Bases méthodologiques de la participation lors de projets ayant des impacts sur le paysage

Vincent Luyet
EPFL, 2005
EPFL thesis

Abstract

Recently, participation emerged as an appropriate tool to enhance natural resource management. Despite official recognition, there is no consensus on the practical meaning of participation. In this work, we consider the participation as a process through which stakeholders influence and share control over development initiatives and the decision and resources affecting them. The aim of this research is to answer to the participation's issues : who should participate? when? and how? The main contribution of this reserach work is to propose a methodology that allows to introduce the participation for large projects having impacts on the landscape. The result of this methodology is a system of participation. This system is composed of elements (project, stakeholders, techniques and levels of participation) and processes (identification, characterisation and structuration of the stakeholders, identification of the participation level, choice of the participation techniques, application and evaluation of the participation) in interaction. This system of participation is general and can be used for others projects. Howewer, the chronological order of the processes is iterative and is project specific. For each of the process used in the participation system, techniques were adapted, deveopped and tested. Stakeholders identification followed the adapatation of the Mason and Mitroff technique. Stakeholders structuration was made using cluster analysis. Identification of the level of participation followed the modifications of the Daniels et al and Vroom models. Relevent identification and assessment of participation techniques were made with the help of tables. All these thechniques yield results readily and pratically usable. The way stakeholders perceive the landscape and its dynamics are also studied in this research. This study allows to analyze the type and the effects of the information presented on the participative process and on the stakeholders. Based on our results, we advise to present landscape dynamics in a participative context. We recommand the use of simple landscape metrics such as the area doubled with the spatialization of the transition matrix. The stakeholders landscape preference allows to identify criteria such as the attitude towards the changes that would help in the elaboration of the future project. The originalities of this study can be found at various levels. In a general way, we can list the globality of the proposed methodology, the overlap of the social and technical sciences and the application of the methodology to the third Rhone correction project. In a more specific way, we can mention technical developments such as the application of original experiments concerning the identification of stakeholders landscape preferences. The system of participation proposed provides a conceptual framework that can be applied to others participative projects such as agenda 21 or the development of any projects having impacts on the landscape.

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Vincent Luyet
EPFL, 2005
EPFL thesis

Abstract

Official source

https://infoscience.epfl.ch/record/53665?ln=en

About this result

Related concepts (16)

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Related publications (5)

Related publications

Dispersal modelling

Séverine Vuilleumier Varisco

In human-dominated landscapes, populations and species extinctions are directly related to habitat destruction and fragmentation. To provide genetic diversity as well as population viability, individual exchanges among isolated populations must be maintained. Therefore, animal dispersal processes in fragmented landscape become an important topic for ecologists, and ecological networks planning has become one of the major challenges for landscape planners. Identification of habitat patches as well as assessment of the effect of ecological networks is badly needed. Since little information on the effect of landscape heterogeneities on animal dispersal is available, simulation models are being developed. As dispersal pattern and success strongly depend on the spatial context, species' interactions with landscapes, species behaviour and species ability to disperse, these models must be able to simulate them explicitly. This research work therefore aims first at developing methods and models that allow realistic animal dispersal simulations in fragmented landscapes. Second it aims at evaluating the effect of landscape heterogeneities and animal behaviour on dispersal and on species persistence. Additionally, the ability of such a model to estimate gene flow is analysed. To carry on this research, the following fields have been explored: landscape ecology, metapopulation dynamic, animal behaviour, genetics, Geographical Information Systems, modelling approaches and programming. A method, based on properties provided by Geographical Information Systems software, is first proposed to generate ecological networks by simulating animal dispersal according to animal movement constraints induced by human infrastructures. The resulting maps provide a spatial identification of ecological networks, corridors and conflicting areas. This model has proved to be a useful and straightforward tool for landscape planning, even if this model, similar to other present-day models used in dispersal simulations, presents numerous technical and scientific limitations. To improve models for animal dispersal, a feature-oriented landscape model associated with an expert system has been developed. Its conceptualisation, its formalism, its data structure and its object-oriented design implementation provide a very accurate representation of landscape features and simulation of complex interactions between model entities (individuals and landscape features) based on simple rules. It allows the spatial identification of simulated processes. The ability of this model to incorporate states, relations and transition rules between entities makes it applicable to simulate large ranges of dispersal processes according to specific behaviour and/or landscape uses. To analyse the influence of landscape heterogeneities and species behaviour on dispersal and their incidence on metapopulation dynamics, the proposed feature-oriented model has been coupled with an animal model. The latter assigns different cognitive and dispersal abilities to individuals. Based on simulations according to three movement strategies (corresponding to the cognitive abilities of the simulated species), two measures evaluate the effect of cognitive abilities on dispersal: the colonisation probability between habitat patches and the ecological distance (due to landscape heterogeneities). These measures give an estimation of metapopulation structures (the habitat patches belonging to the metapopulation) and metapopulation dynamics induced by the landscape heterogeneities (for example, the habitat patches which release individuals). The complexity of dispersal processes, considering species behaviours and dispersal abilities, can therefore be reproduced and analysed at different levels. This application has shown the importance of animal behaviour on metapopulation dynamics and structure. Since tracking animals and providing sufficient data remain difficult, calibration and validation procedures of dispersal models are difficult to perform. One approach proposed here is to measure one of the consequences of dispersal: genetic differentiation among populations. Geographical distances are in general used to explain a part of the genetic differentiations. But as our fundamental assumption states that landscape heterogeneities and spatial arrangements of landscape features may strongly affect dispersal successes, genetic distance between populations must be better explained by the estimate of a model which considers these factors. We have tested this assumption with the greater white-toothed shrew (Crocidura russula). Scenarios considering various behaviours and dispersal abilities of C. russula have been performed. Relating measures of genetic, geographical and ecological distances (the latter emerge from scenario simulation results) highlights the model capability to reproduce dispersal of C. russula by explaining a greater part of the genetic differentiation than that explained by the geographical distances. This application has not only pointed out the ability of the model to quantify connectivity between habitat patches but also the difficulty to relate gene dispersal and individual dispersal.

