domain: shs sdv

text:
L Hazard

M Cerf

C Lamine

D Magda

P Steyaert

A tool for reflecting on research stances to support sustainability transitions

The success of transdisciplinary approaches to address sustainability problems largely depends on the compatibility between the research stances of the researchers involved. A research stance depends on strategic choices that researchers make doing their research regarding epistemology, methodology and implementation. We present a heuristic tool for researchers to reflect on the choices that define their own research stances. Designed and tested as part of doctoral training, this tool uncovers how research choices can lead to a wide range of research stances about a situation that requires action. Our tool allows researchers to articulate and discuss their research stances, to facilitate their management within a project. It is also useful to understand the relevance for action of the knowledge they generate.

 . Ambiguity refers to the controversies arising from multiple interpretations of the problem and its potential solutions 5 . These situations cannot easily be translated into well-defined problems that can be dealt with using proven methods. They are what Rittel and Webber call wicked problems 6 which, in addition, are contextdependent and require tailor-made solutions 2-4 . Indeterminate situations are challenging for issue-driven research. They allows researchers to investigate what is at stake in sustainability transitions and to tackle wicked problems. To investigate these situations, researchers design their research in line with what Thomas Kuhn calls a 'disciplinary matrix' 7 , i.e., the commitment by scientists to the consensual theories, values, instruments and methods of their disciplines. Each disciplinary matrix involves specific ways of problem framing, investigating, and/or considering proof. The difference between these "matrices" is commonly illustrated by differences between life and social sciences. For example and in simplified terms, regarding a local crisis in water management, ecologists will start their investigation focusing on ecosystems. They will quantify the impact of human practices on their functioning, with experimental and/or modelling approaches, to produce indicators as references for management. Sociologists will focus on social relationships. They will proceed by identifying the actors involved, their position regarding the problem, helping

them to redefine the problem and its solutions by dealing with the social process, even if technical knowledge is also involved. Due to these differences, scientific experts, who are expected to 'speak the truth' built on objective scientific knowledge, often disagree when it comes to wicked problems [START_REF] Brante | Empirical and epistemological issues in scientists' explanations of scientific stances: A critical synthesis[END_REF] . The emergence of such controversies can lead to the rejection of science. Recognition of scientific pluralism is therefore essential to tackle wicked problems so that controversies become a driver of change and not an obstacle [START_REF] Lascoumes | The Usefulness of Socio-Technical Controversies[END_REF][START_REF] Mitchell | Unsimple Truths: Science, Complexity, and Policy[END_REF] .

To promote scientific pluralism in action, we provide researchers with a tool to enable them to explain their modes of knowledge production (in the sense of Kuhn's disciplinary matrices) in relation to how they envisage such knowledge could be used. This tool enables exploration of what we call "research stances towards action". We illustrate how it works using the example of a project undertaken with students whose PhD thesis concerns the ecological transition of agriculture (Box 1).

The tool is a heuristic based on extensively debated concepts (explained below). Its originality lies in its ability to get researchers to discover and discuss these concepts, their articulation and the stances they take. Following Donald Schön, the tool invites them to be a Reflective Practitioner [START_REF] Schön | The reflective practitioner : how professionals think in action[END_REF] who questions his or her practices in and on action, and the relevance of the scientific knowledge he or she produces to those who take action. The tool makes it possible to discuss two epistemic uncertainties: the first due to the imperfection of the translation of wicked problems into a scientific issue, and the second due to the hard-to-predict impact of the scientific knowledge used to tackle these wicked problems [START_REF] Jung | Embedded expertise: a conceptual framework for reconstructing knowledge orders, their transformation and local specificities[END_REF] . It facilitates also debating how to articulate scientific knowledge together with other forms of knowledge. Finally, it lays the foundation for a reflexion on the scientist's engagement in societal transformations for sustainable transitions.

Fig. 1 │ Relationship between a problematic situation in a changing world and scientific investigation. A research stance towards action is the research strategy used to deal with an indeterminate situation. It aims to fulfil both academic requirements and those of the society dealing with wicked problems. It involves the choices made concerning the given situation at all steps in the process of knowledge production, i.e. (1) the translation of real-life problems into a scientific issue, (2) the choice of appropriate methods to tackle an addressable question, (3) the production of scientific knowledge, and (4) the use of scientific knowledge to transform the situation.

A heuristic tool to reflect on research stances

The tool questions the interactions between the different steps involved in a scientific approach and the indeterminate situation it studies. At stake is the fulfilment of both academic requirements to produce scientific knowledge and society's requirements for tackling wicked problems by taking relevant actions (Fig. 1). The choices behind these interactions are organised in three main fields: epistemology, methodology and implementation. In each of these areas, a researcher makes choices, which are detailed below and summed up in the heuristic tool (Fig. 2). How the tool works is illustrated using the example of PhD projects conducted by students working on adapting farming to climate change (Box 1). Fig. 2 │ Heuristic tool for discussing a research stance. The different choices which define a research stance are organised in three main fields: epistemology (the nature of the knowledge), methodology (the method of producing the knowledge) and implementation (the use to which the knowledge will be put).

Epistemology

According to Piaget, epistemology refers to what constitutes valuable knowledge [START_REF] Piaget | Logique et connaissance scientifique[END_REF] . Epistemological frameworks are diverse and they guide most of the choices which determine a research stance [START_REF] Carter | Justifying Knowledge , Justifying Method , Taking Action : Epistemologies , Methodologies , and Methods in Qualitative Research[END_REF] . However there is no agreement among scholars on how to classify them [START_REF] Avenier | Finding one's way around various methodological guidelines for doing rigorous case studies: A comparison of four epistemological frameworks[END_REF] . In our tool, the entryway to discuss epistemology is the distinction between two conceptions of scientific knowing based on the investigator's place, which has important methodological implications: positivism vs. interpretivism (Fig. 2). Positivism claims that there is a knowable reality independent of the observer. Scientific investigation then produces a knowledge considered as a univocal description of the world as it exists independently of us. Epistemological frameworks that do not believe in a reality independent of the observer (pragmatism, constructivism, constructionism, relativism, etc.) can be grouped under the term 'interpretivist' [START_REF] Yanow | Neither Rigorous nor Objective: Interrogating Criteria for Knowledge Claims in Interpretive Science[END_REF] . They consider reality as a mind construct derived from the interpretation of each individual's experience. In this case, scientific investigation produces socially constructed knowledge considered as a plausible interpretation of the world that fits lived experience [START_REF] Avenier | Finding one's way around various methodological guidelines for doing rigorous case studies: A comparison of four epistemological frameworks[END_REF] . The choice of an epistemological framework encompasses the researcher's motivation to conduct his/her research (driving force), the place given to others in the process (participation) and to the values (axiology) (Fig. 2).

Driving force. Scientific investigation is a process of objectivizing that is an attempt to produce knowledge about an object that is free from the subjectivity of the investigator. This process varies depending on whether the research aims to reveal universal laws governing the observed phenomena, or to foster agency -that is, the stakeholders' ability to take appropriate action in the indeterminate situation in which they are involved. [START_REF] Emirbayer | What Is Agency?[END_REF] The search for natural laws invites the researcher to separate facts and value judgements and concentrate on the facts. From this perspective, 'science never disputes matters of value, only matters of facts' [START_REF] Ayer | Lenguaje verdad y lógica[END_REF] . Objectivizing therefore involves creating matters of facts for comparison with a theoretical framework, either to challenge it or to confirm it. The strategy for producing general laws is to seek invariants across diverse situations using reproducible protocols. The primary aim of such a mode of knowledge production is to fulfil the conditions of the academic world rather than those of society (Fig. 1).

Fostering agency involves producing an understanding of a given situation in order to define how stakeholders might act in it. The knowledge produced is therefore highly contextualized, but relevant to taking action and assessing its consequences. The methodology aims to make the indeterminate situation intelligible for its stakeholders. Such intelligibility is developed through inter-subjectivation processes among the participants before leading to a qualification of the situation which supports problem framing and action-taking [START_REF] Steyaert | Role of intermediation in the management of complex sociotechnical transitions[END_REF] . The production of generic scientific knowledge can then take the inductive form of a generalization through the accumulation of concordant facts and the production of a theory giving sense to a variety of these facts [START_REF] Avenier | Finding one's way around various methodological guidelines for doing rigorous case studies: A comparison of four epistemological frameworks[END_REF] .

Participation. Sustainability transitions involve multiple domains and require investigation that transcends disciplinary and professional boundaries [START_REF] Hirsch | Implications of transdisciplinarity for sustainability research[END_REF][START_REF] Martens | Sustainability : science or fiction ? Sustain[END_REF][START_REF] Luks | Transdisciplinarity for social learning ? The contribution of the German socio-ecological research initiative to sustainability governance[END_REF] . Participation in a scientific inquiry can be discussed along two lines: (i) from an epistemic point of view by considering who are the relevant participants to contribute to the production of scientific knowledge and how their knowledge is taken on board, and (ii) from a political point of view by considering their involvement in the definition of the direction of research likely to impact their lives in the long term [START_REF] Heron | A participatory inquiry paradigm[END_REF] .

