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Nelva, Pasqual Jean-Sébastien. "Exploration des réseaux d'interactions en écologie : de la structure vers la dynamique : signification des analyses des matrices de communauté en écologie des estuaires". Electronic Thesis or Diss., Bordeaux, 2014. http://www.theses.fr/2014BORD0114.
Pełny tekst źródłaNetworks are a key concept in ecology and a number of models and methods have been used. This PhD dissertation links two approaches, the community matrix and input-output analyses, which have been developed by separate streams of theory. It compares their assumptions with important features of estuarine systems. It explicitly analyses the links between the matrices and the significance of the mixed trophic impacts analysis. Matrices of storage and throughflow analyses are linked to Jacobian matrices of donor or recipient controlled compartment models. Unlike most of what can be seen in the litterature, here the mixed trophic impacts are interpreted as the effects of a compartment being present or absent. Using available data in the case of five European estuaries, qualitative and quantitative matrices are built in the aim of performing sensitivity analyses. First explorations reveal high levels of uncertainties, even in the sign of the predictions. Furthermore, this work examines in more details the possibilities to explore transient dynamics from the community matrix. This PhD dissertation emphasises important features which are necessary to consider when choosing such approaches
Nelva, Pasqual Jean-Sébastien. "Exploration des réseaux d'interactions en écologie : de la structure vers la dynamique : signification des analyses des matrices de communauté en écologie des estuaires". Thesis, Bordeaux, 2014. http://www.theses.fr/2014BORD0114/document.
Pełny tekst źródłaNetworks are a key concept in ecology and a number of models and methods have been used. This PhD dissertation links two approaches, the community matrix and input-output analyses, which have been developed by separate streams of theory. It compares their assumptions with important features of estuarine systems. It explicitly analyses the links between the matrices and the significance of the mixed trophic impacts analysis. Matrices of storage and throughflow analyses are linked to Jacobian matrices of donor or recipient controlled compartment models. Unlike most of what can be seen in the litterature, here the mixed trophic impacts are interpreted as the effects of a compartment being present or absent. Using available data in the case of five European estuaries, qualitative and quantitative matrices are built in the aim of performing sensitivity analyses. First explorations reveal high levels of uncertainties, even in the sign of the predictions. Furthermore, this work examines in more details the possibilities to explore transient dynamics from the community matrix. This PhD dissertation emphasises important features which are necessary to consider when choosing such approaches
Liautaud, Kevin. "Community stability and turnover in changing environments". Thesis, Toulouse 3, 2020. http://www.theses.fr/2020TOU30264.
Pełny tekst źródłaThe question whether communities should be viewed as superorganisms or loose collections of individual species has been the subject of a long-standing debate in ecology. Each view implies different spatial and temporal community patterns. When environment gradually changes in space or in time, the organismic view predicts that species turnover is discontinuous, while the individualistic view predicts gradual changes in species composition. The main objective of this thesis is to understand the theoretical conditions under which these various types of community response can occur. First, I study the role of interspecific competition can play in the emergence of various spatial community patterns. I investigate the theoretical conditions in competition under which smooth or discrete spatial patterns can emerge. Then, I study how interactions between species and their environment can lead to various community patterns in space. I notably show how ecological niche construction can lead to the emergence of abrupt changes in species composition and in the environment, and the role biodiversity plays therein. Finally, I focus on the role biodiversity can play against ecosystem collapse. In this section, I illustrate how diversity loss, through its effects on total biomass, can lead to ecosystem collapse
Génin, Alexandre. "Réseaux d'interactions écologiques, stabilité et résilience des écosystèmes". Thesis, Montpellier, 2018. http://www.theses.fr/2018MONTG031/document.
