domain: math info

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Elisabeta Vergu

Sébastien Ballesteros

Anton Camacho

Caroline C Bidot

Bernard Cazelles

Stochastic metapopulation modeling of multi-strain influenza dynamics

published or not. The documents may come   L'archive ouverte pluridisciplinaire

Here we aim at providing a general framework capturing the dynamics of co-circulating influenza subtypes and to characterize replacement and co-existence conditions. We propose a time-continuous metapopulation stochastic model for three co-circulating subtypes incorporating three key processes of influenza dynamics: antigenic drift, seasonal forcing in transmission and temporary full cross-immunity. The model realism is enhanced by considering three age-classes with specific contact rates based on data. The network underlying the metapopulation structure comprises major cities in the world coupled through real passengers flows. The impact of key determinants (basic reproductive ratio -R0, antigenic drift rate, and seasonality) was explored through computer-intensive simulations based on parameters consistent with recent estimations. For realistic mean antigenic drift rates, resident subtypes can be replaced even by a new virus with a smaller R0. When R0=1.5 for all subtypes and assuming a strong seasonality, the probability of replacement tends to 1 for a rapidly evolving new subtype whatever the value of the antigenic drift rate for the resident subtypes. Co-existence of the three subtypes can be obtained for plausible ranges of parameter values. Besides the interpretation of the replacement or coexistence in terms of R0 and antigenic drift rate, our approach highlights the need of additional hypotheses on mechanisms avoiding the extinction of a new strain introduced in a system with two strains at equilibrium.

  14h15 -15h15 : Elisabeta Vergu INRA -Jouy en Josas, elisabeta.vergu@jouy.inra.fr Stochastic metapopulation modeling of multi-strain influenza dynamics Elisabeta Vergua a , Sébastien Ballesteros b , Anton Camacho c,d , Caroline Bidot a , Bernard Cazelles c,d a INRA -MIA UR341, Jouy-en-Josas, France b Ecology and Evolutionary Biology Department, Princeton University, USA c Ecole Normale Supérieure -UMR 7625, Paris, France d UPMC, Paris, France.


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Sistemi agroalimentari localizzati / Localised Agri-Food Systems

Sommario

La parte monografica di questo numero della rivista presenta contributi che affrontano il tema delle agglomerazioni produttive con particolare riguardo all'agroindustria. José Muchnik ripercorre le tappe che hanno portato alla concettualizzazione dei sistemi agroalimentari localizzati (SIAL), alla loro evoluzione come strumento teorico e di politica di sviluppo locale, mostrando la varietà di situazioni nelle quali il concetto di SIAL può operare. Henri Jesús Piña Zambrano esamina criticamente il quadro teorico delle agglomerazioni produttive come strumento metodologico per analizzare la proposta dei SIAL e derivarne gli elementi fondamentali necessari per promuoverne la formazione. Per fornire evidenza empirica all'analisi teorica si avvale di tre studi di caso condotti rispettivamente in Venezuela, Messico e Colombia. Le variabili analizzate sono: la prossimità geografica, la configurazione delle reti, l'innovazione tecnologica e l'ambiente istituzionale. Gonzalo Rodríguez-Borray avanza una proposta metodologia per la valutazione della multifunzionalità dei SIAL, verificata empiricamente attraverso uno studio condotto su tre agglomerazioni agroindustriali rurali specializzate nella produzione di panela in Colombia. Nella sezione studi e ricerche, Rafael Boix e Yancy Vaillant presentano uno studio sull'individuazione dei distretti rurali in Italia e Spagna in chiave comparata, forti della possibilità di utilizzare la stessa unità territoriale di analisi per entrambi i paesi, cioè i sistemi locali del lavoro; mentre Magdalena Barros Nock e Daniel Díaz Juárez analizzano la partecipazione politica dei messicano


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A first analysis of the central carbon pathway of Bacillus subtilis: Integration of both genetic and enzymatic levels in regulations

A first analysis of the central carbon pathway of Bacillus subtilis: Integration of both genetic and enzymatic levels in regulations

Anne Goelzer and Vincent Fromion

A challenging problem in systems biology consists in understanding the regulation and the global coordination of metabolic pathways of bacteria in response to environmental changes, at the cell scale.

Recently we identified the main regulation structures of metabolic pathways through the manually curated reconstruction of the regulatory networks of Bacillus subtilis [START_REF] Goelzer | Reconstruction and analysis of the genetic and metabolic regulatory networks of the central metabolism of Bacillus subtilis[END_REF]. We noticed a strong interplay between the metabolic pathways and the genetic regulations: 13% of 456 metabolites are involved in genetic regulations and 53% of the genes involved in metabolic pathways are directly regulated by a genetic regulator under the control of a metabolite. Surprisingly, few studies centred on metabolic pathways have considered this coupling between the genetic and metabolic regulatory networks [START_REF] Tyson | The dynamics of feedback control circuits in biochemical pathways[END_REF][START_REF] Santillan | Dynamic behavior in mathematical models of the tryptophan operon[END_REF]. Using a mathematical dynamic model, we illustrate the necessity of integrating both genetic and metabolic regulations, through the study of glycolysis, during exponential growth on glucose. Some interesting results are presented in this talk:  Identification of the key steps of glycolysis,  Identification of the key metabolites which determine the pathway behaviour,  Prediction of the behaviour of the enzymes and metabolites concentrations, of the fluxes and validation in simulation,  The respective role of genetic and enzymatic regulations.

  Goelzer, Vincent Fromion To cite this version: Anne Goelzer, Vincent Fromion. A first analysis of the central carbon pathway of Bacillus subtilis: Integration of both genetic and enzymatic levels in regulations. BACELL 2008, Mar 2008, Oslo, Norway. 1 p. hal-02811611


text:
Eduardo Chia
email: eduardo.chia@cirad.fr

Syndhia Mathé
email: mathe.syndhia@univ-montp1.fr

Hélène Rey-Valette

Facilitating Sustainable Innovations: Sustainable Innovation as a Tool for Regional Development

Keywords:

Based on the assumption that innovation is a social construction which can only result from a simple scientific injunction or proposition, this article emphasizes the significance of organizational innovations in relation to sustainable development. Innovation requires a structuring framework for organizing actor participation, i.e. the interactions between multiple stakeholders including researchers. The methodological protocol described and employed for the co-construction of indicators concerns the implementation of sustainable development indicators in fish farming. After recalling the epistemological foundations of their approach to innovation, the authors describe the structure and interest of the methodological protocol that they have developed in the second section. This protocol is used for facilitating the appropriation of a new reference system by integrating actors' representations. Furthermore, it is organized according to an interrelation pattern: principles, criteria and indicators. This approach enables indicators to be constructed based on criteria, which themselves are defined by principles. These principles account for actors' representations and issues. The application of this approach involves an individual selection phase of principles and criteria and then the collective approval by stakeholders. Its application to pilot sites has enabled to draw up a reference check list including 17 principles, which are then broken down into criteria and indicators. It can then be recomposed and adapted infinitely according to the characteristic needs and expectations of each application. The implementation of this check list therefore represents, for users, an intermediate object facilitating co-construction. The third section proposes an illustration of the procedures employed for its implementation in diversified aquaculture systems. The authors detail the results for Mediterranean fishfarming by showing that the approach can be used for comparing viewpoints and for generating the emergence of compromises around common principles and criteria. Lastly, the authors list the simple and double loop learning processes which were used during the experimentation of the approach.