Disciplinary approaches usually favour participants who comply with the standards of the scientific discipline. Interdisciplinary approaches acknowledge the pluralism of science and bring together researchers from different disciplines to work together. Transdisciplinary approaches are even more inclusive, as they involve non-researchers, such as experts, representatives (of groups of stakeholders, citizens, etc.), and individual stakeholders struggling with or concerned by the indeterminate situation. Transdisciplinarity therefore requires that various types of knowledge, practices, and values of the participantsresearchers from different disciplines, experts, citizens concerned about their future, and/or stakeholders seeking solutions -be articulated [START_REF] Després | Collaborative planning for retrofitting suburbs: Transdisciplinarity and intersubjectivity in action[END_REF] . There is also a need not only to describe who is to be invited to participate in the investigation but also to identify the way participants' knowledge will be taken into consideration. According to the positivist approach, participation is understood as the extraction of people's knowledge in order to produce scientific knowledge and/or to test and implement scientific innovations in the real world. Interpretivist approaches tend to involve people more directly in the scientific investigation, as is the case in extended peer community approaches [START_REF] Funtowicz | Science for the post-normal age[END_REF] .

Axiology. Issue-driven research raises an axiological issue. It is not only the validity and credibility of the knowledge it produces that is important, but also its value with respect to the desires and interests of the people seeking solutions [START_REF] Heron | Co-operative inquiry: Research into the human condition[END_REF] . Despite this issue, researchers typically try to be as neutral as possible. This may lead them to limit their involvement in the situation they are studying. Being neutral, researchers avoid any form of engagement with and responsibility for the situation's stakeholders. Alternatively, researchers can choose to produce scientific knowledge by interacting with the stakeholders [START_REF] Hirsch | Implications of transdisciplinarity for sustainability research[END_REF][START_REF] Luks | Transdisciplinarity for social learning ? The contribution of the German socio-ecological research initiative to sustainability governance[END_REF] . They are then directly exposed to stakeholders' values, desires and interests. Their engagement creates a commitment to these stakeholders, and hence a responsibility [START_REF] Heron | A participatory inquiry paradigm[END_REF] . This commitment leads the researcher to manage the power relations that exist within academy, within society and between academy and society. As pointed out by Marta Struminska-Kutra, managing these power relations requires adjusting one's research posture to guard against opportunism, paternalism or relativism and paralysis [START_REF] Strumińska-Kutra | Engaged scholarship : Steering between the risks of paternalism , opportunism , and paralysis[END_REF] .

Methodology

Jonker and Bartjan define methodology as the way in which researchers conduct their research, i.e., defining a research question (problematization) and the research design to work on it (investigation) [START_REF] Jonker | The essence of research methodology -A concise guide for Master and PhD Students in Management Science[END_REF] . Researchers can adopt the preconceived way of project planning -both the research question and design are established at the beginning of the project, leaving little room for adjustments -or else their research work can be adaptive, with goals and means reviewed based on the dynamics of the situation and the relevance of the obtained results. In addition to this choice, it is possible to make more explicit the problematization, which led to the definition of a research question and the choice of a method of investigation (Fig. 2).

Problematization. Scientific problematization differs from stakeholders' problem framing of the situation being studied since it aims to identify a scientific issue, which meets the scientific concerns of the researcher's community. This issue is then translated into an addressable research question (Fig. 1). Such problematization can be reductionist when the complexity of the situation is broken down into basic parts which are studied separately. This allows the properties of the basic parts taken separately to be investigated analytically, while assuming that everything else remains unchanged. In contrast, holism aims to consider and study the situation as a whole [START_REF] Bawden | The community challenge: The learning response[END_REF] . The complexity of the studied situation is usually translated into a systemic representation with interrelated components. The components are considered as defining each other, so that modifying one of them will change everything else. The whole is thought to be greater than the sum of the parts, and the complex system to have emergent properties.

Investigation. Researchers can engage with the situation they are studying in different ways. They can interact with it simply in order to generate their research question. What would follow would then be an ex situ investigation, such as control experiments or computer modelling, but could also involve observations of the situation without interacting with it. These analytical [START_REF] Popa | A pragmatist approach to transdisciplinarity in sustainability research: From complex systems theory to reflexive science[END_REF] or descriptive-analytical [START_REF] Wiek | From complex systems analysis to transformational change: A comparative appraisal of sustainability science projects[END_REF] approaches aim to understand the situation as it is and/or its genesis. We refer to them as 'hands-off' approaches to distinguish them from approaches involving interaction with the situation, such as participant observation, or even participation in the transformation of the situation as part of a 'transformative' research. The latter method of investigation is based on the principle that 'acting is knowing'. Knowledge production is thus an integral part of the transformation [START_REF] Luks | Transdisciplinarity for social learning ? The contribution of the German socio-ecological research initiative to sustainability governance[END_REF][START_REF] Salas-Zapata | Typology of scientific reflections needed for sustainability science development[END_REF] . Research can take place in real action conditions [START_REF] Wiek | From complex systems analysis to transformational change: A comparative appraisal of sustainability science projects[END_REF] through instruments specially designed for the purpose such as transition experiments [START_REF] Van Den Bosch | Transition experiments: exploring societal changes towards sustainability[END_REF] .

Implementation

The researcher engaged in issue-driven research has a more or less clear idea of how to put scientific knowledge into practice. The two extreme visions of this implementation are, at one extremity, 'instrumental', and at the other, 'emergent'. The 'instrumental' implementation views scientific knowledge as an instrument for solving problems. Scientific knowledge is transformed into recommendations to be implemented to solve the problem. In a more democratic way, scientific knowledge can be introduced into debates concerning problem solving. In this 'emergent' implementation, scientific knowledge is then challenged in a dialogic interaction between its process of production and its implementation. It is put to the test in situations where it is thought that it could be useful [START_REF] Stoker | Design experiments: Engaging policy makers in the search for evidence about what works[END_REF] . The scientific knowledge is then combined with other types of knowledge and rationalities at work in the situation to produce tailor-made solutions. Putting scientific knowledge into action involves a conception of how actors adopt scientific knowledge. It also necessitates choosing a way of evaluating this implementation.

Adoption. If it is to be used, scientific knowledge should be adopted by those taking action. Convincing people that scientific knowledge should be applied in order to improve the action they are taking is the basis of the prevailing strategy of 'transfer' of knowledge [START_REF] Lavis | How Can Research Organizations More Research Knowledge Effectively Transfer to Decision Makers ?[END_REF] . Not using scientific authority argument to persuade, encourages deliberation and critical thinking, which allows people to discuss how scientific knowledge makes sense for them and could be used (or not) in the situation. Scientific knowledge is then embedded in a sense-making process that constructs an intelligibility of the situation. Each participant contributes to and is transformed by this construction [START_REF] Steyaert | Governance of complex environmental situations through social learning: a synthesis of SLIM's lessons for research, policy and practice[END_REF] .

Evaluation. Evaluation could be designed for accountability and/or for learning [START_REF] Lehtonen | OECD Environmental Performance Review Programme: Accountability (f)or Learning?[END_REF] . In the most rationalist-technocratic tradition, implementation projects are evaluated by considering the achievement of the stated goals (goal-based evaluation). In that case, monitoring or ex-post evaluation pursues the same goal: examining whether the action is functioning as planned and producing the expected outcomes [START_REF] Taras | Assessment -Summative and formative -some theoritical reflections[END_REF] . It produces evidence that the implemented solution works and can be promoted. An evaluation designed for learning is more 'responsive' [START_REF] Richards | The Evaluation of Cultural Action[END_REF] . First, it attempts to identify and analyse the diverse outcomes of implementation projects, both expected and not expected. Second, it is revised as the action progresses. The evaluation criteria and methods change each time goals and means are redefined while the action is taking place [START_REF] Smith | Varieties of Investigative Evaluation[END_REF] . This method of evaluation aims to create tailor-made solutions. It is the method of evaluation that is generic, not the implemented solutions.

