Olivier Therond

How to implement biodiversity-based agriculture to enhance ecosystem services: a review

Intensive agriculture has led to several drawbacks such as biodiversity loss, climate change, erosion, and pollution of air and water. A potential solution is to implement management practices that increase the level of provision of ecosystem services such as soil fertility and biological regulation. There is a lot of literature on the principles of agroecology. However, there is a gap of knowledge between agroecological principles and practical applications. Therefore, we review here agroecological and management sciences to identify two facts that explain the lack of practical applications: (1) the occurrence of high uncertainties about relations between agricultural practices, ecological processes, and ecosystem services, and (2) the site-specific character of agroecological practices required to deliver expected ecosystem services. We also show that an adaptive-management approach, focusing on planning and monitoring, can serve as a framework for developing and implementing learning tools tailored for biodiversity-based agriculture. Among the current learning tools developed by researchers, we identify two main types of emergent support tools likely to help design diversified farming systems and landscapes: (1) knowledge bases containing scientific supports and experiential knowledge and (2) model-based games. These tools have to be coupled with well-tailored field or management indicators that allow monitoring effects of practices on biodiversity and ecosystem services. Finally, we propose a research agenda that requires bringing together contributions from agricultural, ecological, management, and knowledge management sciences, and asserts that researchers have to take the position of “integration and implementation sciences.”

Defining assessment projects and scenarios for policy support: Use of ontology in Integrated Assessment and Modelling

Integrated Assessment and Modelling (IAM) provides an interdisciplinary approach to support ex-ante decision-making by combining quantitative models representing different systems and scales into a framework for integrated assessment. Scenarios in IAM are developed in the interaction between scientists and stakeholders to explore possible pathways of future development. As IAM typically combines models from different disciplines, there is a clear need for a consistent definition and implementation of scenarios across models, policy problems and scales. This paper presents such a unified conceptualization for scenario and assessment projects. We demonstrate the use of common ontologies in building this unified conceptualization, e.g. a common ontology on assessment projects and scenarios. The common ontology and the process of ontology engineering are used in a case study, which refers to the development of SEAMLESS-IF, an integrated modelling framework to assess agricultural and environmental policy options as to their contribution to sustainable development. The presented common ontology on assessment projects and scenarios can be reused by IAM consortia and if required, adapted by using the process of ontology engineering as proposed in this paper.

Designing agroecological transitions; A review

Concerns about the negative impacts of productivist agriculture have led to the emergence of two forms of ecological modernisation of agriculture. The first, efficiency-substitution agriculture, aims to improve input use efficiency and to minimise environmental impacts of modern farming systems. It is currently the dominant modernisation pathway. The second, biodiversity-based agriculture, aims to develop ecosystem services provided by biological diversity. It currently exists only as a niche. Here we review challenges of implementing biodiversity-based agriculture: managing, at the local level, a consistent transition within and among farming systems, supply chains and natural resource management. We discuss the strengths and weaknesses of existing conceptual frameworks developed to analyse farming, social-ecological and socio-technical systems. Then we present an integrative framework tailored for structuring analysis of agriculture from the perspective of developing a territorial biodiversity-based agriculture. In addition, we propose a participatory methodology to design this agroecological transition at the local level. This design methodology was developed to support a multi-stakeholder arena in analysing the current situation, identifying future exogenous changes and designing (1) targeted territorial biodiversity-based agriculture, (2) the pathway of the transition and (3) the required adaptive governance structures and management strategies. We conclude by analysing key challenges of designing such a complex transition, developing multi-actor and multi-domain approaches based on a combination of scientific and experiential knowledge and on building suitable boundary objects (computer-based and conceptual models, indicators, etc.) to assess innovative systems designed by stakeholders.

A generic framework for scenario exercises using models applied to water-resource management

Natural-resource management that concerns multiple agents with a variety of interests can be facilitated by integrated assessment methods which include modelling and/or stakeholder participation. Integrated assessment methods are increasingly used for scenario approaches that enable policy-makers to explore possible futures and assess potential consequences of different policy or management strategies. The paper proposes a conceptual and operational framework to illustrate a scenario exercise, based on a previously developed model, by building on recently published progress on the participatory and model-based assessment approach. This framework focuses on information flows in two key operational phases, problem specification and adaptation of model outputs, where scientists and stakeholders interact. In both phases, transformation steps convert narrative information into a quantitative form (and vice-versa), thereby enabling scientists to apply computer models and decision-makers to get confident in model predictions. On the basis of four case studies aimed at solving complex water-resource management problems, we illustrate the difficulties, constraints and questions of each step of the proposed framework and present original solutions. This framework, which can be applied to all natural-resource management issues, clearly defines the step(s) at which each partner should be involved in a scenario exercise and his/her contribution. Consequently, by having greater foresight and transparency, the framework determines the nature of interactions between scientists and non-scientists. A posteriori, it also describes how a scenario exercise was conducted.