Introduction

Innovation has become a major issue in our societies. It applies to firms which must innovate, today, more than in the past, if they want to maintain their position and take over market shares, etc. It also acts as a collective process, particularly for satisfying the new requirements of our Society regarding the protection of natural resources or sustainable development. Innovation is not a simple technical modification or the introduction of a new technique, it is socio-technical and organizational. Since several years, different disciplines (Sociology, Economics, Management Sciences) have studied innovations as socio-technical phenomena [START_REF] Flichy | L'innovation technique: récents développements en sciences sociales, vers une nouvelle théorie de l'innovation[END_REF][START_REF] Akrich | A quoi tient le succès des innovations ? Gérer et comprendre[END_REF][START_REF] David | Structure et dynamique des innovations managériales[END_REF]. [START_REF] David | Structure et dynamique des innovations managériales[END_REF] proposes (based on [START_REF] Hatchuel | L'expert et le système. Gestion des savoirs et métamorphose des acteurs dans l'entreprise industrielle[END_REF] to analyze organizational innovations based on an interacting 3D grid: i) technical substrate, ii) managing philosophy and iii) simplified vision of the organization. The aim is to understand how actors view innovations as well as the role played by research in this process. During the implementation of sustainable development indicators in aquaculture, we have developed an approach for associating stakeholders to the definition of sustainable development principles and criteria so that appropriate indicator systems are determined by the actors. We believe that in order to implement sustainable development at a local level, a majority of actors must be involved in the process of defining future actions, i.e. implementing a common project and language in order to co-design innovations. Producing socio-technical or organization innovations requires plans enabling or facilitating learning processes, which are both individual and collective, but also technical and organizational.

The purpose of this article is to describe the method that we have developed and which has been used for writing a guide for the co-construction of sustainable development indicators in fishfarming. The first part will include a description of the co-construction approach based on the reference context that has been chosen for organizing actor participation in the definition of aquaculture sustainable development indicators. The methodological protocol is structured so as to define indicators based on criteria which themselves are determined from principles accounting for actors' issues and representations. The connection between principles, criteria and indicators is used by actors involved in the approach not only for exploring the possibilities for elaborating a future project, but also for exploring possible options. This construction based on a "Principles, Criteria and Indicators" (PCI) system represents the main type of organizational innovation in the sense that it is used for constructing a structuring framework for organizing the participation process. Over the mean-term, this innovation conditions the emergence of other innovations, which necessarily involve the implementation of sustainable development. Our approach is based on the following assumption: sustainable development does not just concern individuals and is not the outcome of individual actions as it requires an organized and collective action carried out by actors and not individuals. Whilst the second part of this article presents the results from the experimental application of this approach on one of the study sites i.e. the Mediterranean, in the conclusion, we attempt to explore the complex relationships existing between innovation and the learning process by underlining the significance of implementing organizational innovations in aim of facilitating socio-technical innovations.

I.-Co-design based on a participation structuring framework

In relation to this aquaculture sustainable development indicator elaboration project1 , we have implemented a methodological protocol based on the assumption that co-construction enables actors to adapt rules more easily and facilitates the appropriation of sustainable development. It will be easier for actors to familiarize themselves with co-constructed rules as they will be using part or all of their justification system in these rules. On the basis of this assumption, we propose a methodological protocol which focuses on the representations of local actors and stakeholders (producers, others actors from aquaculture sector and institutional actors) and on a systemic approach involving three components: production systems, control systems and the territory.

Representations have been studied through very open face-to-face surveys on how actors view their current activity, sustainable development and the changes related to its implementation. These surveys were conducted on five study sites (the Philippines, Cameroon, Indonesia, Cyprus and France) which are representative of various technical systems (cages, pools, ponds), territorial typologies (littoral or rural territories) as well as of control systems and degrees (informal or formal as well as slightly or extremely demanding). The textual analysis of the interviews enabled to identify key questions related to the main sustainable development issues such as viewed by aquaculture system actors. 17 major issues were identified overall for stakeholder actors (see Table 1).

Prompted by our methodological approach, we based our analysis on the identification of issues close to actors' representations and not on traditional sustainable development pillars. This type of approach, which has been favoured since several years in relation to the local implementation of sustainable development, enables to take into account the integrated character of sustainable development. Bilateral or multilateral interactions between social, economic, environmental and institutional components are accounted for via a transversal design of choices made by Society. It is then possible a posteriori, once issues have been identified, to classify them per pillar according to their characteristics so as to respect the balance of relative weights between the four key principles of sustainable development (Table 1). Based on surveys, the study of aquaculture systems (production systems, control systems and interactions with the territory) has enabled to establish a connection between issues and current practices and therefore to provide action strength to identified issues. This relationship between the "wishes" expressed for the future by actors and their action potential has been represented by using the principles, criteria, indicators method (PCI method). This method is used for establishing a connection between issues, actions and positioning. Criteria represent an intermediate level between principles and indicators, which concerns programming and action in the different sustainable development dimensions. Positioning is provided by actors to indicators as it enables them to become aware of the distance separating reality from the objectives that have set themselves via the issues they have revealed. In this sense, indicators represent a planning system. By using these tools, actors agree on what is to be done and how to do it. In this method, due to the relationship described above, issues are obviously going to be the determining components for criteria and indicators, i.e. for the actions which will be conducted and their follow-up. However, issues vary over time i.e. they will become more or less significant and new issues will appear. Thus, sustainable development is defined by Marmont (1999) as the formulation of a project through negotiations and dialogue, a project which is continuously reformulated due to the unstable character of issues and relationships existing between actors. Consequently, the ranking of PCIs will be renewed over a more or less long period. It is recalled that as PCIs have generated the implementation of an observation system for monitoring the progress of sustainable development objectives, it is necessary to ensure indicator durability for this follow-up to be operational and relevant. Sustainable development is a long-term process and the methods enabling its appropriation by actors are progressive. These PCIs can be considered as intermediate objects [START_REF] Vinck | Les objets intermédiaires dans les réseaux de coopération scientifique. Contribution à la prise en compte des objets dans les dynamiques sociales[END_REF] which will be used by actors for discussing and building a common sustainable development reality.

Table 1: Different learning processes based on co-construction approach

Participation to this approach generally involves organizational innovations. Traditionally, actors, particularly those from the productive sector, have a horizontal vision of their activity i.e. a "system-based" vision in which their concerns are mainly related to suppliers (feed and fry) and customers (wholesalers and retailers). This vision will become broader because regulations for production and its environment (ecological and socio-economic) play an increasingly significant role in production strategies. Producers must respect international and local regulations concerning water use (Water law in France and Europe), site selection (ICPE2 rules in France), environmental protection (law of the 5th of August 1996 regarding Environmental Management in Cameroon), exports (The Export Development Act and The Fisheries Code in the Philippines), food safety (HACCP3 principles) and the local development strategy (rural code in France, competitiveness pole policies). Producers will need to widen their operating scope and adopt a territorial vision of their activity including the regulatory system4 , social community (civil society, users and local networks) and the ecosystem in which they are positioned, particularly the impact of their activity on the services ensured by this ecosystem. Management rules and procedures to be respected in fishfarming are constructed within regulatory systems by decision-making structures, which very often have very little connection with the productive sphere. The actors from these systems typically have a very administrative (vertical) vision of the sector and aim to answer global objectives which are not always compatible with the true onsite situation. However, due to the "participation" component in sustainable development, co-constructing objectives and rules related to territorial development is recommended so as to compensate for dysfunctions between scales and actor profiles. Thus, organizing an advisory panel between actors from the territory seems to be a solution enabling each person to be informed of individual constraints and objectives. This discussion structure refers to the eco-citizen participation model (Claeys-Mekdade, 2006) which acts as an interface between decisionmakers and militants. Only, coordination within this structure is not easy as it requires an effective organization of actor systems, which involves informal discussions, negotiations and concerted decision-making [START_REF] Billé | Gestion des zones côtières : quatre illusions bien ancrées[END_REF]. Using PCIs as a discussion object within this structure is a solution for coordinating actors in an effective manner. Actors will be able to familiarize themselves with the PCIs by using the shifting, adaptation, extension and diversion strategies of this object [START_REF] Akrich | Les utilisateurs acteur de l'innovation[END_REF]. Thus, they will contribute to organizing the discussion structure and represent an "extra-social" means [START_REF] Strum | Redéfinir le lien social : des babouins aux humains[END_REF]) which, combined with the discussion, will facilitate coordination. Following this coordination phase, actors from the production sphere, control system and social community will be able to develop a transversal vision, i.e. they will be able to take into account all of the elements from the system (aquaculture systems) of which they are part when making a decision. When a fishfarmer produces fish or when an institutional official legislates, they are both aware that they are each creating a more or less coordinated collective action [START_REF] Callon | Sociologie de l'acteur réseau[END_REF]) in the aquaculture system. In this sense, implementing an approach structured by the PCIs is an organizational innovation as it can not only be used for controlling actions but also for exploring new options, for (re)-defining objectives and for agreeing on what has to be achieved (action guide and operation) for implementing sustainable development.