Box 1 │ Reflecting on research stances with PhD students

The tool presented in this article was developed and tested during a training scheme for PhD students in INRA's 'Science for Action and Development' Department. The majority of PhD students in this department conduct issue-driven research as part of participatory and interdisciplinary projects. We work with these students on their research stances. This helps them report on their work, design responsible research, and become aware of the skills they used during their thesis work. The students produced an account of how they conduct their research, which was collectively analysed using this tool. Below, we illustrate how this tool encouraged three PhD students working on the adaptation of forage resources to climate change to reflect on their practices. AG chose to do her PhD in Ecology to produce knowledge about a fungal-plant symbiosis in order to use it to improve the drought tolerance of plant cultivars. Her research stance was typical in natural science, and the scientific knowledge produced was intended to be used as a means of creating new cultivars (Fig. 3a). Nevertheless, the originality of her work was revealed by her stance: she designed a research project aimed at explaining the world as it is, but with the idea that it should be useful for the purpose of transforming it. She therefore studied symbiosis using a systemic approach without dismantling it [START_REF] Gibert | A fungal endophyte reinforces population adaptive differentiation in its host grass species[END_REF] whereas the traditional approach taken by agronomists was more reductionist, i.e., separating symbionts from their hosts to understand how the symbiosis works. The reflective work she carried out with the tool revealed to her the originality of her stance, which was not over-reductionist as is usually the case in the community of researchers working on plant endophytes. She then became aware of the very originality of her work as well as the origin of the difficulty she had in dialoguing with the researchers of the 'disciplinary matrix' to which she belonged. MS did her PhD in Agronomy in order to design grassland management methods that respond to climate change. Her stance evolved during her work. Its primary objective was originally to model climate change, its impact on forage resources and changes in livestock producers' practices based on an optimisation process, therefore following a positivist, preconceived and instrumental logic. However, in order to understand how farmers came to make their decisions, she organised participatory workshops [START_REF] Sautier | A Sequential Participatory Approach to Adapt Livestock Systems to Climate Change[END_REF] . She then realised that her workshops were places where farmers exchanged, learned and transformed themselves. However, she did not incorporate these findings into her PhD work because the workshops were not designed to capture them. She was not able to fully embrace the 'emergent' view of Implementation (Fig. 3b). Nevertheless, this reflective work contributed towards her choice to do a post-doctoral fellowship in social science in order to build on her understanding of farmers' agency. CL had a background in agronomy and did a PhD that combined aspects of agronomy and management sciences. Reflecting on her stance led her to fully adopt and pursue a transformative and engaged research project at a time when she was questioning the relevance of this stance (Fig. 3c). She therefore became involved in a project being run by a group of livestock farmers who, after several years of drought, wished to increase their forage autonomy. She started by helping them co-design their own diagnostic tool, thus fostering their agency. She went on to develop with them a type of workshop to redesign their agricultural systems [START_REF] Lacombe | Participatory design of agroecological farming systems needs to match the collective goal of transformation with farmers' professional projects[END_REF] . While her methodology was highly adaptive, the implementation was, from the beginning of the project, emergent: the farmer's group qualified itself as a 'progress group' whose members learned from deliberation and assessment to improve their situation.

At an individual level, the use of this tool allows the coherence of the research process to be tested and statements to be aligned with practices. It also makes it possible for researchers to adopt or develop the stance that appears the most appropriate in their own particular case. Finally, tensions between researchers, or communities of researchers, with different stances can be identified. Tensions may arise, for example, between a PhD student and his/her supervisor, or between his/her different supervisors. At a collective level, the tool highlights a wide range of stances to a given problematic situation, and above all, the different rationales and practices that underlie these stances. Highlighting them and discussing them with young researchers is a way of making their diversity acceptable. It fosters the responsibility and respect required when adopting the transdisciplinary approaches indispensable for sustainable transitions.

At first glance, the tool produces two opposing caricatural stances: a positivist, reductionist stance producing recommendations, and an interpretivist systemic stance leading to the emergence and co-production of knowledge and solutions. The tool nevertheless proposes an in-between space. This in-between space reveals its importance when analysing how the researcher really interacts with the studied situation. The sterile debate between positivism being too normative and interpretivism not being sound enough is quickly overshadowed by the image of a more complex reality: the existence of arrangements between poles proposed by the tool for example, in an evaluation coupling accountability and learning [START_REF] Lehtonen | OECD Environmental Performance Review Programme: Accountability (f)or Learning?[END_REF] , positive knowledge that makes sense in a participatory process of problem solving [START_REF] Hazard | Mutual learning between researchers and farmers during implementation of scientific principles for sustainable development: the case of biodiversity-based agriculture[END_REF] , the recognition that recommendations made by scientists cannot be value free [START_REF] Davoudi | Evidence-Based Planning. disP -Plan[END_REF] , etc. A diversity of stances then emerges (box 1). The tool allows researchers to better justify their practices regarding both knowledge production within Academy and the implication for action within Society (Fig. 1).

Managing the double epistemic uncertainty

The tool is particularly useful to help researchers reflect on the production and implementation of scientific knowledge when the problem is ill-defined, which is often the case given the complexity of sustainability transitions [START_REF] Hirsch | Implications of transdisciplinarity for sustainability research[END_REF][START_REF] Martens | Sustainability : science or fiction ? Sustain[END_REF][START_REF] Luks | Transdisciplinarity for social learning ? The contribution of the German socio-ecological research initiative to sustainability governance[END_REF] . The positivist, reductionist and instrumental stance has proved its ability to solve well-defined problems. When tackling wicked-problems, the scientific approach, whatever the stance, must integrate and manage a double epistemic uncertainty [START_REF] Jung | Embedded expertise: a conceptual framework for reconstructing knowledge orders, their transformation and local specificities[END_REF] . The first is the result of the imperfection with which science tackles societal problems: a single original and clear research question cannot adequately represent the fuzziness of an indeterminate situation (Fig. 1). The second uncertainty arises from the unpredictability of the effects of scientific knowledge when introduced in a complex situation. Due to these two uncertainties, implementing scientific knowledge in an instrumental way often produces disappointing results [START_REF] Jordan | Embedding the concept of ecosystem services ? The utilisation of ecological knowledge in different policy venues[END_REF] .

The first uncertainty could be partially resolved by combining different points of view to make the indeterminate situation more intelligible. This could easily be done at the beginning of the investigation to define the problem or, in a more challenging way, though a transdisciplinary approach which involves the situation's stakeholders throughout the process of research investigation [START_REF] Hirsch | Implications of transdisciplinarity for sustainability research[END_REF][START_REF] Martens | Sustainability : science or fiction ? Sustain[END_REF][START_REF] Luks | Transdisciplinarity for social learning ? The contribution of the German socio-ecological research initiative to sustainability governance[END_REF] . It combines scientific and empirical points of view raised during a process of intermediation [START_REF] Steyaert | Role of intermediation in the management of complex sociotechnical transitions[END_REF] .

The second uncertainty could be reduced by closing the gap between the environment in which knowledge is produced and the environment in which it will be applied. The strategy that prevailed in the 20th century was to transform the environment in which knowledge will be used so that it resembles the knowledge production environment [START_REF] Callon | Acting in an Uncertain World: An Essay on Technical Democracy[END_REF] . However, this strategy proved to be unsustainable, as demonstrated by agricultural intensification [START_REF] Hazard | Baser l'enquête sur l'expérience pour gérer les incertitudes d'une transition durable : le cas de la transition agroécologique[END_REF] . Sustainable strategies tend to involve steering endogenous processes already at work in the situation rather than replacing them with exogenous ones, which are better known and consequently thought to be more manageable. Such situation-based management means working with the situation's stakeholders. It maximises the chances of the knowledge being useful, used, thereby contributing to sustainable transitions [START_REF] Hazard | Mutual learning between researchers and farmers during implementation of scientific principles for sustainable development: the case of biodiversity-based agriculture[END_REF] . It is nevertheless still possible that the knowledge implemented in a complex situation will produce unexpected outcomes. Only longterm experience accompanied by a thorough assessment will enable identification of these effects.

Framing the problem with stakeholders is clearly a necessary condition when it comes to identifying which piece of scientific knowledge or research strategy is relevant to their situation. However, alone, this condition is not sufficient: if it is to work in an indeterminate situation, such knowledge must continue to be shaped and reshaped over the course of long-term interactions between researchers and stakeholders [START_REF] Hazard | Mutual learning between researchers and farmers during implementation of scientific principles for sustainable development: the case of biodiversity-based agriculture[END_REF] .

Engaging in sustainable transitions

Our tool helps overcome the illusion that it is necessary to accompany the entry of scientific knowledge into society in order to guarantee its proper use. In our opinion, the researchers' responsibility lies in explaining the research stance, which led to the production of this scientific knowledge. Be that as it may, researchers who wish to participate in the implementation of scientific knowledge will have to choose between two major strategies. This choice depends whether they think that knowledge precedes action and informs the decision, or that it is an integral part of the action. Both options involve collective action for a process of either advocacy or inquiry. Advocacy involves raising citizens' awareness of a problem and proposing solutions based on evidence. Inquiry refers to the pragmatist philosophy: it is a critical investigation of the indeterminate situation carried out collectively by the situation's stakeholders, in which researchers can participate in producing or in making use of scientific knowledge.

Advocacy. The goal of advocacy is to get stakeholders to hear the alerts issued by scientists and to follow their recommendations. However, in order to comply with scientific recommendations, a stakeholder takes a wide range of information into account, not only the recommendation [START_REF] Simon | A behavioral model of rational choice[END_REF] . Each stakeholder, through his/her experience, values and access to information, develops his/her own rationale. The implementation of scientific knowledge is therefore confronted with this diversity of rationales at work in the situation. [START_REF] Coreau | The influence of ecological knowledge on biodiversity conservation policies: A strategic challenge for knowledge producers[END_REF] The 'speaking truth to power' strategy therefore shifts towards 'sharing truths with multiple actors of influence' [START_REF] Craft | Policy formulation, governance shifts and policy influence: location and content in policy advisory systems[END_REF] . 'Evidence-based' strategies become 'evidence-informed' ones, opening the way for the recognition that many other factors influence decision-making beyond scientific evidence alone. Seen in this light, advocacy is influencing, i.e., trying to ensure scientific knowledge is taken into account in the decision-making process. This leads to the creation of 'epistemic communities' which bring together researchers and a wide range of stakeholders who share the same convictions based on scientific facts [START_REF] Haas | Introduction: epistemic communities and international policy coordination[END_REF] . The role played by these epistemic communities involves raising awareness, framing the way of posing problems, and helping to defining new standards and regulations.