Pełny tekst źródłaEcological systems are not simple but composed of many different elements(species, for example) interacting with each other. These networks ofinteractions exhibit structural properties that determine ecological systems’ability to absorb and recover from perturbations. Mappinginteractions along with their changes in time and space is therefore key tounderstand and predict empirical communities' response to global changes.In this thesis, we used plant communities as model systems (i) to explore howspatial patterns may help identify feedbacks loops which make communities morefragile to upcoming changes and (ii) to map species interactions in empiricalcommunities and describe how they change along stress gradients and recover fromperturbations. To do so, we used two datasets documenting plant communities insubalpine meadows (USA) and Mediterranean grasslands (France).Our results show that feedback loops can be inferred to some extent from thespatial patterns of plant communities and hence help identify communities thatmay respond more abruptly to perturbations. Going to a more detailed level ofdescription, plant-plant interactions (as measured through spatial associations)were shown to respond strongly and consistently to stress but exhibited a weakresilience to disturbances.This work shows that plant-plant interactions -- which are linked to the response of the community to perturbations -- can be uncovered using spatial patterns. It paves the way towards a better understanding and a better anticipation capacity of how ecological communities might reorganize when subject to disturbances
Subrahmaniam, Jaishree. "Identification des bases génétiques de la coopération plante-plante chez la plante modèle Arabidopsis thaliana". Thesis, Toulouse 3, 2020. http://www.theses.fr/2020TOU30043.
Pełny tekst źródłaDespite the importance of plant-plant interactions in the functioning of both natural ecosystems and agro-ecosystems, studies on plant-plant interactions still have two major gaps to be addressed, that is (i) the genetics of natural variation of plant-plant interactions and (ii) the relative importance of positive interactions within plant species. After writing two reviews on the state-of- the-art related to these gaps, I decided to understand the adaptive genetic bases of intraspecific positive plant-plant interactions in Arabidopsis thaliana at two geographical scales. To do so, I adopted an interdisciplinary approach between quantitative genetics, ecology and genome-wide association mapping. Firstly, based on a field experiment designed to study natural variation of genotype-by-genotype interactions among 52 whole-genome sequenced natural populations from the Midi-Pyrénées region, I identified two different strategies of positive interactions, i.e. kin cooperation and overyielding. Natural variation of positive interactions among these populations were mainly associated with biotic ecological factors varying at a fine spatial scale, such as presence of commensal bacteria or Shannon index of plant communities in the native habitats. Importantly, QTLs associated with variation of positive interactions were significantly enriched in genomic signatures of local adaptation. Secondly, based on a greenhouse experiment using 195 whole-genome sequenced accessions collected in a local French population located in a highly diverse and competitive environment, we revealed the existence of certain genotypic combinations that were benefitting reciprocally to each other’s presence, resulting in a ‘super overyielding’ strategy. Importantly, genetic dissimilarity at the QTLs associated with this strategy was detected for such pairs, supporting the ‘compatibility genes’ hypothesis as underlying this ‘super overyielding’ strategy. Finally, at both geographical scales, we detected a predominance of metabolism related gene functions underlying natural variation of positive interactions, which might be explained by their putative roles in (i) recruitment of similar microbiota by kin to explain kin cooperation, and (ii) potential complementary metabolite cross-feeding to explain overyielding. The next step is undoubtedly cloning of the candidate genes to identify causal associations, thereby allowing to start getting a glimpse on the genetic and molecular landscape associated with positive interactions in A. thaliana
Ohlmann, Marc. "Vers une théorie spatiale des réseaux d'interaction en écologie : méthodes, concepts et applications Diversity indices for ecological networks : a unifying framework using Hill numbers Unveiling the food webs of tetrapods across Europe through the prism of the Eltonian niche A spatial theory of mutualistic metacommunities : assesment of metacommunity capacity (in prep) Mapping the imprint of biotic interactions on β-diversity Multi-trophic -diversity mediates the effect of environmental gradients on the turnover of multiple ecosystem functions Combining abundances from different markers for environmental DNA (in prep)". Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAV065.
Pełny tekst źródłaThis thesis focuses on the links between interaction networks, space and time. There is a paradigm shift in community ecology concerning the representation of a species community : from a collection of species towards species and their interactions, represented by an interaction network. We aim to build the bricks for a spatial network theory, by developing new methods, new models and applying it on ecological data. This manuscript contains four chapters. In a first chapter, we extend the diversity indices, built on Hill numbers, to network diversity indices. We define diversity indices across species aggregation levelsand show the interest of this method on a trophic network data set. In a second chapter, we develop a spatially explicit meta-community theory, with various kind of interactions. The theory contains a stochastic and a deterministic meta-community model. We then define the notion of meta-community persistence capacity. In a third chapter, we focus on network reconstruction from environmental DNA data along an environmental gradient.We show that the proposed method allows to evaluate the influence of environmental variables on community and infer a network in agreement with the literature on soil interactions. Finally, in a fourth chapter, we develop a method to combine environmental DNA data coming from different primers and show the efficiency of the method to better estimate plant abundances
Maghnia, Fatima-Zahra. "Décryptage des réseaux d'interactions plante-champignon pour une meilleure gestion des subéraies méditerranéennes". Thesis, Montpellier, 2017. http://www.theses.fr/2017MONTT073/document.