II.-Results: Facilitating the construction of a common project in relation to sustainable development

In this section, we will present the main and immediate outcome of our approach when applied on the five study sites .i.e. the principle and criteria choices made by actors from the aquaculture systems of the five study sites. A criteria and indicator check list has been drawn up based on issues and representations. This list is therefore a general list in which, according to local situations, actors from each aquaculture system can discuss and select a reduced list of principles, criteria and indicators representing local expectations and their vision of sustainable development. This procedure has been carried out in two phases. Firstly, principles and criteria are ranked, and secondly, the new list with selected principles and criteria is approved.

In the first phase, actors identify principles and rank all criteria according to a qualitative graduation from "priority" to "secondary" including a "to be included later" comment. Thus, actors can express the value judgement that they have regarding the notion of sustainable development in aquaculture. This phase concerns the individual choices made by the actors so that they are not affected by strength or power conflicts between the different actors and provides interesting results concerning the choices made by actors regarding principles. Individual results have be aggregated by distinguishing two sub-groups: actors belonging to the productive sector (producers and the others actors from aquaculture sector) and actors which do not belong to this sector (actors related to the fishfarming environment, belonging to the control system or territory (social community)). It is then possible to confront both points of view. Results will be presented in this section for the study site in the Mediterranean area which includes fishfarming in Cyprus and in French Mediterranean areas (Provence Alpes côte d'azur and Corsica -see Diagram 1). The distribution of selected principles [START_REF] Sourget | Validation et construction d'indicateurs de durabilité de la pisciculture marine en Méditerranée. Vers une Evaluation et une Mise en place de la Durabilité de la pisciculture de bars et daurades en Méditerranée (France et Chypre)[END_REF] shows an over-representation of the technico-economic pillar for actors from the productive sector whereas other actors have made more balanced choices combining technicoeconomic, social and environmental pillars. It should be noted that interest for the social pillar is low in both cases as it is either non-existent or hardly represented. Thus, producers have given significant importance to the flexibility, adaptability and durability of firms which involves diversification as well as research and implementing innovations such as using labels or taking part in quality approaches. "Non-producers" underline the importance of the social food supply, the need for governance plans as well as the Government's participation in the implementation of sustainable development.

The second phase consists in collectively approving the PCI list prepared by aggregating individual choices. This aggregation is carried out by weighting via scores the choice classes used for the selection. In the initial phase, the aim was to provide all actors with the results for their individual choices by showing the differences observed between the sites or actor categories. This restitution then gave rise to a debate between actors which enabled to identify converging and diverging viewpoints among the actors, particularly between both categories. Following this discussion and as long as a consensus has been reached, it is then possible to collectively re-introduce (or exclude) certain principles or criteria whose significance was revealed during the discussion. Thus, this approval phase is used for defining a compromise between two major types of actors in the aquaculture system. In the case of the Mediterranean site, it is observed that the validation phase was employed for reaching a compromise which will re-balance the representation of the four pillars (see Diagram 2).

Diagram 2: Results following phase 2 (approval) in the Mediterranean area

Results obtained following the implementation of this construction approach show the advantage of its collective character in terms of actor coordination and of building a compromise based on sustainable development issues on a given territory. Criteria representing action fields have also been subject to an individual selection by actors (according to the principles to which they are connected). They have often been used, which is also the case for indicators, during the individual selection or in the discussion of the collective approval phase for illustrating the usefulness or meaning of the principles. Collective discussions have shown that actors gave much more attention to principles and indicators than to criteria. The criteria and indicators were then finally selected by researchers so as to balance criteria per principle and to account for information availability.

Lastly, as regards results over a longer term related to the learning processes enabled by this co-construction approach, we can attempt to list a few examples of situations and/or objects which have been part of a learning process characterized as individual or collective according to Agyris and Schön, (1996), i.e. according to whether they are used for modifying the practices (simple loop learning process) and objectives (double loop learning process) of actors. Table 2 lists the main fields and subjects for which learning processes have been completed (see Table 2).

Conclusion

The co-construction method for sustainable development indicators in aquaculture is used for including actors in the definition or listing at a local scale of sustainable development principles, which can thus facilitate their appropriation by actors. It offers an operational framework which fulfils participation objectives supported by sustainable development and thus facilitates its appropriation (materialization process) as an organizational and institutional innovation. In actual fact, sustainable development imposes major changes both individually for fishfarms, as well as collectively regarding the changed reference system and representations within a group of actors which tends to increase in size due to the emergence of new actors involved in sustainable development. Thus, the learning process must be based on a double loop principle involving appropriate and progressive support structures with respect to current actors' representations. This involves institutional changes at the level of territorial governance structures. In this innovation approach framework (in which the social character becomes central), the multiple and complex relationships existing between innovation and learning are to be examined. This domain is a main topic in the problems encountered in Management Sciences, particularly regarding the co-construction process or more generally concerning research and partnership positions and organizations determining the implementation of these processes.

Thus, this article has described how the co-construction protocol for sustainable development indicators has been constructed with actors, according to participation and association structures according to the research phases. The principle criteria and indicator system on which is based the construction of the approach represents an organizational innovation according to [START_REF] David | Structure et dynamique des innovations managériales[END_REF]. We can, in actual fact, consider that we have jointly mobilized the three components identified by David for the innovation process, i.e. technical substrates (tools, models, references, representation analysis, etc.), a management philosophy (in our case, the assumption according to which the effective implementation of sustainable development requires a cooperation strategy via a co-construction approach) and lastly a simplified vision of organizational relationships (in this case, the organization of individual and collective relationships around the selection and approval of principles and criteria). This type of approach is used for connecting indicators and interacting individual, collective and scientific knowledge. The major role played by institutional conditions and innovations should however be noted for achieving this type of innovation as it can only be developed and operated if structures, which facilitate the learning process and transform knowledge into local useable know-how [START_REF] Avenier | La communication des savoirs actionnables à diverses communautés de praticiens : chaînon souvent manquant dans la recherche[END_REF], have been implemented.

  the capacity for dealing with uncertainties and crises P8-Reinforcing the durability of facilities P13-Developing plans for quality, certification and traceability labelling approaches in aim of reinforcing product quality P16-Respecting animal welfare and health 4 Environnemental pillar P2-Ensuring the protection of natural resources P3-Improving the ecological yield of the activity P4-Maintaining and valorizing biodiversity P5-Adapting the activity to the environment carrying capacity 4 Social pillar P1-Contributing to the food supply of societies P9-Reinforcing the professional identity of fish farmers P10-Reinforcing the social investment of aquaculture firms (working conditions, quality of life, etc.) P11-Contributing to the reinforcement of social relationships and social cohesion P12-Contributing to the creation of economic activities for reducing poverty (associated sector and system) 5 Institutional pillar P6-Promoting aquaculture as a national planning component P14-Implementing incentive institutional plans enabling the participation of fish farmers and stakeholders in aim of improving regulations P15-Reinforcing research and information related to this sector P17-Reinforcing the effective role of the Government in the implementation of sustainable development 4

Diagram 1 :

 1 Results from phase 1 per actor profile in the Mediterranean region

  Table2: Illustration of learning processes created by the co-construction structure

This research project is part of the Agriculture and Sustainable Development Federating Program funded by the National Research Agency (ADD-ANR). It associates 5 research institutions (Cirad, Ifremer, Inra, IRD and the University of Montpellier 1) and mobilizes a multi-disciplinary team of fifteen researchers).

Facility Classified for the Environment

Hazard Analysis Critical Control Point

"All management procedures (« which combine management measures and the institutions in charge of their implementation and control ) affecting one or several productive systems in interaction"[START_REF] Rey | Système Halieutique. Un regard différent sur les pêches[END_REF]

Acknowledgements

The authors would like to acknowledge Sourget QUITERIE for her research on fishfarming in Cyprus and in French Mediterranean areas (Provence Alpes côte d'azur and Corsica).