Inquiry. A pragmatist inquiry is a deliberative and experiential process to deal with the discomfort of stakeholders who realize that they can no longer go on doing what they do in the same way [START_REF] Lorino | Inquiry: the process of thinking, acting, and mediating[END_REF] . First, participants in an inquiry exchange experiences and produce a collective understanding of the situation. During this first phase, researchers can provide scientific knowledge to support this process. This may help generate the hypotheses to be tested to improve the situation [START_REF] Davoudi | Evidence-Based Planning. disP -Plan[END_REF] . The scientific approach itself can then be used to design the test, provided it involves all the inquiry's participants. Collective inquiries aim to promote learningby-doing so that the participants transform themselves at the same time as the situation, thereby achieving a real transition to an acceptable situation [START_REF] Palmer | Creativity, ethics and transformation: key factors in a transdisciplinary application of systems methodology to resolving wicked problems in sustainability[END_REF] . This learning requires reflexivity on the acceptability of both the expected and unexpected effects of the action taken [START_REF] Boud | Reflection: Turning experience into learning[END_REF] . Being in a position outside the situation, the researcher can organise this reflection and/or propose his/her interpretation of what has been experienced. All this occurs in a highly dynamic situation. The situation being studied 'does not remain static through the application of the research process': [START_REF] Cole | Being Proactive : Where Action Research meets Design Research[END_REF] Actions taken transform the situation, stakeholders learn from these changes, their points of view change, and what is acceptable one day may not be acceptable the next. Even though being at the heart of these changes is one advantage of the approach for researchers, they should develop their own reflective activity which will allow them to conduct their research wisely and be able to identify potential scientific outcomes [START_REF] Hazard | Mutual learning between researchers and farmers during implementation of scientific principles for sustainable development: the case of biodiversity-based agriculture[END_REF] .

Conclusion

The goal of the tool we describe here is to question and reflect on researchers' choices and their strategy for producing scientific knowledge for social transformations such as sustainable transitions. The tool can also be used to design and justify responsible research. It helps understand the diversity of scientific practices and their justification, thereby contributing to recognise scientific pluralism. This recognition and understanding will help acknowledge different research stances in inter-and transdisciplinary projects needed to tackle wicked problems [START_REF] Hirsch | Implications of transdisciplinarity for sustainability research[END_REF] . This tool and the facets of the scientific activity it makes available for exploration are original; researchers tended to reflect on their work by showing their results, whose relevance is usually discussed in terms of the quality of the data collection and analysis.

Being accountable to society should mean paying the same degree of attention to research stances in issue-driven research, as to the discussion of the results. However, some may infer from this paper that researchers bear the full responsibility for the interaction between science and society, which is not the case. Stakeholders, who often consider themselves clients of research, also have their own conceptions of what knowledge is, what research needs to produce and how. Just like research stances that are not epistemologically compatible, the views held by stakeholders on what action to take and how, may not be compatible either. A field consultant, for instance, can view his/her activity as knowledge brokerage, fostering enduser's innovation, or as technical advisory promoting their adoption of ready-to-use innovations. The tool presented here could certainly be adapted to shed light on these views that exist in society.

Fig. 3a│AG stance.

  Fig. 3a│AG stance.

Fig.

  Fig. 3b │MS stance.

Fig

  Fig. 3c │ CL Stance.

Acknowledgements

The authors thank D. Gardin, who produced the illustrations; A. Cardona, C. Fiorelli, B. Leclerc, G. Martel, F. Maxime, L. Prost and R. Sabatier, who tested the different versions of the tool during the JDD doctoral program; and A. Gibert, M. Sautier and C. Lacombe, who agreed to have their work presented in this paper. INRA's SAD Department supported this work financially.

Author contributions P.S. initiated the work by proposing an interpretative framework that was transformed by L.H. into a reflexive tool. The framework and tool were then reworked during the development of the manuscript by all co-authors. The writing and revision process were led primarily by L.H.


Hector Daniel

Inurreta Aguirre

Pierre-Eric Lauri

Christian Dupraz

Inurreta-Aguirre Hector Daniel
email: hector-daniel.inurreta-aguirre@supagro.fr

Lauri Pierre-Éric

; Dupraz

Christian ; Gosme

Yield components and phenology of durum wheat in a Mediterranean alley-cropping system

Keywords: Shade tolerance, Position in the alley, Grains per spike, LAI, NDVI

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

Introduction

Agroforestry, i.e. a land use that combines agriculture and forestry, including the agricultural use of trees [START_REF] Van Noordwijk | Central hypotheses for the third agroforestry paradigm within a common definition[END_REF], has been said to provide different services at various scales: field [START_REF] Jose | Interspecific interactions in temperate agroforestry[END_REF][START_REF] Simelton | Trees and agroforestry for coping with extreme weather events: experiences from northern and central Viet Nam[END_REF], farm [START_REF] Malézieux | Mixing plant species in cropping systems: concepts, tools and models. A review[END_REF][START_REF] Leakey | Tree domestication in agroforestry: progress in the second decade (2003-2012)[END_REF], landscape [START_REF] Nair | Agroforestry as an approach to minimizing nutrient loss from heavily fertilized soils: The Florida experience[END_REF][START_REF] Rockwood | Short-rotation woody crops and phytoremediation: opportunities for agroforestry?[END_REF], country [START_REF] Garrity | Agroforestry and the achievement of the Millennium Development Goals[END_REF][START_REF] Jerneck | Food first! Theorising assets and actors in agroforestry: risk evaders, opportunity seekers and "the food imperative" in sub-Saharan Africa[END_REF] and world [START_REF] Droppelmann | Water use efficiency and uptake patterns in a runoff agroforestry system in an arid environment[END_REF][START_REF] Stavi | Agroforestry and biochar to offset climate change: a review[END_REF]. One of the services is the increased total productivity (i.e. considering both crop and tree production) [START_REF] Muschler | Agroforestry : essential for sustainable and climate-smart land use?[END_REF]. However, when considering only crop yield, agroforestry usually results in a decrease in crop yield compared to the pure crop because of the competition for resources between the crop and the trees [START_REF] Cannell | The central agroforestry hypothesis: the trees must acquire resources that the crop would not otherwise acquire[END_REF][START_REF] Jose | Interspecific interactions in temperate agroforestry[END_REF]). Agroforestry, by its conception, imposes light reduction to the crop (i.e. shade) which can be a limitation for its productivity [START_REF] Fischer | Yield potential in a dwarf spring wheat and the effect of shading[END_REF].

Belowground, the competition for nutrients and water could also reduce productivity (Jose et al. 2000a, b).

On the other hand, agroforestry can have beneficial effects on crop yield, e.g. by changing the microclimate.

On top of the protection that trees can bring against adverse climatic extremes (Lin 2007), agroforestry microclimate could modify not only the thermal time experienced by the crop [START_REF] Lott | Understorey microclimate and crop performance in a Grevillea robustabased agroforestry system in semi-arid Kenya[END_REF]) and consequently impact crop phenology [START_REF] Sudmeyer | Influence of windbreak orientation, shade and rainfall interception on wheat and lupin growth in the absence of below-ground competition[END_REF], but also the evapotranspiration rate [START_REF] Karki | Microclimatic differences between young longleaf-pine silvopasture and open-pasture[END_REF]. Due to the spatio-temporal complexity of both below-ground and above-ground competitions [START_REF] Talbot | Simple models for light competition within agroforestry discontinuous tree stands: are leaf clumpiness and light interception by woody parts relevant factors?[END_REF], as well as the possible beneficial effects, the net effect of agroforestry on crop productivity is uncertain [START_REF] Ivezic | Relative crop yields of European silvoarable agroforestry systems[END_REF]. Often, the balance between a positive or negative tree-crop interaction depends on the edaphoclimatic conditions of the system [START_REF] Mosquera-Losada | Definitions and components of agroforestry practices in Europe[END_REF][START_REF] Muschler | Agroforestry : essential for sustainable and climate-smart land use?[END_REF], the management practices [START_REF] Kohli | Microclimate modification and response of wheat planted under trees in a fan design in northern India[END_REF][START_REF] Gill | Productivity and nutrient uptake of newly released wheat varieties at different sowing times under poplar plantation in north-western India[END_REF]) and the intrinsic characteristics of the crop and the trees [START_REF] Singh | Performance of wheat varieties under poplar (Populus deltoides Bartr.) plantations in Punjab (India)[END_REF][START_REF] Manceur | Dry matter partitions and specific leaf weight of soybean change with tree competition in an intercropping system[END_REF].

In order to better understand the effect of different management and/or environmental conditions on crop yield, it is useful to decompose yield into measurable yield components [START_REF] Kambal | Components of yield in field beans, Vicia faba L[END_REF]). These yield components develop sequentially, with later-developing components under the control of earlier-developing ones and interacting in compensatory patterns, particularly under stressful environments [START_REF] Simane | Ontogenetic analysis of yield components and yield stability of durum wheat in water-limited environments[END_REF][START_REF] Moragues | Yield formation strategies of durum wheat landraces with distinct pattern of dispersal within the Mediterranean basin I: Yield components[END_REF]. During a crop cycle, the light requirements [START_REF] Dong | Low light intensity effects on the growth, photosynthetic characteristics, antioxidant capacity, yield and quality of wheat (Triticum aestivum L.) at different growth stages in BLSS[END_REF]) and the optimal temperatures [START_REF] Porter | Temperatures and the growth and development of wheat: a review[END_REF] vary according to the phenological stage. Thus, considering the sequential formation of the yield components through the phenological development of the crop, the timing of occurrence of a beneficial or detrimental microclimate condition could impact (positively or negatively) a specific yield component.