Pełny tekst źródłaThe Cork oak (Quercus suber) forests play an important role in terms of ecological services and socio-economic development for the Mediterranean populations. However, the cork oak forests, notably in the Southern Mediterranean basin are highly threatened by increasing human and climate pressures, which accelerates desertication. The conservation of this ecosytem is strongly dependent of our ability to predict the environmental changes induced by these pressures as well as to develop sustainable approach for their restoration. In this context, the identification of biological indicators of cork oak health and the intensification of plant-plant facilitation processes appears as promisising ecological strategies. Their success is however subjected to our understanding of plant-fungal interactions, notably with fungal mycorrhiza, key factors of forest ecosystem functionning. The current work aimed at deciphering plant-fungal networks, notably mycorrhizal networks with cork oak and its understory shrub vegetation in three Moroccan cork oak habitats (Maâmora, Benslimane, Chefchaoun) characterized by different degradation levels. The root-fungal diversity associated to cork oak and major components of its understory shrub vegetation (Cistus salviifolius, Cistus monpeliensis et Lavandula stoechas) has been analysed by combining traditional methods based on morphological identification, and new generation high- throughput DNA sequencing methods to characterize communities at the molecular level.The study represents the most extensive survey of soil fungal diversity, notably mycorrhizal diversity, in Moroccan cork oak ecosystems. Different fungal community structures were revealed, depending on habitat, plant host type, and degradation forest status. A wide range of fungal indicators of plant type × forest status has been identified, highlighting the importance of several ectomycorrhizal fungi (notably Cenococcum, Russula, Terfezia and Tomentella) as well as ericoid mycorrhizal fungi (Cladophialophora, Oidiodendron) and arbuscular mycorrhizal fungi (Rhizophagus, Redeckera, Racocetra, and Paraglomus). The current work provides an extensive database on the ecology of soil fungi related to the Moroccan cork oak forest, offers new insights into the potential of soil fungi for monitoring the health of the cork oak forest, and for the developement of efficient conservation programs of this ecosystem by taking into account the soil fungal communties associated. The use of proposed appoaches to a larger diversity of forest ecosystems are promising to better understand the biological fonctionning of forest ecosystem and their conservation in response to the worsening of worldwide human and climate pressures
Kamenova, Stefaniya. "Réseaux d'interactions, biodiversité et services éco-systémiques en milieu agricole : que nous apprennent les coléoptères carabiques ?" Thesis, Poitiers, 2013. http://www.theses.fr/2013POIT2319.
Pełny tekst źródłaBiological control is one of the main ecosystem services provided by biodiversity in agroecosystems. Communities of beneficial insects, hosted by agricultural areas exhibit high levels of species and functional diversity, and their biology and life history traits are well described today. These communities are therefore an excellent model for addressing issues of fundamental and applied interest about mechanisms at the origin of biodiversity and its impacts on the supply of ecosystem services. In this thesis, we develop an original combination of advanced molecular approaches and more traditional methods in order to elucidate trophic interaction network within the community of carabid beetles in agricultural areas. The carabid beetles can significantly contribute to the service of biological control, but their contribution and beneficial conditions are difficult to assess because of their opportunistic and plastic feeding behavior. A without a priori investigation of carabid diet at community level in a typical agricultural landscape reveals a resource partitioning between groups of species. Additional experimental studies in laboratory conditions indicate that interspecific competition could be the mechanism generating this partitioning. From a fundamental point of view, these results suggest a preponderance of deterministic processes (niche partitioning) compared to neutral processes (environmental stochasticity) to explain the coexistence of species. From an applied point of view, the importance of the resource in structuring carabid communities provides a potential lever of action for the development of efficient management strategies optimizing carabid function as crop auxiliaries
Auclair, Etienne. "Réseau bayésien dynamique étiqueté : cadre et apprentissage de structure pour application aux réseaux écologiques". Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30002.