Sandra Said
email: said@supagro.inra.fr

Sophie Thoyer
email: thoyer@supagro.inra.fr

Agri-environmental auctions: choosing the farm area put under contract

Keywords: Agri-environment, multiple unit auctions, multi-criteria index JEL: Q58, H23, C0

Introduction

Agri-environment schemes were introduced into the Common agricultural policy (CAP) during the late 1980s as a financial instrument to encourage more environmentally-friendly farming practices. After implementation of Agenda 2000, European budgets dedicated to agrienvironmental payments (co-financed by the EU and national states) were increased significantly: in the 2000-2006 programming period, they amounted to 13.5 billion € and the share of European agricultural land enrolled in agri-environmental contracts had reached 25% in 2005 (CE, 2005). The allocation mechanism -although variable from one member State to another -is based on the following rule: farmers can choose, on a voluntary basis, to commit themselves for a given period to adopt environmentally-friendly farming techniques on their private land. They sign up for a tailored contract which includes a number of relevant measures chosen amongst a large menu (measures such as extensification practices, management of low intensity pasture systems, preservation of habitats and biodiversity, adoption of organic farming etc) and they receive in return payments that are estimated so as to compensate them for additional costs and loss of income (thereafter cost of compliance) arising from their new farming practices.

Such payments often represent a non negligible -and secure-source of farm income and have contributed to maintain farming in less favourable areas. It is a fact that agrienvironmental policies have often been used by member States to supplement farm income, in a way which was compatible with the decoupling requirements of the World Trade Organization. Although supervised by Brussels, allocation rules vary from one member State to another, often reflecting the relative weights that national decision-makers give to genuine environmental concerns and to income-support objectives. This ambiguity about the true objectives of agri-environmental scheme explains partly the disheartened evaluation conducted by the EC (CE, 2005;Primdahl et al, 2003) which pointed out the insufficient environmental outcomes of agri-environmental payments. The EC diagnostic was that disappointing outcomes resulted from ill-designed measures, dispersion of efforts as well as multiple "windfall effects" (farmers being paid for what they were already doing or for what they would have done anyway).

Following an audit of the European Court of Auditors, the EC has made a formal statement to recommend that agri-environmental schemes include quantifiable objectives, be more cost-effective, and to strongly encourage member States to adopt competitive bidding in the allocation process. This last recommendation is quite revolutionary in the European context since the mechanism used so far is based on a menu of regional measures which does not allow to overcome satisfactorily the asymmetries of information on true compliance costs. On the other hand, it is useful to select priority zones and priority actions and to target specific categories of farmers in need of income support. An important question for the European regulator is therefore the design of a competitive bidding process, which could target farmers able to supply greater environmental benefits -as a joint product of farming activities -at a lower cost for society.

There exists already a vast empirical (mainly based on the US and Australian experience) and theoretical literature on agri-environmental auctions (see Latacz-Lohmann et Schilizzi, 2007 for a review). Theoretical models, inspired by the US Conservation Reserve Program and by the pioneering work of Latacz-Lohmann et [START_REF] Latacz-Lohmann | Auctioning conservation contracts : a theoretical analysis and an application[END_REF], demonstrate that sealed bid auctions lead to greater efficiency and lower budgetary expenditures than fixed price schemes. Since such auctions are often multidimensional (the regulator seeks multiple environmental outcomes), [START_REF] Johansson | Indices for working land conservation: Form affects functions[END_REF][START_REF] Johansson | Indices for working land conservation: Form affects functions[END_REF] and Cattaneo, Lankoski and Ollikainen (2007) analyse how to design a ranking index aggregating the different dimensions of bids. However, all these models make the simplifying assumption that farmers only bid for one unit of land, therefore overlooking the effects of enrolling a larger proportion of farmland both on total costs (due to economies or diseconomies of scale in compliance costs) and on total environmental benefits (due to either increasing marginal benefits or decreasing marginal benefits). This paper bridges this gap in the literature. We design a "green" auction in which the regulator imposes a given set of management practices. Farmers are invited to make a unique bid on the number of ha of their farmland they wish to put under contract and on the compensatory payment they wish to get. This is the most likely auction scenario that could be developed in Europe: although the Australian authorities have tried to be more innovative by allowing farmers to bid also on the technologies and practices they adopt (see the BushTender pilot study studied by Stoneham et al, 2003, Casan andGangadharan, 2004), it is much less costly to implement and monitor an auction with a pre-determined level of environmental effort per ha. This paper is organised as follows: in the first section, we use the Latacz-Lohmann and Van Der Hamsvoort's resolution (1997), based on decision theory rather than on game theory, to calculate optimal bidding strategies. In section 2 we demonstrate that the optimal bidding on the area put under contract depends on the structure of environmental gains and compliance costs (section 2). In section 3, we demonstrate that, under certain conditions, imposing stricter management practices can induce farmers to put a greater share of their farmland under contract. Another difficulty for the designer of an auction is to decide on the safeguard rules regarding the payments received by each farmer: in particular, it is likely that a maximum payment per farm will be imposed. Such rule exists in the US Conservation Reserve Program as well as in most agri-environmental schemes in Europe, mainly for equity reasons although it can alter the efficiency of the green auction. In section 4, we conduct numerical simulations to illustrate the impact of two maximum payment rules, an egalitarian rule (the same maximum payment for all per exploitation) and a proportional rule (a maximum payment proportional to farm size). Section 5 concludes.

The auction

We assume that public authorities announce an agri-environmental scheme in order to manage a specific environmental issue associated with farming practices. For example, the regulator wishes to limit soil and water pollution by pesticides in a cereal farming region. A given set of technical measures is prescribed such as: the quantities and types of pesticides recommended for each crop, the frequency of use, the establishment of buffer strips between fields and waterways. Farmers are then invited to participate in an auction in which they bid on the surface area they agree to include in the scheme and on the compensatory payment they wish to obtain as a compensation for compliance. The auction is a sealed bid multiple contract procurement auction with a discriminatory payment rule: winning farmers get the payment they have bid. Therefore, each participating farmer i submits a unique sealed bid with two dimensions ( )

, i i i b n r -i
n denotes the number of hectares on which farmer i is willing to adopt the recommended technical measures, described as a fixed environmental effort e per hectare.

i r denotes the level of agri-environmental payment per unit of hectare and per unit of environmental effort e that farmer i wishes to get as a compensation.

Since bids are multi-dimensional, the challenge for the decision-maker is to design a scoring function capable of aggregating the various benefits embodied in the farmer's bid into a single index used to rank bids. Indices are then ranked from highest to lowest and the decisionmaker allocates the contracts to farmers with the highest indices, with a cut-off rule which is either defined by a budget constraint or by a target constraint (e.g. the surface under contract or the total environmental gain). Each winning farmer i then signs a contract, in which he commits himself to provide environmental effort e on area i n of his farmland in return for a total compensatory payment * * i i r e n . Farmers who have not won any contracts do not have to provide efforts and get paid nothing. We assume that there is no moral hazard: farmers' actions are observable and can be monitored. However, the regulator cannot observe farmers' types in terms of compliance costs.

We assume that farmers are risk neutral and that they have private information about their farm profits and their compliance costs. A farmer i will bid ( )

, i i i b n
  = + - + -   -i
π is the total farm profit when no environmental effort is provided -( )

, i i
C e n is the total cost of providing environmental effort e on area i n . We assume that these compliance costs increase with the level of environmental effort and with the area under contract.

( )

, 0

i i i n i C e n C n ∂ = > ∂ and ( ) , 0 i i i e C e n C e

∂ = > ∂

prob denotes the probability of winning the auction.

The bid's score

The probability of winning the auction depends on the rank of the farmer's bid. Following Cattaneo ( 2006), we establish an additively separable scoring rule ( )

m a x m a x , * * 1 i i i i i P P i e d g e n r n e I w e w w G M   = + + -     (1) with:
-

[ ] 0,1 pi e ∈
denotes the priority score given to the area in which the farmer i is located. We assume here that the decision-maker can decide to give greater priority to Natura 2000 areas or/and to environmentally vulnerable zones. For land which is less vulnerable to pollutions or which is already degraded, pi e is close to 0. For land which requires greater protection, for example because it displays high value threatened biodiversity, or there is a vulnerable aquifer, pi e is closer to 1. It is therefore an exogenous measure of environmental gain, associated with the location of bidder's land. It is common knowledge. Alternatively, pi e can be mobilized to indicate the priority given to certain types of farmers (low revenue, young farmers) or to certain types of farming activities.