Crop phenology is a function of accumulated degree days, photoperiod (day length) and vernalization requirements [START_REF] Brisson | Adaptation of the crop model STICS to intercropping[END_REF]). The phenology in cereals has been predicted using these factors [START_REF] Streck | Improving predictions of developmental stages in winter wheat: A modified Wang and Engel model[END_REF][START_REF] Master | Simulating the influence of vernalization, photoperiod and optimum temperature on wheat developmental rates[END_REF]. Specifically, [START_REF] Master | Simulating the influence of vernalization, photoperiod and optimum temperature on wheat developmental rates[END_REF] report that the use of vernalization and photoperiod as explicative factors results in accurately simulating anthesis date for a wide range of sowing dates. [START_REF] Slafer | Responses to photoperiod change with phenophase and temperature during wheat development[END_REF] reported that development in all phases is modified by photoperiod and air temperature to a different extent depending on the genotype. Also, they found that the ratio between the influence of photoperiod and temperature changes along the cycle. [START_REF] Gouache | Evaluating agronomic adaptation options to increasing heat stress under climate change during wheat grain filling in France[END_REF] agree that photoperiod affects the phenology during the whole cycle. However, they pointed out that vernalization is only relevant to calculate phenology until stem elongation. As agroforestry modifies both air temperature [START_REF] Peng | Photosynthetic response of soybean to microclimate in 26-year-old tree-based intercropping systems in southern Ontario, Canada[END_REF][START_REF] Gosme | Microclimatic effect of agroforestry on diurnal temperature cycle[END_REF]) and, most importantly, radiation under the trees, it is likely that it changes crop temperature and it could have an impact on crop phenology. A delay in phenological development of the crop might allow some sort of compensation for the reduced light under the tree canopy by extending the growing period of the crop. Furthermore, a change in the timing of occurrence of the sensitive stage in relation to an adverse weather event, or a mitigation of the extreme weather events itself, might be beneficial to the crop.

Agroforestry conditions could also modify cereal morphology [START_REF] Li | Effects of shading on morphology, physiology and grain yield of winter wheat[END_REF][START_REF] Wang | Interspecific interactions alter root length density, root diameter and specific root length in jujube/wheat agroforestry systems[END_REF], which in turn could change the interaction between the environment and the crop. It has been proved that shade conditions can increase the leaf area index (LAI), improving the capacity of the understory crop to intercept radiation [START_REF] Li | Effects of shading on morphology, physiology and grain yield of winter wheat[END_REF]. Other vegetation indices, such as the normalized difference vegetation index (NDVI), can be used as a proxy to estimate photosynthetic area in cereals [START_REF] Hansen | Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression[END_REF].

NDVI is a classical index of the crop, calculated using the red reflectance (R red) and near-infrared reflectance (Rnir).These changes in the photosynthetic area could compensate to some extent the reduction of light by the tree canopy.

Alley cropping is a type of agroforestry system in which parallel tree lines are planted in croplands, the alleys between tree lines are covered by natural or sown herbaceous vegetation and the soil on tree lines is usually not tilled [START_REF] Cardinael | Impact of alley cropping agroforestry on stocks, forms and spatial distribution of soil organic carbon -A case study in a Mediterranean context[END_REF]. In alley cropping systems, the environment is not homogeneous across space, depending mainly on the distance to the tree line [START_REF] Kohli | Microclimate modification and response of wheat planted under trees in a fan design in northern India[END_REF][START_REF] Sudmeyer | Influence of windbreak orientation, shade and rainfall interception on wheat and lupin growth in the absence of below-ground competition[END_REF].Therefore, trees in alley cropping system affect crop yield differently in the different positions in the alley, as both direct effects (competition for light, water, and nutrients) and indirect effects (modification of microclimate) depend on the distance to the tree as well as the position of the tree's shade as determined by the system's architecture, and the combination of latitude and time in the year and during the day. Considering the above, there is a lack of knowledge about the effect of alley cropping system (and within these, the distance with respect to the tree line) in Mediterranean conditions on foliar development, phenology and yield components of durum wheat. The aim of this study was to evaluate the impact of two different alley cropping systems, under typical conditions of the Northern Mediterranean region, on the yield, yield components, phenology, LAI and NDVI of a range of durum wheat genotypes, as well as the possible interactions between these traits that could allow compensation mechanisms to take place.

Materials and methods

Study sites

Two experiments were carried out in 2015 and 2016 at two different sites located in the 'Restinclières Agroforestry Platform (RAP) ' (CIRAD 2017) in Hérault department in the south of France (43° 42'N, 3°

51'E). The climate is sub-humid Mediterranean and the soil is deep calcareous silty clay. A local farmer rents the land to grow arable crops, but part of the plots can be dedicated to scientific experiments. In the experimental subplot, all cultural practices except sowing and harvesting are done by the farmer. The performance of durum wheat was evaluated in both alley cropping systems, (agroforestry, AF) and full sun (FS) conditions. In order to introduce genetic variability, 12 genotypes were tested in each experiment, among which four were evaluated in both experiments, totaling 20 genotypes. Genotypes were taken from old cultivars kept at INRA's durum wheat genebank (INRA 2017), as well as commercial cultivars. AF conditions were different in the two experiments. In 2015, wheat was sown in a single alley (13 m wide), with 15-year-old poplars (Populus canadensis CV I214) 30 m of height, planted at six meter distance within the row. The gap fraction of the trees canopy in the alley, measured through hemispherical photographs at harvest, was 67%. The cropped alley was split into 36 microplots (1.55 X 6 m). The 12 genotypes were planted in triplicate in the 36 microplots so that each genotype was present once in the two rows of microplots nearest to the trees on the South side of the alley, once in the microplots in the middle of the alley, and once in the microplots nearest to the trees on the North side of the alley (Figure 1a). In 2016, wheat was sown in three 13 m wide alleys, with 21-year-old ash trees (Fraxinus angustifolia Vahl) 15 m of height, planted at two meters along the line. The gap fraction of the trees canopy in the alley, measured through hemispherical photographs at harvest, was 65%. Each alley was considered as a block and was split into 12 microplots (1.55 X 6 m), totaling 36 microplots among the three alleys. The 12 genotypes were planted in each block so that each genotype was present once in the microplots nearest to the trees on the West side of the alley, once in the microplots in the middle of the alley, and once in the two microplots nearest to the trees on the West side of the alley (Figure 1b). In order to assess the effect of the position of the plot in the alley regarding the trees, the single alley in 2015 and the tree alleys in 2016, were split into three zones, each one formed by two lines of plots. Therefore, in 2015 the alley was subdivided into north, central and south zones and in 2016 into east, central and west zones. In both experiments, the distance from the tree rows to the first plot in each side was 1.85 m. The same planting pattern was repeated in FS conditions as the AF conditions (Figure 1).

[Insert Fig 1]

Management practices

In the '2015 experiment', the soil was prepared by plowing followed by a rotary harrow on January 07, 2015 because of floods that prevented sowing in the previous autumn. Sowing was done on January 12, 2015, at a density of 300 seeds per m 2 , using a sowing machine. The seeds were pretreated with PREMIS 25FS (active ingredient: triticonazole) in order to prevent fungal infection. Due to the late sowing, the usual treatment calendar of the farmer could not be applied to the experimental subplot, so no fertilizers or pesticides were applied. Harvest was done on June 30, 2015. In the ''2016 experiment'', the soil was prepared with a rotary harrow on October 23, 2015, and sowing was done on November 02, 2015, with the same methodology and density as in the '2015 experiment'. Applications of an herbicide (Athlet®, 3,6L/ha) and of a fertilizer (180 kg ha -1 ammonium nitrate + 33 units of sulfur), were carried out on November 13, 2015, and December 01, 2015, respectively. Due to a serious weed infestation, two hand weeding were done on 28/01/2016 and 22/03/2016. However, due to the size of the field, it was not possible to clean it all, so the weeds were only removed in a central area of 1m X 1.55 m in each microplot, and all measurement thereafter were done on this subset of the microplot. Harvest was done at maturity, on June 28, 2016, in FS and July 6, 2016, in AF.

Microclimate conditions

The air temperature was monitored using humidity and temperature probes (HMP155, Campbell Scientific, USA), placed inside a radiation and precipitation shield (DTR500, Vaisala, Finland). The incoming solar radiation under the tree canopy was measured using pyranometers (SP1110, Campbell Scientific, USA).

The sensors were installed from stem elongation onwards in 2015 and over the whole cycle in 2016, at locations shown in figure 1. Data from a meteorological station located in full sun conditions at 1.3 and 0.8 km from the '2015' and '2016' experiments, respectively, were used to fill in when data from the sensors were missing (e.g. due to battery failure or displaced cable).

