chemical losses into account, they would probably have obtained a higher value for the flux consistent with our result. When considering the SL9 source hypothesis and fixing the value of q 0 at 6 10 -8 , we derive a deposition pressure level p 0 of 0.45 mbar. When fixing p 0 =0.2 mbar, we obtain q 0 =1.5 10 -7 , leading to a water column density of 2.6 10 15 cm -2 . The latter set of parameters better reproduces the line contrast than the previous one (see Fig. 3).

The overall best fit model is the SL9 source model with p 0 =0.2 mbar. The line wings are better modeled with such a model than with an IDP source model, which gives too broad wings. Moreover, the model satisfies the constrains derived from CO deposition observations and is close to the H 2 O column density as measured by ISO.

This results tends to confirm the ISO conclusions on the origin of water in the stratosphere of Jupiter. However, these results must be confirmed by re-analysing the SWAS data with the same model and trying to reproduce the ISO lines as well. Though, the signal to noise ratio is insufficient to firmly conclude in favor of the SL9 source when only considering the Odin data. Further observations with Odin as well as observations with Herschel would be very valuable with regards to answering the question of the origin of water in the stratosphere of Jupiter.

Fig. 1 .

 1 Fig. 1. Odin observations of Jupiter at the H2O (110-101) line frequency of November 8, 2002. The observed antenna temperature is displayed as a function of velocity.

Fig. 2 .

 2 Fig. 2. SL9 source vertical profiles of water at the time of the SL9 impacts (07/1994) in solid line and at the time of the Odin observations (11/2002) in dashed lines. The evolution of water abundance is computed by the photochemical model. The water vapor mixing ratio is displayed as a function of atmospheric pressure. Profiles correspond to a fixed value of p0=0.2 mbar, and an adjusted value of q0=1.5 10 -7