Characterizing potential flexibility in grassland use. Application to the French Aubrac area

Farmers increasingly need to adjust their management practices to accommodate unexpected events such as drought, and preserve the sustainability of their production. This flexibility requires background knowledge about where and when freedom of choice can be exercised. Here, we designed an analysis framework for grassland-based farming systems in mountainous and less-favored areas. An expert-based discrimination tree characterizes organizational flexibility by determining the range of possible types of grassland use under various topographic and farming constraints such as suitability for mechanization, and ease of access to a field. A set of time windows evaluates the timing flexibility in grassland use, each associated with a combination of a grassland community type and a type of grassland use. Our results show that the outputs of the discrimination tree match for 139 of 165 grassland fields, by comparison with field data obtained in the French Aubrac region. For a particular type of grassland use, the set of time windows proves that timing flexibility in grassland use between grassland community types can increase by 15 days over a 37-day time range. When applying the two components of the analysis framework to a farm case, it shows that 24% of the farm area offers organizational flexibility, with several possibilities for grassland use. Timing flexibility for bringing forward or delaying the use of the grassland fields is unused in the farm. Most of the dates of grassland first use are similar irrespective of the diversity of grassland communities. The application of the analysis framework offers a sound evaluation of the potential flexibility to establish where and when it is possible to adjust management practices to cope with unexpected events. It can also be helpful in setting up coherent alternatives to the observed management strategies that can then be expanded in dynamic simulation models enabling deeper analysis.

A social-ecological framework for analyzing and designing integrated crop–livestock systems from farm to territory levels

Integrated crop–livestock systems are often considered a promising way to address agricultural sustainability issues. Many authors claim that complementarities and synergies between crops and livestock can improve nutrient cycling and delivery of ecosystem services (ES) in agricultural systems. They have analyzed effects of interactions at the farm level and affirmed the potential advantage of developing crop–livestock interactions at the territory level. However, potential benefits of developing synergies beyond the farm level have not been clearly identified. Thus, we developed a conceptual framework that can be used to analyze, design and perform integrated assessment of crop–livestock systems at the territory level. To address crop–livestock interaction issues, we define it as a social-ecological system called the territorial crop–livestock system (TCLS). The ecological system is represented as three interacting components, crops, grasslands and animals, allowing description of various land uses and their potential effects on nutrient cycling and ES. The social system, represented as farmers interacting with natural-resource managers and agro-food chain actors, determines land use and the nature and intensity of ES delivered. We highlight the importance of coordination and learning among actors to support implementation of complex adaptive systems such as TCLSs. We illustrate the expressive power of our conceptual framework through development of a generic typology of crop–livestock systems. Then we show how our conceptual framework can be used as an intermediary object with stakeholders in participatory design approaches. We illustrate this process by representing four archetypal TCLSs. We provide an example of the design approach implemented in Southwestern France to address severe recurrent water shortages, which includes analysis of land use in the current crop–livestock system and the associated key metabolic and ES issues, identification of options for change and multi-criteria analysis of these options. We conclude that this framework shows great potential to support development of sustainable farming systems at the territory level.

On the Use of Hydrological Models and Satellite Data to Study the Water Budget of River Basins Affected by Human Activities: Examples from the Garonne Basin of France

Natural and anthropogenic forcing factors and their changes significantly impact water resources in many river basins around the world. Information on such changes can be derived from fine scale in situ and satellite observations, used in combination with hydrological models. The latter need to account for hydrological changes caused by human activities to correctly estimate the actual water resource. In this study, we consider the catchment area of the Garonne river (in France) to investigate the capabilities of space-based observations and up-to-date hydrological modeling in estimating water resources of a river basin modified by human activities and a changing climate. Using the ISBA–MODCOU and SWAT hydrological models, we find that the water resources of the Garonne basin display a negative climate trend since 1960. The snow component of the two models is validated using the moderate-resolution imaging spectroradiometer snow cover extent climatology. Crop sowing dates based on remote sensing studies are also considered in the validation procedure. Use of this dataset improves the simulated evapotranspiration and river discharge amounts when compared to conventional data. Finally, we investigate the benefit of using the MAELIA multi-agent model that accounts for a realistic agricultural and management scenario. Among other results, we find that changes in crop systems have significant impacts on water uptake for agriculture. This work constitutes a basis for the construction of a future modeling framework of the sociological and hydrological system of the Garonne river region.