Measured variables

In both experiments, the phenology was assessed from stem elongation stage to maturation stage (see below), weekly or twice a week depending on the season. The follow-up was done using the Zadoks scale [START_REF] Zadoks | A decimal code for the growth stages of cereals[END_REF]) that describes the phenology of cereals using 10 stages: the code from 0 to 9 correspond to the germination stage, 10 to 19 to seedling stage, 20 to 29 to tillering stage, 30 to 39 to stem The components of yield considered in the analysis were the number of plants per m², the number of tillers per plant, the percentage of fertile tillers, the number of grains per spike and the weight of grains. The harvest index was calculated as the ratio of the dry weight of grain to the total dry matter harvested (straw and spike). In both years, the number of plants was determined at the end of winter and tillers were counted before heading. The plants and tillers were counted in a line meter in two places of the microplot. The spikes were harvested in quadrats included in the weeded subsets of each microplot, 1m x 1m (2015) or 0.78m x 1m (2016, the four central sowing rows, to avoid edge effects). The harvested spikes were counted and the fresh and dry (after three days in a stove at 60 °C) weight were measured. The spikes were threshed and the grains counted and weighed.

Data management and statistical analysis

Due to the differences in experimental conditions in 2015 and 2016, each year was analyzed separately.

The climate data of each hour were classified as day or night according to the sunset and sunrise times of each day, using the 'R' package 'RAtmosphere'. The data concerning temperature and radiation were grouped according to three "growth periods" (germination-stem elongation, stem elongation-anthesis, and anthesis-maturity) defined based on the median stage of all microplots in a given system (FS vs AF). The thermal time was calculated as the number of growing degree days (GDD), using the daily maximal and minimal temperature [START_REF] Arnold | Maximum-minimum temperatures as a basis for computing heat units[END_REF]) and considering a unique base temperature equal to 0 °C [START_REF] Brisson | Conceptual basis, formalisations and parameterisation of the STICS crop model[END_REF][START_REF] Richter | Sensitivity analysis for a complex crop model applied to Durum wheat in the Mediterranean[END_REF]. Using data from observation dates when at least one phenological change occurred, a cumulative link mixed model ('Ordinal' package of R statistical software), was used to estimate the probability of each of the 72 microplots (36 in AF and 36 in FS) to remain in the previous stage, as a function of system (fixed effect) and genotype (random effect). Then, data from AF only were used to test the effect of position in the alley (North, center, South in 2015; East, center, West in 2016) considered as a fixed effect. Similarly, each yield component was analyzed using a mixed effect model ('lmer' package of R statistical software), considering the system as a fixed effect and the genotype, the block (only in 2016) and all the first order interactions as random effects. Using first the 'forward-fit methodology' for the random effects and the 'backward-fit methodology' for the fixed effects the best model was chosen based on the Akaike information criterion (AIC). Then, if the system effect was kept in the model, comparisons between systems were performed with Tukey's HSD test. The threshold for significance was set at α=0.05. Then, the effect of position in the alley was analyzed with the same methodology but taking only data from AF.

The LAI and NDVI data were analyzed with mixed effect models with the same random effects, but the fixed effect was a factor with 4 levels: FS and the three positions in the alley in AF.

Results

Yield and yield components

In 2015, the grain yield was not significantly different between FS and AF, with a mean of 45 and 46 g m -², for FS and AF respectively (Table 1). In 2016, the grain yield was considerably higher in FS than in AF, with 203 and 62 g m -² respectively. The comparison of yield components between the AF and the FS conditions (Table 1) showed that in 2015 the number of plants per square meter, the weight of grains and the harvest index were significantly higher in AF, whereas the number of grains per spike was significantly lower in AF. In 2016, the number of tillers per plant, the number of grain per spike and the harvest index were significantly lower in AF, while for the other yield components no statistical differences were found.

In both experiments the only yield components impacted by the position in the alley within agroforestry, was the number of grains per spike. In 2015, it was higher in the south zone of the alley in comparison with the north zone; the central zone was not statistically different from any of the border zones and in 2016 the west zone was higher than the other two (Table 2). In 2016 the final grain yield was also impacted by the position in the alley, being higher in west zone than in the central zone; the west zone was not different from any of the other two zones.

[Insert Table 1] [Insert Table 2]

Phenology [Insert Fig 2]

In both years, considering the median of all microplots, FS reached maturity first. However, in 2015, the difference between systems was small (about two days) with a high variability between genotypes (data not shown). In 2016, wheat ripened one week earlier in FS than in AF. In 2015, the probability of remaining in the earliest Zadoks's stage at the end of a given time period, was higher in AF from anthesis onward. In 2016 this probability was higher in AF whatever the period, but particularly since heading (Figure 2). The phenological stages used to define the growth periods in the following analyses of temperature and radiation were reached on various dates (Table…). There were no visible differences in the cumulative air temperature per hour (base 0°C) between systems during all periods for either year (Figure 3a). However, considering hourly temperature in the period between stem elongation and anthesis, AF showed a 'buffer' effect, warming the air below the canopy of the trees at night and cooling it during the day (Figure 3b and3c). The mean difference between AF and FS in 2015 was +1.14 during the night and -1.13 during the day; in 2016 the difference was +0.86 during the night and -1.72 during the day. On hot days in both years, the air temperature could be almost 6 °C lower in AF.

[Insert Fig 4]

There was a large difference between systems in the cumulated radiation that reached the crop in different growth periods for both years (Figure 4). In 2015, the cumulative radiation received in FS in the periods from stem elongation until before anthesis and from anthesis to harvest was 272 and 471 MJ m -2 , respectively; meanwhile, AF received in the same periods 115 and 192 MJ m -2 . In 2016, the cumulative radiation received in FS in the periods from emerging until before stem elongation, from stem elongation until before anthesis and from anthesis to harvest was 953, 578 and 586 MJ m -2 , respectively; meanwhile, AF received in the same periods, 523, 263 and 303 MJ m -2 . In both experiments and in all periods, the reduction rates in received radiation between FS and AF were around 50%. In spite of the fact that the late sowing in 2015 entailed higher instantaneous incident radiation at a given stage in comparison with 2016, the crop received more radiation during the stem elongation-anthesis period in 2016 because the duration of this phenological stage was longer (it lasted 24 days in 2016 and only 14 in 2015). Neither the temperature nor the radiation cumulated during the different periods of growth were statistically different in the different zones of the alley within the agroforestry system.

Relationship between phenology and temperature [Insert Fig 5]

The number of days after sowing (DAS) needed to achieve the stem elongation, anthesis and maturation stages in 2015 were lower than in 2016 by 56, 59 and 77 days, respectively (Figure 5a). In general, in 2015, the phenology in both systems was faster than in 2016, reducing the cycle by more than two months. This was due to the date of sowing: sowing in January in 2015 produced very different climate conditions, with both fewer days of the crop in winter and warmer temperature and longer photoperiod at a younger stage of the crop. Indeed, considering the thermal time instead of the DAS the differences between both years got shorter, but there were still differences in the number of growing degree days to reach each stage (figure 5b). Similarly, using thermal time instead of DAS was not sufficient to explain the lag between FS and AF.

Photosynthetic area [Insert Fig 6]

In 2015, the LAI of the crop measured close to anthesis (21/05/2015) was significantly higher in FS than in the center and south zones of the alley, but not significantly different from the north zone. In turn, the LAI of the crop was significantly higher in the north zone than in the south zone, and the central zone had an intermediate value, not being significantly different from either the north or the south zones (Figure 6a). In 2016 the LAI of the crop around anthesis (03/05/2016) was significantly higher in FS than in AF, whatever the position in the alley (Figure 6b). In 2015, the NDVI of the crop measured close to anthesis (13/05/2015) was significantly higher in FS than in AF (whatever the zone), and the north zone was significantly higher than the center and south zones (Figure 6c). In 2016, the NDVI of the crop, also measured close to anthesis (06/05/2016), was statistically not different between FS and the west zone of the alley, and both were significantly higher than the center and east zones, which were not significantly different one from the other (Figure 6d).

Discussion

Our results show that the impact of agroforestry on durum wheat yield was different in the two experiments.

In 2015, the yield was not statistically different between systems, however, it is important to highlight that the yield obtained in this experiment in both systems was considerably lower than the historical yield of the site (i.e. mean yield was about 10% of the normal yield, which is around 4.5 t ha -1 ; [START_REF] Dufour | Assessing light competition for cereal production in temperate agroforestry systems using experimentation and crop modelling[END_REF].

Meanwhile, in 2016, the yield in agroforestry was 70% lower than in full sun conditions, and yield in full sun conditions was not too bad, considering that the tested genotypes were mostly old varieties. This is consistent with [START_REF] Malézieux | Mixing plant species in cropping systems: concepts, tools and models. A review[END_REF] and [START_REF] Ong | Tree-Crop Interactions Agroforestry in a Changing Climate[END_REF], who, in their respective reviews, present a range of situations, in which the results of agroforestry change depending on the conditions of the system.