EPFL2003

The framework of complex networks has been shown to describe adequately a wide class of complex systems made up of a large number of interacting units. In this framework, a node is associated to each unit and two nodes are connected by an edge if the two units interact with each other. Examples of such systems can be found in living organisms—the map of interactions between proteins or the network of neurons in the brain. Moreover, artificial systems such as the WWW, electrical grids or airplane connections have been studied using the tools of complex networks. Finally networks have found many applications in social sciences to characterize for instance human interactions of different kinds underlying the spreading of an epidemic. For most of these systems, the complexity arises because of the large number of units and their intricate connection patterns. A natural approach is therefore to simplify the systems by decreasing their size. Different schemes can indeed be designed for each particular system, leading to effective but case-dependent methods. From a more global and statistical perspective, a promising alternative is to reduce the complexity of the corresponding networks. In order to simplify complex networks, two strategies are presented in this Thesis. The first approach refers to the well-known clustering paradigm. It aims at identifying groups of nodes densely connected between each other and much less to the rest of the network. Those groups are referred to as clusters or communities. For most real systems, nodes within a community share some similarity or common feature. For instance, in a synonymy network where nodes are words and edges connect synonymous words, we have shown that finding communities allowed us to identify words corresponding to a single concept. We have also studied a network describing the dynamics of a peptide by associating a node to a microscopic configuration and an edge to a transition. The community structure of the network was shown to provide a new methodology to explore the main characteristics of the peptide dynamics and to unravel the large-scale features of the underlying free-energy landscape. Finally we have designed a new technique to probe the robustness of the community structure against external perturbations of the network topology. This method allows us, among else, to assess whether communities correspond to a real structure of the network, or are simple artifacts of the clustering algorithms. Community detection techniques have found a large number of practical applications as a method to simplify networks since the number of clusters is often much smaller than the number of nodes. However, a crucial issue has often been disregarded: is the network of clusters truly representative of the initial one? In this Thesis, we show that this is indeed not verified for most networks. For example we have considered the evolution of random walks on the network of clusters and found that it behaves quite differently than in the initial network. This observation led us to develop a new strategy to simplify complex networks, ensuring that the reduced network is representative of the initial one. It is based on the idea of grouping nodes, akin to community detection. However, the aim is no longer to identify the "correct" clusters, but to find a smaller network which preserves the relevant features of the initial one, and especially the spectral properties. We therefore refer to our method as Spectral Coarse Graining, by analogy with the coarse graining framework used in Statistical Physics. Applying this method to various kinds of networks, we have shown that the coarse-grained network provides an excellent approximation of the initial one, while the size could be easily reduced by a factor of ten. Therefore, the Spectral Coarse Graining provides a well-defined way of studying large networks and their dynamics considering a much smaller coarse-grained version. Overall, we first discuss the use and the limits of the usual clustering approach to reduce the complexity of networks, and apply it to several real-world systems. In a second part, we develop a new coarse graining strategy to approximate large networks by smaller ones and provide several examples to illustrate the power and the novelty of the method.