-( )

, i i
g e n is the function of environmental gain for farmer i . It measures the environmental benefit to society of producing the environmental effort * i n e . It could be measured by the reduction of toxic molecules accumulating in soils and leaching into aquifers and rivers. We assume that environmental gain is quantifiable at the level of each farm. In practice, it is often difficult to measure the score adequately but the decision-maker can build his own environmental benefit score. We assume here that the environmental benefit can be measured as a function of n and e, and that it increases when more hectares are contracted, or/and when the environmental effort per hectare is greater:

( ) , 0 i i i n i g e n g n ∂ = > ∂ and ( ) , 0 i i i e g e n g e ∂ = > ∂ - max G
denotes the maximum environmental gain which can be provided by a single farm. It is the same for all farms and depends on the fixed environmental effort e .

The environmental gain component

( ) max , 0 1 i i g e n G ≤ ≤
helps the decision-maker to assess the level of environmental contribution by each farmer compared to the maximum level attainable.

max

M

is the maximum payment per farm. g e n r n e , the score will be greater for the farmer requiring the lowest payment. Such index reflects well the policy pursued by most decision-makers in Europe: to ensure that environmental payments, often used also as income support, are accessible to a large proportion of eligible farmers.

Each farmer can calculate privately his score because he knows his costs, his environmental gain function and weights are common information. His bid is accepted provided his score is greater than the cut-off value c I . The cut-off score is computed by decision-makers after all bids have been submitted. If it is a target auction in which public authorities want to allocate k contracts, then c I is the score of the k th farmer accepted in the scheme (that is the value of the n th score when ranked from the highest to the lowest). It is more likely that the auction is in fact limited by a maximum budget. In such case, c I is the score of the last winning farmer once the whole planned budget has been allocated to winning contracts. It is important to note here that the total expenditure is measured by * * j j j r e n ∑ for the j th winning farmers.

The probability to win

Following Latacz-Lohmann and [START_REF] Latacz-Lohmann | Auctioning conservation contracts : a theoretical analysis and an application[END_REF], we assume that each bidder, although he cannot know c I or the score j I of other bidders j, forms expectations about their distribution. Let's call ( ) f I the density function of this distribution and I the score value under which the bidder's expectation to win is zero. The probability Prob of being accepted in the auction is the probability that the score i I for farmer i is superior to the cut-off value score c I :

( ) ( ) ( ) i I i c I prob P I I f I dI F I = > = =

∫

If we assume that farmers expect I to be uniformly distributed between I and I (the score above which the farmer's expectation to win is 1) , then the cumulative distribution function

( )

F I can be written:

( ) 0 i f i f , 1 i f I I I I F I I I I I I I I     -     = ∈     -       p f For example if 0 I = , 1 I = then ( ) F I I = .
It indicates that bidders are very uncertain about the outcome of the auction. We can expect however that if the auction was repeated several times over the years, farmers would get an opportunity to learn more about the score value of other bidders and would therefore form a narrower range of expectations for I and I .

Properties of optimal bidding strategies

The farmer chooses * i r and * i n to maximize his expected profit ( )

EP ( ) ( ) ( ) ( ) ( ) ( ) * * , * * 1 * * , * i i i i i i i i i i i EP r e n C e n F I F I r e n C e n F I π π π     = + - + - = - +    
subject to a number of constraints on decision variables: i n must be positive and inferior to his total farm area max i n , and the level of agri-environmental payment that he wishes to get * i i r n must be positive and inferior to the maximum allowed payment per farm max M .

The bidder is individually-rational if he is better-off when winning the auction than when not winning: The individual rationality constraint (RC) or participation constraint can be written as:

( ) ( )

: * * , : * * , 0 i i i i i i i i i i RC r e n C e n RC r e n C e n π π + - ≥ - ≥
The optimisation programme of the bidder is therefore the following:

( ) ( ) ( ) ( ) ( ) , m ax m ax * * , 0 0 * * * , 0 i i i i i i i r n i i i i i i i i r n e C e n F I Subject to n n r n M r n e C e n M ax π - + ≤ ≤ ≤ ≤ - ≥ (2)
The Lagrangean for the problem reads as,

( )

1 2 3 4 5 1 max 2 3 max 4 5
, , , , , , * * , * * * * * ,

i i i i i i i i i i i i i i i i i L r
( ) ( ) ( ) ( ) : * * * * * , i i n i n n i i i L r e C F I F r e n C e n - = - - (3) ( ) ( ) ( )
: * * * * * , i r i r i i i L n e F I F r e n C e n = - - (4)
Where ( )

n i F I F n ∂ = ∂ and ( ) r i F I F r ∂ = ∂
Assuming that the participation constraint is strictly respected, we derive ( )

    = + -+ +     (6)
Let's write ( )

. i i n i n C K g = If ( ) . i K is reversible, then * i n is the solution of ( ) ( ) 1 i K β -
The condition for ( )

. i K
to be reversible is that it must be continuous and monotonous, then there is an unique solution to the optimisation problem ( )

* 1 i n K β - = We derive ( ) . i K with respect to i n : ( ) 2 * * i i i i i nn n n nn n i n C g C g K g - = (7)
where ( )

, i i i n i K n e K n ∂ = ∂ , ( ) 2 2 , i i i nn i g e n g n ∂ = ∂ and ( ) 2 2 , i i i nn i C e n C n ∂ = ∂
We will examine only two cases: 8 -the case when ( )

. i K is always increasing ( ) 0 i n K >
-and the case when ( )

. i K
is always decreasing ( )

0 i n K < .
In both cases, we note that In other words, farmers will increase their bid on r when the total allowed payment increases and when the weight given to environmental benefits increases. On the contrary, bids on r decline when the decision-maker is more sensitive to budget spending. When the cost function is convex and the environmental gain function is concave, a greater weight on environmental benefits or a greater maximum payment per farm induces farmers to bid a larger proportion of their farm area. On the other hand, the greater the maximum environmental gain or a greater weight on budget spending decreases the area that farmers are willing to bid. The classical case of diseconomies of scale (leading to increasing marginal costs) can be observed for example if production risks increase at a higher speed for larger areas under reduced pesticide use. At the same time, the environmental benefit function is concave, indicating that marginal environmental gains decline with the number of hectares under the scheme. This is often the case that the first units of pollution reduction yield more benefits than the following due to threshold effects in the way pollution affects water resources. With such structure for compliance costs and for environmental gains, we expect farmers to bid for relatively small proportions of their farmland. We may end up with a the allocation of many small contracts. A convex environmental gain function can be observed in the case of mammal biodiversity, when large areas of protection must be set-up to improve significantly the quality of habitats and therefore the population. A concave cost function can be observed in cases of economies of scale, for example if the new practices require to invest in equipments whose costs are more efficiently shared over a greater number of ha. We can also assume that adopting a new technology requires high learning costs for the first few ha. In such configuration, reducing the weight on environmental gains or reducing the maximum payment per farm will lead farmers to bid more hectares on the scheme, in order to be more competitive through the environmental benefits they can supply.

If the decision-makers can characterize the shape of environmental benefit and compliance cost functions, then he can choose the parameters of the auction (the weights and the maximum allowed payment) in order to induce farmers to either bid greater areas or to bid lower compensatory amounts.

The impact of effort intensity on area put under contract

The decision-maker must also make a decision on the intensity of environmental effort e that should be imposed in the auction: from the viewpoint of environmental efficiency, is it preferable to impose stricter measures inducing greater e or to encourage farmers to bid for greater area?

To respond to this question, we analyse how * i n changes with e By differentiating ( ) ( )

, i i K n e e β =
, we obtain * 0

i n e n K K e ∂ + = ∂ i i e e n n K n e K ∂ = = - ∂ (8) with ( ) 2 i i i i i nn n n nn n i n C g C g K g - = and
( )

2 i i i i i ne n n ne e i n C g C g K g - =
We will examine four cases: Sufficient conditions under which we find 0 with e when the cross derivative of compliance costs with respect to n and e is negative, and the cross derivative of the environmental gain function is positive, indicating that area and effort intensity are complement for marginal gains: when the environmental effort is stricter, marginal compliance costs of increasing the area under contract are lower and marginal environmental gains greater. Such case is illustrated by figure 1 The conclusion is that it is necessary for decision-makers to gain a clearer understanding of the shape of compliance cost and environmental gain functions in order to design an auction yielding the desired outcome in terms of the area bid by farmers.