Despite the fact that the experiments in 2015 and 2016 were different in terms of sowing date, understory tree species and tree line orientation, some results are similar. The yield component with the highest negative impact of agroforestry in both years was the number of grains per spike. In the same way, agroforestry always delayed crop maturity by a few days. It is worth mentioning that in both experiments, there was a great variation among genotypes in all the yield components (the genotype effect was always included in the statistical model by the forward-fit procedure for the random effects in the linear mixed models). However, there was never an interaction between the genotype and the system meaning that on average, wheat genotypes were impacted in the same way by agroforestry. In line with this, other authors reported significant variation among genotypes under shade [START_REF] Lakshmanakumar | Physiological basis of yield variability in wheat (Triticum aestivum L.) under varying degree of shades[END_REF]) and agroforestry conditions [START_REF] Singh | Performance of wheat varieties under poplar (Populus deltoides Bartr.) plantations in Punjab (India)[END_REF][START_REF] Gill | Productivity and nutrient uptake of newly released wheat varieties at different sowing times under poplar plantation in north-western India[END_REF], even concluding that the success of agroforestry systems depends on the use of shade tolerant genotypes [START_REF] Barro | Forage yield and nitrogen nutrition dynamics of warm-season native forage genotypes under two shading levels and in full sunlight[END_REF][START_REF] Ehret | The effect of shade and shade material on white clover/perennial ryegrass mixtures for temperate agroforestry systems[END_REF]. The comparison between genotypes was beyond the scope of this paper, but further analyses of the performance of the tested genotypes in full sun and agroforestry systems in several sites and years should be performed in the future.

Effect of agroforestry on yield components

In 2015, the number of plants per square meter was higher in FS, mainly due to the improvement in germination or winter survival, which might be due to milder temperatures under the trees in winter (unfortunately temperature was not measured before 10/03/2015 in the '2015 experiment'). This effect was probably exacerbated by the late sowing in 2015, which was carried out in January while the normal sowing date in the region is November. Microclimate conditions that positively impact yield have been reported for wheat in agroforestry for some (but not all) orientations of the tree line and distances between the crop and the tree line [START_REF] Kohli | Microclimate modification and response of wheat planted under trees in a fan design in northern India[END_REF].

In 2016, the yield was strongly reduced in agroforestry, through reduced tillering (31% less tillers per plant)

as well as a reduction in floral initiation (25% fewer spikelets per spike, data not shown) and fertility (42% fewer grains per spikelets, data not shown). A negative effect of agroforestry on yield caused by belowground [START_REF] Zhang | Temporal and spatial distribution of roots as affected by interspecific interactions in a young walnut/wheat alley cropping system in northwest China[END_REF]) and aboveground [START_REF] Sudmeyer | Influence of windbreak orientation, shade and rainfall interception on wheat and lupin growth in the absence of below-ground competition[END_REF] competitions have been reported. [START_REF] Kohli | Microclimate modification and response of wheat planted under trees in a fan design in northern India[END_REF] found that agroforestry caused a reduction in quantity and quality of light that resulted in a lower number of tillers per land unit area. Similarly, [START_REF] Gill | Productivity and nutrient uptake of newly released wheat varieties at different sowing times under poplar plantation in north-western India[END_REF] and [START_REF] Kaur | Agro-techniques for increasing productivity of wheat (Triticum aestivum) under poplar (Populus deltoides) plantation[END_REF] reported a declining trend in the number of tillers of wheat in agroforestry with poplars, this effect being greater in systems with older trees. These reductions could be due to the effect of shading at tillering stage [START_REF] Kemp | Effect of tiller removal and shading on spikelet development and yield components of the main shoot of wheat and on the sugar concentration of the ear and flag leaf[END_REF][START_REF] Master | Effects of shading on winter wheat yield, spike characteristics and carbohydrate allocation[END_REF]). It should be noted that although tree budbreak happened in April 2015 (poplars) and March 2016 (ash trees), radiation interception by trunk and branches was important, due to the large tree size in 2015, and to high branchiness of the ash trees in 2016 : the gap fraction measured from hemispherical photographs before budbreak was XX% in 2015 and XX% in 2016.

The number of grains per spike was significantly lower in agroforestry than in full sun in both experiments (Table 1). This is in agreement with studies showing that the number of grains is highly affected by shade [START_REF] Slafer | Wheat development as affected by radiation at two temperatures[END_REF][START_REF] Abbate | Grain yield in wheat : Effects of radiation during spike growth period[END_REF][START_REF] Dufour | Assessing light competition for cereal production in temperate agroforestry systems using experimentation and crop modelling[END_REF], especially if the shade occurs during the rapid vegetative growth [START_REF] Slafer | Preanthesis shading effects on the number of grains of three bread wheat cultivars of different potential number of grains[END_REF][START_REF] Arisnabarreta | Grain number determination under contrasting radiation and nitrogen conditions in 2-row and 6-row barleys[END_REF]. [START_REF] Artru | Impact of spatio-temporal shade dynamics on wheat growth and yield, perspectives for temperate agroforestry[END_REF] also found a negative effect of shade in the number of grains per spike, but they have contradictory results about the relationship between the reduction in the number of grains and the quantity and daily dynamics of shade.

In our experiments, the radiation that reached the crop was always lower in agroforestry than full sun conditions, from sowing (shade of branches and trunks in winter) to harvest (Figure 4). However, the reduction in the number of grains per spike was not directly proportional to the reduction in the incident radiation. Indeed, the number of grains per spike was lower in agroforestry than in full sun by 21% and 62% in 2015 and 2016, respectively (Table 1), while radiation received in the period of formation of the number of grains (stem elongation-anthesis) was reduced by 41% and 52% in 2015 and 2016, respectively (Figure 4). The impact of agroforestry on the harvest index of the crop was not consistent in the two experiments.

In 2015, the harvest index was significantly higher in agroforestry, although, neither the weight of aerial dry biomass (straw + spikes) nor the yield of grain showed significant differences according to the system. In 2016, the situation was different, the harvest index was lower in agroforestry because although the dry weight of straw was lower in agroforestry, the grain weight was even more reduced in agroforestry and as a result, the harvest index was significantly lower in agroforestry compared to full sun. In line with these results, the literature shows that the relationship between agroforestry and harvest index is not clear. While some authors have found a negative impact of agroforestry systems on harvest index [START_REF] Gill | Productivity and nutrient uptake of newly released wheat varieties at different sowing times under poplar plantation in north-western India[END_REF]), others have found that despite a reduction in grain yield, the harvest index was not statistically different [START_REF] Dufour | Assessing light competition for cereal production in temperate agroforestry systems using experimentation and crop modelling[END_REF]. This variation in the results could be related to the conditions of radiation and soil humidity. In a study over several years, [START_REF] Sudmeyer | Competition for water between annual crops and short rotation mallee in dry climate agroforestry: The case for crop segregation rather than integration[END_REF] determined that the impact of agroforestry on harvest index depended on the rainfall conditions during the crop cycle. Non-agroforestry shade experiments also showed that a reduction in light could produce lower harvest index [START_REF] Lott | Long-term productivity of a Grevillea robusta based overstory agroforestry system in semi-arid Kenya II. Crop growth and system performance[END_REF][START_REF] Mu | Long-term low radiation decreases leaf photosynthesis, photochemical efficiency and grain yield in winter wheat[END_REF]. It is worth mentioning that the low average harvest index from both agroforestry and full sun conditions in our study was likely due to the ancient durum wheat varieties that were included in both experiments.

Effect of position in the alley on yield components

In both years the only yield component impacted by the position in the alley was the number of grains per spike, which was higher in the south zone in 2015 and in the west zone in 2016 (Table 2). It should be noted that in 2016, the position in the alley wih the lowest number of grains per spike (and also lowest yield) was the center zone ; this is surprising because many authors reported higher reductions in the yield components in the areas closer to the trees [START_REF] Dong | Low light intensity effects on the growth, photosynthetic characteristics, antioxidant capacity, yield and quality of wheat (Triticum aestivum L.) at different growth stages in BLSS[END_REF][START_REF] Yang | Impacts of long-term jujube tree/winter wheat-summer maize intercropping on soil fertility and economic efficiency -A case study in the lower North China Plain[END_REF]) due mainly to the reduction in the global incident radiation [START_REF] Bouttier | Vertical root separation and light interception in a temperate tree-based intercropping system of Eastern Canada[END_REF], daily dynamics of radiation [START_REF] Ding | Effects of tree shading on maize crop within a Poplar-maize compound system in Hexi Corridor oasis, northwestern China[END_REF] but probably also due to belowground competition for water and nutrients. Harvest index showed no difference with respect to the position in the alley, which is in agreement with the results reported by [START_REF] Kohli | Microclimate modification and response of wheat planted under trees in a fan design in northern India[END_REF] and [START_REF] Sudmeyer | Influence of windbreak orientation, shade and rainfall interception on wheat and lupin growth in the absence of below-ground competition[END_REF].

Correlation between yield and light interception

In these experiments, no difference was found in the cumulated radiation that could be correlated with an impact on the yield components.

Compensation effects (morphological or physiological changes) may have occurred in our experiments allowing wheat to perform better in the border than in the center of the alleys. For instance, in the 2016 experiment there was a higher NDVI in the west zone of the alley than in the other zones (Figure 6d), and this is where the number of grains per spike as well as yield were highest. This in agreement with [START_REF] Mu | Long-term low radiation decreases leaf photosynthesis, photochemical efficiency and grain yield in winter wheat[END_REF] and [START_REF] Li | Effects of shading on morphology, physiology and grain yield of winter wheat[END_REF], who found a negative correlation between the radiation received and the LAI.