EPFL2007

Theoretical and Experimental Studies of Dendritic Metacommunities

Francesco Carrara

The present thesis deals with the understanding of the origins and the mechanisms of maintenance of biodiversity in natural landscapes, in particular by identifying key processes that define large-scale patterns of abundance and diversity. Biological communities often occur in spatially structured habitats where connectivity directly affects dispersal and metacommunity processes. Recent theoretical work suggests that dispersal constrained by the connectivity of specific habitat structures affects diversity patterns and species interactions. This is particularly relevant in dendritic networks epitomized by fluvial ecological corridors. This thesis addresses whether connectivity alone can explain observed features of biodiversity and selectively promote different components of community composition in river-like landscapes, such as local species richness or the among-community similarity. The relevance of this thesis lies in the major ecological challenges posed by the topic, and its fundamental importance to conservation biology. The studies pursued herein are also deemed relevant because of the influence of the spatial connectivity and dispersal on population dynamics and of the relevance of biodiversity to ecosystem functioning. Mechanisms of species coexistence were investigated with a blend of theoretical tools (broadly related to statistical mechanics and the theory of stochastic processes) and experimental work using laboratory microbial communities. The research tools ranged from aspects of modern coexistence theory in a local perspective to the recent concept of the metacommunity in spatial ecology, within a unified framework. The study of biodiversity in riverine ecosystems guided by observational data has been addressed by combining theoretical metacommunity models with laboratory experiments. The results are diverse. First, they show experimentally that connectivity per se shapes key components of biodiversity in metacommunities. Local dispersal in isotropic lattice landscapes homogenizes local species richness and leads to pronounced spatial persistence. By contrast, dispersal along dendritic landscapes leads to higher variability in local diversity and among-community composition. Although headwaters exhibit relatively lower species richness, they are crucial for the maintenance of regional biodiversity. By suitably arranging patch sizes within river-like networks the effect of local habitat capacity (i.e., the patch size) and dendritic connectivity on biodiversity can be experimentally disentangled in aquatic microcosm metacommunities. It is shown in this thesis that species coexistence and community assembly depend on intricate, non-trivial interactions of local community capacity and network positioning. Furthermore, an interaction of spatial arrangement of habitat capacity and dispersal along river-like networks also affects a key ecosystem descriptor, namely regional evenness. High regional evenness in community composition is found only in landscapes preserving geomorphological scaling properties of patch sizes. In riverine environments some of the rarer species sustained regionally more abundant populations and were better able to track their own niche requirements compared to landscapes with homogeneous patch size or landscapes with spatially uncorrelated patch size. All the experimental results were supported and extended by a theoretical analysis where the above mechanisms have been generalized. This thesis provides the first direct experimental evidence that spatially constrained dendritic connectivity is a key factor for community composition and population persistence in riverine landscapes. As such, this thesis assesses a longstanding issue in spatial community ecology. It offers unique insights into the ecological forces structuring natural communities in a key ecosytem, and demonstrates principles that can be further tested in theoretical metacommunity models possibly to be extended to real riverine ecosystems. Taken together, the analyses show how the structure of ecological networks interacts with the spatial environmental matrix in determining biodiversity patterns and the functioning of biological communities. The analyses also suggest that altering the natural linkage between dendritic connectivity and patch size strongly affects community properties at multiple scales. The first part of this thesis (chapters 2 and 3) addresses key aspects of biodiversity-ecosystem functioning research where the combination of theory-guided experiments and theoretical investigations shows how a stochastic implementation of population dynamics proves fundamental for key community properties such as species persistence and community stability. The diversity-productivity and diversity-stability relationships are explored. Both experimental findings and the results of a stochastic model fitted to the experimental interaction matrix, suggest the emergence of strong stabilizing forces when species from different functional groups interact in the same environment, increasing species coexistence and community biomass production. The last part (chapter 6) provides a synthesis of this thesis work, in that it aims at unifying aspects from niche-theory, usually adopted in spatially implicit models, with those characteristic of a spatially explicit context from a typical real-life mountainous regions. It is dedicated to the possible explanation for a macroecological pattern routinely observed from organisms in different domains of life, that is, the mid-elevational peak in local species richness. Guided by empirical observations on diversity of macroinvertebrates in Swiss river basins, a theoretical ansatz is provided which is deemed to capture the essential geomorphological drivers and controls relating species-fitness to altitude. A set of overarching conclusions and perspectives for future research are discussed in the concluding chapter.

EPFL2013