Livestock system sustainability and resilience in intensive production zones: which form of ecological modernization?

Abstract Changes in agriculture during the twentieth century led to high levels of food production based on increasing inputs and specialization of farms and agricultural regions. To address negative externalities of these changes, two forms of ecological modernization of agriculture are promoted: “weak” ecological modernization, mainly based on increasing input efficiency through crop and animal monitoring and nutrient recycling, and “strong” ecological modernization, based on increasing agrobiodiversity at different space and time scales and within or among farms to develop ecosystem services and in turn reduce industrial inputs even more. Because characterizing the sustainability of these two forms of ecological modernization remains an issue, we review the literature on livestock systems to compare their advantages and drawbacks. After defining the livestock system as a local social–ecological system embedded in a complex multi-level and multi-domain system, we characterize the two forms of ecological modernization (weak vs. strong). When sustainability is defined as a state that should be maintained at a certain level and assessed through a set of indicators (environmental, economic, and social), we highlight that one ecological modernization form might have an advantage for certain sustainability criteria, but a disadvantage for others. When sustainability is viewed as a process (resilience), we find that these two forms of ecological modernization are based on different properties: governance of the entire agri-food chain for weak ecological modernization versus local governance of agriculture and its biophysical and social diversity and connectivity, and management of slow variables for strong ecological modernization. The relevance of this sustainability-analysis approach is illustrated by considering different types of dairy livestock systems, organic agriculture and integrated crop–livestock systems.

Diagnosis and simulation: a suitable combination to support farming systems design

Designing or improving farming systems requires understanding their dynamics so as to predict their behaviour in response to management. Simulation tools can potentially support the process by which farmers and scientists might obtain such an encompassing understanding. The usability of these tools is, however, partially inhibited by the inherent complexity of the interactions at work in farm-scale models. Whereas such models are generally used in isolation, here we present an approach in which a field-scale diagnosis method complements a farm-scale simulation model. This diagnosis method lends itself easily to an intelligible presentation of field-specific knowledge that can be fed to the simulation tool for more encompassing considerations. Our approach is used to support the design of novel management strategies in grassland-based beef systems and proved to be effective when applied to two farms in the French Pyrenees. Thanks to the integrative representation of the various processes, including the management ones, simulation contributed to deeper learning of both scientists and farmers about room for manoeuvre for increasing self-sufficiency for forage. The diagnosis phase enhanced the learning process by providing a simpler framework in which elementary problems at field scale could be considered separately before being examined concurrently at farm scale in the simulation phase.

A new analytical framework of farming system and agriculture model diversities. A review

In most current farming system classifications (e.g. “conventional” versus “organic”), each type of farming system encompasses a wide variety of farming practices and performances. Classifying farming systems using concepts such as “ecological”, “sustainable intensification” or “agro-ecology” is not satisfactory because the concepts “overlap in…definitions, principles and practices, thus creating…confusion in their meanings, interpretations and implications”. Existing classifications most often focus either on biotechnical functioning or on socio-economic contexts of farming systems. We reviewed the literature to develop an original analytical framework of the diversity of farming systems and agriculture models that deal with these limits. To describe this framework, we first present the main differences between three biotechnical types of farming systems differing in the role of ecosystem services and external inputs: chemical input-, biological input- and biodiversity-based farming systems. Second, we describe four key socio-economic contexts which determine development and functioning of these farming systems: globalised commodity-based food systems, circular economies, alternative food systems and integrated landscape approaches. Third, we present our original analytical framework of agriculture models, defined as biotechnical types of farming systems associated with one or a combination of socio-economic contexts differing in the role of relationships based on global market prices and “territorial embeddedness”. We demonstrate the potential of this framework by describing six key agriculture models and reviewing key scientific issues in agronomy associated with each one. We then analyse the added value of our analytical framework and its generic character. Lastly, we discuss transversal research issues of the agriculture models, concerning the technologies required, their function in the bioeconomy, their multi-criteria and multi-level assessments, their co-existence and the transitions between them.