Claude Monteil

Modelling and simulating change in reforesting mountain landscapes using a social-ecological framework

Natural reforestation of European mountain landscapes raises major environmental and societal issues. With local stakeholders in the Pyrenees National Park area (France), we studied agricultural landscape colonisation by ash (Fraxinus excelsior) to enlighten its impacts on biodiversity and other landscape functions of importance for the valley socio-economics. The study comprised an integrated assessment of land-use and land-cover change (LUCC) since the 1950s, and a scenario analysis of alternative future policy. We combined knowledge and methods from landscape ecology, land change and agricultural sciences, and a set of coordinated field studies to capture interactions and feedback in the local landscape/land-use system. Our results elicited the hierarchically-nested relationships between social and ecological processes. Agricultural change played a preeminent role in the spatial and temporal patterns of LUCC. Landscape colonisation by ash at the parcel level of organisation was merely controlled by grassland management, and in fact depended on the farmer’s land management at the whole-farm level. LUCC patterns at the landscape level depended to a great extent on interactions between farm household behaviours and the spatial arrangement of landholdings within the landscape mosaic. Our results stressed the need to represent the local SES function at a fine scale to adequately capture scenarios of change in landscape functions. These findings orientated our modelling choices in the building an agent-based model for LUCC simulation (SMASH–Spatialized Multi-Agent System of landscape colonization by ASH). We discuss our method and results with reference to topical issues in interdisciplinary research into the sustainability of multifunctional landscapes.

How to Set Up a Research Framework to Analyze Social-Ecological Interactive Processes in a Rural Landscape

Interdisciplinary research frameworks can be useful in providing answers to the environmental challenges facing rural environments, but concrete implementation of them remains empirical and requires better control. We present our practical experience of an interdisciplinary research project dealing with non-industrial private forestry in rural landscapes. The theoretical background, management, and methodological aspects, as well as results of the project, are presented in order to identify practical key factors that may influence its outcomes. Landscape ecology plays a central role in organizing the project. The efforts allocated for communication between scientists from different disciplines must be clearly stated in order to earn reciprocal trust. Sharing the same nested sampling areas, common approaches, and analytical tools (GIS) is important, but has to be balanced by autonomy for actual implementation of field work and data analysis in a modular and evolving framework. Data sets are at the heart of the collaboration and GIS is necessary to ensure their long-term management and sharing. The experience acquired from practical development of such projects should be shared more often in networks of teams to compare their behavior and identify common rules of functioning.

Models for Sharing Representations

Companion modelling implementation is based on a network of individuals and artefacts amongst which models occupy a special place. This chapter presents the various models developed in a companion modelling process for purposes of representation sharing. Designed as a way of understanding actual (reference) systems in which social and biophysical dynamics overlap, models represent the evolution of these systems and are used for organizing exploratory simulation exercises involving stakeholders in the reference system.

A participatory Bayesian Belief Network approach to explore ambiguity among stakeholders about socio-ecological systems

Participatory modelling must often deal with the challenge of ambiguity when diverse stakeholders do not share a common understanding of the problem and measures for its solution. In this paper, we propose a framework and a methodology to elicit ambiguities among different stakeholders by using a participatory Bayesian Belief Network (BBN) modelling approach. Our approach consists of four steps undertaken with stakeholders: (1) co-construction of a consensual conceptual model of their socio-ecological system, (2) translation of the model into a consensual Bayesian Net structure, (3) individual parametrization of conditional probabilities, and (4) elicitation of ambiguity through the use of scenarios. We tested this methodology on the ambiguity surrounding the effect of an ecological process on a potential innovation in biological control, and it proved useful in eliciting ambiguity. Further research could explore more conflictual or controversial ambiguities to test this methodology in other settings. A participatory Bayesian Belief network method is proposed to sort out ambiguities among different stakeholders.The method is based on participation of stakeholders all along, from framing the research question to scenario exploration.The case study explored the ambiguities between local agricultural stakeholders and a landscape ecology scientist.

Simulating spatially-explicit crop dynamics of agricultural landscapes: The ATLAS simulator

The spatially-explicit AgriculTural LandscApe Simulator (ATLAS) simulates realistic spatial-temporal crop availability at the landscape scale through crop rotations and crop phenology. Intended to be linked to organism population dynamics, the simulator is developed in a multi-agent platform. The model relies on initial GIS inputs for landscape composition and configuration. Users define typical rotations and crop phenology stages to be included, according to their objectives. In the study, we present two applications to contrasting landscapes, where ATLAS is capable of simulating accurate composition (crop area) and configuration (crop clustering) dynamics. ATLAS has potential applicability to a range of contrasting agricultural landscapes. The benefits of such a simulator are the possibility to study the effects of various simulated management scenarios of crop spatial-temporal availability in relation to target organisms and/or specific ecological processes (e.g. pest, biological control), within a single model framework.

Description Formalisms in Agent Models

This chapter will aim to present good practice in, and the benefits of, formalization in modeling multiagent systems (MAS). To achieve this, the authors will first reiterate the usefulness of modeling systems, while placing the paradigms associated with a multiagent approach in context. Then, they will argue that the use of graphic modeling languages enhances the exchanges between the parties involved in the design of an MAS. Following this, two types of graphic models based on the same semantic base are presented: Unified Modeling Language (UML) and Agent Modeling Language (AML). The first graphic model is intended for general use and facilitates its users to analyze the ontology and dynamics of the modeled system. The second graphic model uses paradigms specific to agents and facilitates its users to create a design which is closer to the MAS which will be produced. After having discussed the relative merits of each of these graphic model types and presented some possible extensions, the chapter discusses the utility of, and a method for, documenting a multiagent model. In order to do this, the Overview, Design concepts, Details (ODD) protocol, which guides the modeler in the creation of a documentation of the objectives, constitutive elements and specific properties of the model, is presented.