. The choice of the maximum payment rule: numerical simulations

The analytical characterization of n* and r* shows that the maximum payment rule affects optimal bidding strategies. It is a fact that decision-makers often choose to impose such rules, although they cannot be justified on the basis of economic efficiency. It reveals that agrienvironmental schemes are also indirect ways of providing income-support and of buying political support. France has traditionally used an egalitarian rule stating that all farms are submitted to the same maximum payment per farm, notwithstanding the size of the farm. We have already indicated that such rule embodied in the index described in equation 1 favours the dispersion of payments over a greater range of farmers.

In other countries, the maximum payment per farm is proportional to farm size, allowing larger farms to get greater maximum payments than smaller ones. An index based on this rule (see equation 10) will favour the concentration of environmental payments on a smaller number of farmers.

( )

m a x m a x , * * 1 i i i i i P P i e d i g e n r n e I w e w w G M   = + + -     (10) max max * i i M r n =
is a maximum payment per farmer which depends on max i n the total farmland area of farmer i and r a fixed average payment per ha

If two farmers make identical bids, this scoring function provides a better rank to the farmer with the greatest farmland area.

We compare here the consequences of these two rules (egalitarian versus proportional) through numerical simulations using therefore two different scoring functions:

We apply thus the above model to an hypothetical auction. We build an hypothetical sample of 40 farmers characterised by max i n in a range of [30,120]. We have identified high priority area ( 0.8 We choose the properties of these functions so as to be in case one when ( )

* , i i
K e n is an increasing function 1 of n i 1 Authors have also conducted simulations for the case when K is decreasing but results are not reported here.

They will be added in the final version 13

In first time, we apply the theoretical model to the case where ( ) g n e n e n = + ).

, i i K e n
,

Figure 3: Compliance costs functions and environmental gain functions

To compare the two auctions, we calculated the equivalent fixed maximum payment by using the following rule: The social welfare 0,45 0,48

Costs

Ratio

Mmax Mmaxi

Note : Ratio is (r*n-C)/C

Table 2 shows that auction performance is greater when the fixed maximum payment rule applies. The budget return efficiency which measures the informational rent distributed to farmers (if efficiency = 100%, it means that payments exactly compensate true compliance costs) is improved in the egalitarian scenario compared to the equity scenario.

The average public expenditures per enrolled hectare as well as the average public expenditures per unit of environmental gain decreases when decision-maker selects the fixed maximum agri-environmental payment.

The social welfare ( )

 = + + -       ∑ ∑ ∑ ∑ ∑ ∑
The last line of table 2 confirms that a fixed maximum payment increases social welfare. Of course, it means that a proportional maximum payment rule would be more advantageous to farmers as a whole. But it is interesting to analyse what categories of farmers benefit more than others. Figures 3 and4 show us that the equitable scenario favours large landholders (the average of total farm area of enrolled farmers is equal to 72 ha versus 59 ha in the egalitarian case). On the one hand, a large landholder increases his environmental gain criteria by supplying more hectares, on the other hand he can bid higher r because he also benefits from a larger max i

M

. On the other hand, small landholders benefit more under the egalitarian scenario.

Conclusion

This paper provides an analysis of optimal bidding strategies when farmers are invited to bid simultaneously on compensatory payments and on the proportion of their farm area they wish to put into the agri-environmental scheme. We first demonstrate that bidding strategies can be reversed according to the convexity and concavity properties of both the environmental gain function and the cost function. It indicates that the choices made by policy-makers in terms of the scoring function and the maximum payment per farm should be guided by all information he can gather on the structure of these functions. Likewise, the paper shows that stricter management practices can under certain conditionswhen environmental effort intensity and surface are complementary -induce farmers to increase their bids on the area they wish to put into the scheme. Finally we demonstrate that a fixed maximum payment rule increases the performance of the auction, both in terms of budget returns and allocative efficiency, compared to a proportional maximum payment rule. This paper therefore provides useful insights on the way such auctions should be designed.

Bibliography

Cason T N., Gangadharan L. (2004). Auction design for voluntary conservation programs, American Journal Agricultural Economics 86, n° 5 pp 1211 -1217 [START_REF] Johansson | Indices for working land conservation: Form affects functions[END_REF] ) ( )

  various dimensions of each bid and the characteristics of the bidder in a single index value comprised between 0 and 1.

  At interior solution, the Lagrange multipliers are zero and the first order conditions are:

  costs and concave environmental gains, we observe that * i n increase

Figure 1 :

 1 Figure 1: Optimal bids on n when e increases, with complementary effects between area and effort intensity

Figure 2 :Figure 3 :

 23 Figure 2: Optimal bids on n when e increases, with substitution effects between area and effort intensity

  the Natura 2000 zoning. We use hypothetical cost and environmental gain functions. We build heterogeneity in our sample by introducing high cost function H C and low cost function L C , as well as high environmental gain function H g and low environmental gain function L g .

  of the simulations are presented in table 2.

  to compare the level of payment made to farmer i compared to the maximum authorized payment per farm.The environmental and budget components of the score illustrate the following tradeoffs: the farmer can decide to require a greater compensation but this reduces his score unless he can offer a high environmental gain (either because his environmental gain function is high or because he increases the number of ha under agri-environmental practices).

		The budget component	max * * i r n e i M	helps the
		decision-maker -, , p e d w w w reflect the weights that the decision-maker assign to priority areas,
		environmental gains and public expenditures.	p w w w e d + +	=	1
	i	, / * * i i i

I can be interpreted as a normalized weighted social welfare function made of three normalized social surplus: priority zones, environmental benefits and budget spending. Such scoring function therefore reflects the priorities of the decision-maker. It is built in a way which gives priority to specific areas or farmers, and which can give different weights to budget spending and to environmental gains. Moreover, it favours the dispersion rather than the concentration of environmental payments: for two farmers offering the same ratio ( )

Table 1 : The simulation scenarios Simulations "Proportional" "Egalitarian"

 1

					w	p						0,2			0,2
					e w						0,4			0,4
					d w						0,4			0,4
	M	max	i	=	max r n *	i	and max M	M	max	i	=	70*	max n	i	max M =	5115, 25

Table 2 : The simulation outcomes

 2

	Simulations

winner Figure 3: Distribution of net profits with respect to maximum farm size under equitable and egalitarian maximum payment rules

		12,00
		10,00
		8,00
	Ratio	6,00
		4,00
		2,00
		0,00
		0	20	40	60	80	100	120	140
					nmaxi
					Mmax Mmaxi
	Figure 4:

(*) the budget is 78 000 for the two but spending might be a bit over or under this amount according to the bid of the last

Distribution of net profits with respect to costs under equitable and egalitarian maximum payment rules

	12.00
	10.00
	8.00
	6.00
	4.00
	2.00
	0.00
	0.00	100.00	200.00	300.00	400.00	500.00	600.00	700.00	800.00	900.00

  SW can be measured by the weighted sum of different criteria:

	S W	w	P	e n r o l e n r o l e	P i i	w	e	e n r o l e n r o l g	i g	( i	( , e n m a x ) , i i e n	)	w	d	 	1	e n r o l e n r o l r	i	* M	m a x * i i n	e	

  . Auctioning conservation payments using environmental indices, Contributed paper to the International Association of Agricultural Economists Conference, Gold Coast, Australia, 12-18 August 2006, 17 p Cattaneo A., Lankoski J., Ollikainen M. (2007) Green auctions with joint environmental benefits. Environmental Economics. University of Helsinki, Department of Economics and Management. Discussion Paper N° 19. Environmental Economics. EC European Commision (2005). Agri-environment measures, overview on general principles, types of measures and application, Directorate general for agriculture and rural development, Unit G-4 Evaluation of mesures applied to agriculture, studies. Mars 2005, 24 p

	i	* *	i	i	i	, *
		p	*	p	e	*	i	*	i	max ,	i	d	* 1	max * *	i	i

Appendix

Sign of the determinant of the Hessian matrix:


Pour mémoire ACTA, le réseau des instituts des filières animales et végétales, ce sont :

-16 instituts techniques agricoles qualifiés dont une tête de réseau. -Les outils professionnels de recherche appliquée et de transfert technologique au service des filières agricoles.