Specifically, in agroforestry conditions, [START_REF] Abas | Light regime under Eucalyptus deglupta as hedgerows and its effect on intercropped Zea mays[END_REF] found a reduction in the LAI of the crop which was higher in the treatment with narrower alleys. In a north-south oriented alley of poplar and maize, [START_REF] Ding | Effects of tree shading on maize crop within a Poplar-maize compound system in Hexi Corridor oasis, northwestern China[END_REF] found that a zone with intermediate PAR achieved the highest grain yield, due to its high LAI (and still sufficient PAR). Another explanation could be that trees caused a beneficial environment in the border zone which may have benefited the crop near the trees in 2016 and in the whole alley in 2015 (e.g. less evapotranspiration, buffering of extreme temperatures).

Effect of agroforestry on crop phenology

In 2015, the crop reached maturity 149 days after sowing, meanwhile, in 2016 the maturity was reached 226 days after sowing (Figure 5a); this was due to the date of sowing which imposed completely different climatic conditions to the system. The difference in phenology between systems was clear in both years, in 2015 from the anthesis onward and in 2016 from stem elongation onward (Figure 2). According to Mc [START_REF] Master | Simulating the influence of vernalization, photoperiod and optimum temperature on wheat developmental rates[END_REF], the phenology of wheat is a linear function of the thermal time and responds to the photoperiod and the vernalization. Considering that photoperiod was the same in both systems (i.e. they were located at the same latitude) and that durum wheat has no requirements for vernalization, the differences in the phenology between systems must have been due to thermal time. The use of growing degree days instead of the days after sowing shortened the gap in the phenology between years, but it was not sufficient to explain all the variation in the development (Figure 5b), nor the difference in phenology between systems since there were practically no differences in thermal time between agroforestry and full sun using the standard way of computing growing degree days. The traditional method uses the maximum and minimum daily air temperature, which is inaccurate in agroforestry due to two phenomena: a) the fact that in agroforestry systems air temperature is not a good proxy to estimate the crop temperature, which is the variable that actually drives the phenology and b) the buffering effect of agroforestry on the daily temperature cycle (Figure 3). Further studies are thus necessary to better understand the complex relationships between agroforestry microclimate and crop phenology. This is all the more important since the delay in phenological development could partially compensate the reduction in incident light under the canopy, i.e. less light but for a longer period. experiments during the periods between phenological stages: ger-ste: period from germination until before the stem elongation; ste-ant: period from stem elongation until before the anthesis; ant-mat: period from anthesis until the end of maturation (harvest). Comparisons were made between systems in the same experiment. Pm -2 : number of plants per square meter, TP -1 : number of tillers per plant, %FT: percentage of fertile tillers, GS -1 : number of grains per spike, TKW: thousand kernel weight, HI: harvest index, GY: grain yield in g.m -2 . Means with different letters are significantly different according to Tukey's HSD,(p<0.05). No letter indicates that the system effect was not considered in the selected model according to the AIC. Comparisons were made between the positions in the alley in the same experiment. Pm -2 : number of plants per square meter, TP -1 : number of tillers per plant, %FT: percentage of fertile tillers, GS -1 : number of Grains per spike, TKW: thousand kernel weight, HI: harvest index, GY: grain yield in g.m -2 . Means with different letters are significantly different according to Tukey's HSD,(p<0.05). No letter indicates that the system effect was not considered in the selected model according to the AIC.

Figures name

  elongation stage, 40 to 49 to booting stage, 50 to 59 to heading stage, 60 to 69 to anthesis stage, 70 to 89 to grain filling stage and 90 to 99 to maturation stage. In 2015, the monitoring of the phenology was done at the microplot level. Due to the variability observed within the plots in 2015, in 2016, the phenological stage of the plot was determined by recording the Zadok's stage of 20 individual plants. The LAI was estimated using the LAI-2000 ® (LI-COR ®) and the normalized difference vegetation index (NDVI) with a handheld crop sensor (greenseeker, Trimble ®).

Fig 1 .

 1 Fig 1. Map of the 2015 (a) and 2016 (b) experiments, indicating the position of the different genotypes, the tree lines and the climate sensors.

Fig 2 .Fig 3 .

 23 Fig 2. Probability of remaining in the earliest phenological stage at the end of a time period for 2015 (a) and 2016 (b). Only the time periods in which at least one of the plots changed their stage were considered. ste: stem elongation stage; bot: booting stage; hed: heading stage; ant: anthesis stage; gaf: grain filling stage; mat: maturation stage.

Fig 4 .

 4 Fig 4. Cumulative global radiation received in full sun (FS) and agroforestry (AF) systems in 2015 and 2016

Fig 5 .

 5 Fig 5. Phenology of durum wheat in the different systems in 2015 and 2016 experiments as function of days after sowing (DAS) (a) and growing degree days (GDD) (b).

Fig 6 .

 6 Fig 6. Boxplots of the crop LAI and NDVI, according to the system and position in the alley within AF. Leaf area index (LAI) of wheat at anthesis in 2015 (a) and 2016 (b) experiments. Normalized difference

Fig 1 .

 1 Fig 1. Map of the 2015 (a) and 2016 (b) experiments, indicating the position of the different genotypes, the tree lines and the climate sensors.

Fig 2 .

 2 Fig 2. Probability of remaining in the earliest phenological stage at the end of a time period for 2015 (a) and 2016 (b). Only the time periods in which at least one of the plots changed their stage were considered. ste: Stem elongation stage; bot: Booting stage; hed: Heading stage; ant: Anthesis stage; gaf: Grain filling stage; mat: Maturity stage.

Fig 3 .

 3 Fig 3. Comparison of air temperature between agroforestry (AF) and full sun (FS) systems. Cumulative temperature per hour (base 0°C) between stem elongation (se) and maturity (mat) for 2015 and throughout the whole cycle for 2016 (a). Difference in the temperature measured at 1m above the soil (TAF-TFS), for each hour of the day in the period between stem elongation (se) and anthesis (ats) for 2015 (b) and 2016 (c) experiments. The black line shows the mean values of hour in the day.

Fig 5 .

 5 Fig 5. Phenology of the systems in 2015 and 2016 experiments in days after sowing (DAS) (a) and growing degree days (GDD) (b).

Table 1 .

 1 Yield components (mean ±SD) and yield inFS and AF in 2015 and 2016 experiments

	Experiment System	Pm -2	TP -1	%FT	GS -1	TKW	HI	GY
	2015	FS AF	152.49 (±35) b 168.37 (±31) a	1.15 (±0.36) 1.14 (±0.34)	53% (±0.15) 59% (±0.14)	14.27 (±4.1) a 11.22 (±4.1) b	33.48 (±4.8) b 36.93 (±5.4) a	0.23 (±0.06) b 0.29 (±0.06) a	44.79 (±24.8) 45.68 (±23.7)
	2016	FS AF	89.63 (±41) 99.97 (±35)	3.43 (±1.49) a 2.35 (±1.12) b	81% (±0.08) 85% (±0.11)	25.63 (±8.8) a 9.72 (±3.5) b	38.17 (±5.0) 36.87 (±4.7)	0.28 (±0.09) a 0.21 (±0.07) b	202.79 (±73.7) a 62.49 (±30.8) b

Table 2 .

 2 Yield components (mean ±SD) in three positions in AF in 2015 and 2016 experiments

	Experiment Position	Pm -2	TP -1	%FT	GS -1	TKW	HI	GY
		North	171.26 (±42)	1.07 (±0.39)	58% (±0.08)	8.87 (±3.2) b	35.91 (±6.5)	0.28 (±0.7)	49.53 (±20.6)
	2015	Center	167.98 (±21)	1.09 (±0.18)	61% (±0.21)	11.82 (±4.1) ab	37.67 (±4.7)	0.30 (±0.7)	49.53 (±24.6)
		South	165.87 (±39)	1.26 (±0.38)	58% (±0.15)	12.96 (±4.7) a	34.54 (±5.3)	0.26 (±0.7)	46.30 (±26.0)
		East	99.24 (±42)	2.49 (±1.31)	86% (±0.12)	9.38 (±3.4) b	36.97 (±3.9)	0.21 (±0.08)	61.31 (±29.14) ab
	2016	Center	110 (±30)	1.80 (±0.5)	86% (±0.09)	7.94 (±3.5) b	39.10 (±4.1)	0.20 (±0.06)	53.68 (±38.2) b
		West	90.67 (±31)	2.73 (±1.23)	83% (±0.12)	11.84 (±2.4) a	34.53 (±5.1)	0.22 (±0.06)	72.48 (±22.8) a

Acknowledgements

This research was partly funded by the Conseil Départemental de l'HERAULT (PIRAT project) and the European AGFORWARD project (Grant Agreement N° 613520), within the 7th Framework Programme of RTD, Theme 2 -Biotechnologies, Agriculture & Food. The views and opinions expressed in this paper are purely those of the writers and may not in any circumstances be regarded as stating an official position of the European Commission.

Compliance with Ethical Standards

The authors declare explicitly that they have no conflict of interest. All data presented in this article are results of original research conducted by the authors. This manuscript has not been submitted to any other journal and has not been published before, in a partial or complete manner. This research did not include any animal or human participant as objects of experimentation. All co-authors have been actively involved in this research and have given their consent for publication.