-Une forte présence sur le territoire national avec près de 200 implantations en région.

-Une force de 1100 ingénieurs et techniciens. -Un budget de 168 millions d'euros en 2007 dédiés à la recherche agricole appliquée.

Modeling for decision support and modeling for impact assessment. How do the modeling projects differ?

••

  ACTA, coordinator and representative of the technical institutes of agricultural sectors Applied plant research ARVALIS -Institut du végétal CETIOM, Centre Technique Interprofessionnel des Oléagineux Métropolitains CTIFL, Centre Technique Interprofessionnel des Fruits et Légumes IFV, Institut Français de la Vigne et du Vin AGPH, Association des Producteurs de Houblons de France ANIFELT, Association Nationale Interprofessionnelle des Fruits et Légumes Transformés ANITTA, Association Nationale Interprofessionnelle Technique du Tabac ARTB, Association de Recherche Technique Betteravière ASTREDHOR, Association Nationale des Structures d'Expérimentation et de Démonstration en Horticulture IDF, Institut pour le Développement Forestier IFPC, Institut Français des Productions Cidricoles ITAB, Institut Technique de l'Agriculture Biologique ITB, Institut Technique Français de la Betterave Industrielle ITEIPMAI, Institut Technique Interprofessionnel des Plantes à Parfum, Médicinales et Aromatiques ITL, Institut Européen du Lin UNIP, Union Nationale Interprofessionnelle des Plantes Riches en Protéines Applied animal research INSTITUT DE L'ELEVAGE IFIP, Institut du Porc ITAVI, Institut Technique de l'Aviculture ITSAP, Institut Scientifique et Technique de l'Abeille et de la Pollinisation (ex. CNDA, Centre National du Développement Apicole) => 1100 engineers and technicians Ex.1 : IFV (vine and wine), main modeling themes • Vineyard protection against pests and diseases • Yield Quality : evaluation of potential of a field or year. • Physiology of vine : information on key phenological stages to predict yield and maturity of grape. • Vineyard soil water status: drought constraint and global warming impact assessment. Environment impact assessment : fluxes (C, N, P, K, Cu, Zn) to water, air and soil. Ex.ante and multicriteria assessment of production strategies. • Milk production system : consequences of management on milk production. • Technical and economical. 2010 (Paris) « What's new, what's next in dynamic system modeling in agronomy » 8 Modeling activity… Existence of a huge quantity and variety of models => Importance of clarifying what are these modeling works and their place in our community. The goal of such work is not to construct a model, but to answer a practical issue with a specific purpose. => Viewpoint of "modeling project" September 7, 2010 (Paris) « What's new, what's next in dynamic system modeling in agronomy » 9 Modeling projects for agricultural development September 7, 2010 (Paris) « What's new, what's next in dynamic system modeling in agronomy » s new, what's next in dynamic system modeling in agronomy » 12 Duration September 7, 2010 (Paris) « What's new, what's next in dynamic system modeling in agronomy s new, what's next in dynamic system modeling in agronomy » 14 Type 1: ex. Wheat Septoria •A clear and operational message provided to farmer •Real time data •Regional map •Suggested date for the first treatment David Gouache et col., Arvalis September 7, 2010 (Paris) « What's new, what's next in dynamic system modeling in agronomy » 15 Type 1: ex. Apricot yield planning CTIFL September 7, 2010 (Paris) « What's new, what's next in dynamic system modeling in agronomy » 16 sowing dates Type 2: ex. SUNFLO Pierre Casadebaig et col., CETIOM/INRA September 7, 2010 (Paris) « What's new, what's next in dynamic system modeling in agronomy » 17 Type 2: ex. MELODIE MELODIE model (INRA-IE-IFIP) used to assess environmental impact of livestock dairy cattle or pig Scenarios of farm management At short (months) and long term (decades) Access to variables that can not be measured End user: engineers ITA & researchers INRA. Philippe Faverdin et col., INRA/IE/Ex. disease population + crop growth + crop practices September 7, 2010 (Paris) « What's new, what's next in dynamic system modeling in agronomy s new, what's next in dynamic system modeling in agronomy » 24 Conclusion All the modeling projects are long and mobilize different skills the projects can be divided into two types • projects aiming at decision aids for agricultural production systems • projects aiming at assessment of agricultural production systems In general, the same steps in the modeling projects The way each step is carried out is quite different, and resources' management should be adapted to the project. => it's really important to clarify the issue and the objective

Summary of the two types Type 1.

• duration : Several years, mainly devoted to the evaluation of the model compared to real references (networks of observation). • Importance of quality for prediction OR for decision Type 2.

• duration: Several years, mainly devoted to the design and improvement of the model. • Importance of the conceptual model


Ch

Herbivore respiration

Without supply of fresh C (energy) for microbes, deep carbon is stable In CO 2 equivalents, using the global warming potential (GWP) of each gas at the 100 years time horizon (IPCC, 2007):

NGHG : on site greenhouse gas balance Attributed NGHG: on and off site greenhouse gas balance Off site: emissions in the barn from cut herbage (digestion and wastes)

Budgeting GHG: net GHG balance in CO 2 equivalents (Soussana and Tallec, 2009) GHG balance in CO 2 equivalents at European sites (g CO 2 -C equivalents m -2 yr -1 ) (Soussana et al., 2007, Soussana andTallec, 2009)

Management NCS Att- NCS Grassland methane GWP CH4 F CH4

  Changes in total soil organic carbon content are hardly detectable within a few years How stable is organic carbon? Comparing deep this large pool of carbon going to react to global change and accelerate the rise of atmospheric CO 2 ? (Fontaine et al., Nature 2007) Effect of fresh C supply to deep microbes. soil C (priming effect).

•4

  Tallec, Animal, in press; Soussana et al., in prep.) Fate of harvested C at cut sites (g C m -2 yr -1 ) Mean of 3 sites (Soussana et al., 2007, AGEE; Soussana & Tallec, 2009, Animal) Att-NCS = NCS + NCS @barn = NCS + f humif Max[0, (1-f diges )F harvest -F manure ] Fate of harvested C at cut and grazed sites (g C m -2 yr -1 ) al., 2007, AGEE; Soussana & Tallec, 2009, Animal) Herbage utilisation by grazing and cutting (gC m -2 an -1 The less carbon is used, the more is returned to the soil, which increases C sequestration • Nitrogen supply also favours carbon sequestration Carbon sequestration (NCS) at 10 European grassland sites (Soussana et al. Agriculture, Ecosys. Environment, 2007) Global technical mitigation potential by 2030 of each agricultural management practice Carbon sequestration in agricultural soils : 89 % Mitigation of CH 4 emissions: 9 % Mitigation of N 2 O emissions: 2 % (IPCC, 2007) Mitigation potential of GHG emissions from the agriculture sector in 2030 (Mt CO 2 eq./year, B2 scenario, 100 $ US/tCO 2 -eq) Drawn from data in Smith et al., 2007a. CH 4 : in-situ dual tracer mehod -N 2 O: automated chambers On site emissions of N 2 O and CH 4 , converted in CO 2 equivalents using the GWP of each gas, offset 43 % of the ecosystem C sink The net greenhouse gas balance, also including off-site emissions of N 2 O and CH 4 through digestion of cut herbage, is a small net sink by 85 ± 77 g C m -2 yr -1 (Flechard et al., 2007, Pinares-Pineiro et al., 2007, Soussana et al., 2007)

  more plant species in a permanent grassland patch, the higher the local productivity Root traits effects on productivity and C sequestration (Klumpp and Soussana, 2009 Global Change Biol., in press) when there are less coarse roots Outline 1. Introduction: the terrestrial carbon sink 2. Carbon sequestration in European grasslands 3. Carbon sequestration in the context of GHG balance 4. Vulnerability of carbon stocks to climate change and biodiversity loss 5. Carbon sequestration options for livestock farms

loss may impact C sequestration Soil organic matter CO 2 Energy Chemical characteristics of litter Plant Production/ Allocation Micro- environmental Plant species diversity Plant functional traits Defoliation by cutting and grazing

  Impacts of climate variability and extremes on the C cycle in grasslands

	Climate change impact on grassland Biodiversity effect at patch scale Outline soil carbon sequestration in managed grasslands
	1. Introduction: the terrestrial carbon sink Interannual variability
	Total methane GWP CH4 F CH4 145 476 447 NGHG Att-2. Carbon sequestration in European grasslands Grazing 471 471 145 Grazing & cutting 183 268 159 Cutting 259 359 0 4 F CH4 land ne Total methane GWP CH4 F CH4 Grassland N 2 O GWP N2O F N2O Total N 2 O GWP N2O F NGHG (A) biomass N2O 145 22 22 320 320 476 64 81 -22 -272 447 30 53 230 -141 3. Carbon sequestration in the context of GHG balance 4. Vulnerability of carbon stocks to climate change and biodiversity loss Agricultural management Above-ground Log Greenhouse gas emissions 0 2 4 6 8 10 12 Green	G GW
	NGHG: grassland greenhouse gas balance Att-NGH: attributed greenhouse gas balance (including off site emissions) Number of Species Biomass 5. Carbon sequestration options for livestock farms (g)

(Smith et al., 2005, Global Change Biol.) Biodiversity (Gross et al., in revision, BAE)

(Fontaine et al., Nature 2007)

C sequestration reaches 6 % of gross photosynthesis, similar to forests Direct plus indirect emissions of N 2 O and CH 4 lead to a 45 % trade-off (Soussana et al., in prep.)

A dynamic model coupling lifecycle analysis and carbon sequestration (Salettes et al., 2004;Schils et al., 2007;Duretz et al., 2009) Net greenhouse gas balance of cattle farms per unit energy in animal products (FarmSim model) Concluding remarks

• There is a clear potential for C sequestration in European grasslands


domain: sdv info

text:
BON cells are a cell line derived from human enterochromaffin cells. They were previously described to express various olfactory receptors (ORs), but it is unclear whether a single cell expresses several types of ORs, as reported for spermatogenic cells, or a single type of OR as for olfactory sensory neurons (OSNs). The goal of the present work was first to answer this question and secondly to explore whether BON cells could be used for functional studies of heterologously expressed ORs.

BON cells were kindly provided by Kirk Ives (UTMB Galveston, USA). As the cell population appears heterogeneous in terms of morphology, we first serial diluted BON cells to isolate clones. RT-PCR was then carried out on RNAs from clones. RT-PCR products were subsequently cloned and sequenced. Clonal BON cells appear to express more than one OR and some ORs identified are expressed by several clones. To confirm the expression of several olfactory receptors by a single cell, single-cell RT-PCR was also performed.

Since BON cells endogenously express ORs, we expected they could also efficiently express heterologous ORs, which is still a challenge for most ORs in mammalian cells. Thus, we tried to heterologously express two human ORs (OR1G1 and OR17-40) in BON cells. We demonstrated that BON cells efficiently expressed these olfactory receptors at the plasma membrane level. Furthermore, we conducted calcium imaging and confirmed the activation of both receptors by their known ligands. While other ORs shoud be tested for functional expression by BON cells, these first results already suggest that BON cells constitute an interesting means to carry out functional studies of heterologously expressed ORs. BON cells expressing OR1G1 or OR17-40 were loaded with fluo-4 and stimulated with various concentrations of cognate ligands of these ORs. They displayed a calcium response within seconds when the ligand of the expressed OR was applied, while mock-transfected BON cells did not. BON cells also express pseudogenes at the mRNA level.

INRA, UMR1197

• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • BON cells

Endogenous expression of olfactory receptors by BON cells

Functional heterologous expression of olfactory receptors by BON cells

Both OR7E38P and OR2A9P pseudogenes, as well as OR7A17, OR7D2 and OR2A1 are reported to be expressed in several tumors.

Clones of BON cells could have derived with time. We confirmed that single BON cells can indeed express several ORs using single-cell RT-PCR and specific primers targeting some of the previously identified ORs.

We did not succeed in detecting all the receptors we were looking for. Nevertheless, we found that single cells of clone 14 co-express OR4F16 and OR10Q1.

•

• • • • • • • •

Conclusion

Contrary to OSNs, BON cells were shown to endogenously co-express various functional ORs and pseudogenes at the mRNA level. While some receptors appear to be expressed by all cells, each clone of BON cells seems to express a specific panel of ORs.

In the olfactory apparatus, a combinatorial code is used to detect and discriminate odorants, involving several OSNs each expressing a single type of OR. In the case of BON cells, the variability in OR expression and the ability to co-express several ORs could be used for the detection of various odorants or other molecules brought by food intake into the gastro-intestinal tract.

Furthermore, we demonstrate that BON cells can express functional heterologous ORs. Thus, BON cells seem promising for contributing to the deorphanization of ORs and their functional study.

  Neurobiologie de l'Olfaction et de la Prise Alimentaire, Domaine de Vilvert, F-78350 Jouy-en-Josas, France, Université Paris-Sud 11, UMR 1197, F-91400 Orsay, France, IFR 144 Neuro-Sud Paris, France

  heterologously express human OR1G1 and OR17-40 receptors. The receptors are fused to the cmyc epitope at their N-terminal end. They are revealed with an anti-cmyc antibody coupled to Cy3 on non permeabilized cells. BON cells were transiently transfected with mammalian expression vectors carrying the OR1G1 or OR17-40 receptor. Cells were observed 72h after transfection.

  of absence of genomic DNA nested PCR using pairs of degenerate primers corresponding to conserved regions of ORs cloning and sequencing of PCR products clones growth nested PCR using pairs of primers corresponding to variable regions of the previously identified ORs sequencing of PCR products Various clones of BON cells express various groups of ORs, but a subset of ORs (OR7D2, OR1F1) is common to most of the clones.


A mathematical test of the framework by Suding et al. ( 2008) (Klumpp & Soussana, GCB, 2009) Grassland mesocosms exposed to 13 C labelled CO 2 . Conclusions (statistical approach)

• Response&effect susccessfully tested • A simple equation encapsulates:

-Direct effects of drivers -Response&Effect of:

• Aggregated traits • Functional divergence of traits

• Drawbacks

-Often models with different traits are difficult to discriminate statistically, -More studies needed to generalise

D I S C O V E R D I S C O V E R
DISCOVER project (2006)(2007)(2008) • Is functional group diversity enough to explain diversity effects. How much species-specific information do we need?

• Can we distinguish between complementarity and selection effect in the model and assign processes to these effect groups?

• Do correlations between traits (trade-offs) force different species into complementary resource use?

Grassland Ecosystem Model with Individual centred Interactions, (GEMINI) Model parametrisation from trait measurements in grass monocultures (with no major limiting factors) 54 parameters were determined for 14 grass species (data basis, see Pontes et al., 2007Func. Ecol., 2008, GFS;Maire et al., Func. Ecol. 2009) Common garden study, Theix (288 micro-plots) Native grass species (2002)(2003)(2004)(2005)(2006)

  l e a f l e n g t h l l m a x θ Internode radius ri* Internode density di* Max. and min. length li max , li min (coll. Christian Wirth, MPI BGC) (Under development)

  Photo: A. Peeters

RNC (gN g -1 DM)

	A
	2.0
	1.8
	1.6
	1.4
	1.2
	1.0
	0.8
	0.6

) Leaf traits B) Root and rhizome traits

	Separating direct role of disturbance A role of functional diversity
	from Response&Effect
	Rao's index of functional divergence (FD)
	(Mason et al., 2005, Leps et al., 2006)
		b 2 , direct
	) C sequestration (gC m -2	Constant low disturbance (LL, ) Shift to high disturbance (LH, ) Constant high disturbance (HH, ) Shift to low disturbance (HL, ). disturbance effect aE 2 , trait mediated effect
		(after Klumpp & Soussana, GCB, 2009)
		(Klumpp & Soussana, GCB, 2009)

Acknowledgements • INRA UREP (Clermont, France) -Nicolas Gross (Post-Doc) -Vincent Maire (PhD student) -Raphael Martin (Engineer) -Bruno Bachelet (Engineer)

• Probably a key mechanism shaping BD-EF relationships

• Largely ignored so far

Plastic behaviour in GEMINI

Modelling the role of plant functional traits and of their plasticity