Pełny tekst źródłaAn ecological network represents the interactions between living species within an ecosystem. The knowledge of the structure of such a network is an important challenge in the field of ecology.This task can be realized by inference methods : a set of methods that uses ecological observations data (species abundance, presence or absence of species...) in order to learn the interactions mathematically, by the exploitation of the effect of these interactions on the observed data.This thesis describes a case where the ecological data we dispose of are only data of presence/absence of species observed at different moments. The goal is to develop a method that exploits those kind of data in order to learn the interaction between these species. The main difficulty is that binary variables carry little information. Expert knowledge on the system is used to help learning the network's structure.We use the framework of dynamic Bayesian network : temporal presence/absence data are modeled as the realization of a set of dynamic random variables whose dependencies are described by an oriented graph. Such a model can be simplified using expert knowledge.This thesis describes a particular model of "labelled" dynamic Bayesian network. In this model, the graph is defined by a small number of different types of interactions that constitute a set of labels attributed to the edges of the graph.This model can describe several phenomena where an information or a perturbation can be propagated by contact (rumour, disease, forest fire....)This model describes the presence or absence probabilities of each species as a function of the number of interactions of each label this species is subject to. This model allows to describe every presence/absence probability of species using a small number of parameters independent from the network's structure. This is the framework used for the modeling of species dynamics within an ecological network : the information propagated is the presence or the absence of a species, knowing the interaction between the species of the network. Then, we describe the processes we use for learning the structure of a labelled dynamic Bayesian network using time series of binary variables. This 'Estimation-Restoration' algorithm alternates two steps : a phase of parameter estimation knowing the structure, and a phase of structure learning knowing the parameters. This last step can be complex. It is done by solving a integer linear programming problem. This allows to use efficient existing tools for solving those kind of problems. Moreover, we can easily add expert knowledge by the form of linear constraints. This process has been used on a particular case study :the observation of arthropods species trapped in experimental fields in the united kingdom. In order to highlight the differences between the different crops, different networks have been learnt. Finally, we compare the learnt network with others, learnt with different learning methods on the same data
Manincor, Natasha de. "Ecologie des plantes et des pollinisateurs dans les prairies calcaires le long d'un gradient latitudinal en France : diversité des espèces et structure des réseaux d'interaction plantes-pollinisateurs". Thesis, Lille 1, 2019. http://www.theses.fr/2019LIL1R024/document.
Pełny tekst źródłaIn the current context of biodiversity crisis and the associated risks of ecosystem service failure, plant-pollinator networks are among the most studied mutualistic networks. Without pollinators, many plants could not reproduce and set seed, and 70% of agricultural production directly depends on them. However, pollinating insects constitute some of the terrestrial taxa most affected by global changes. As such, understanding plant-pollinator networks is of particular relevance if we are to prevent catastrophic disruption of pollination interactions and associated ecosystem services. In plant-pollinator networks, species need to be present in the same site and at the same moment for interactions to occur. In France, plant and pollinator abundance, richness and presence differ along the latitudinal gradient, which correspond to natural variations in biodiversity, and these variations could potentially affect network structure. Moreover, interaction networks are often reported based on temporally aggregated data, but in truth pollination interactions are not static and vary in time, since different plant and pollinator species display different phenologies. Large datasets on plant-pollinator interactions which comprise the entire flowering season or multiple years and allow relevant comparisons among networks along environmental gradient are rare. Due to their complexity and variation among years, most studies of mutualistic networks have focused on predicting and comparing classic network metrics which are all influenced by network size, i.e. the number of plant and insect species. Furthermore, most of these networks are based on interactions observed in the field, and thus some existing links between species remain unobserved. As such, visit-based networks represent a subsample of possible interactions, which call for the development of new methodological approaches to better explore the ecological processes determining species interactions. The general aim of this study is to understand and help predict the effects of environmental changes on plant and pollinator communities by studying plant-pollinator associations along an environmental gradient. Here, I provide and analyse a new database made of geo-localized data characterizing plant-pollinator associations at the species level, spatial variation in community structure and trait assemblage, focusing on six different calcareous grasslands along a latitudinal gradient in France. I first compared the taxonomical diversity variation in space (between and within region) and time (along the season). Then, I used a new methodological approach to compare networks of different size and to study the consequences of environmental gradients on plant-pollinator interaction probability. To understand how much distorted is our vision of plant-pollinator networks sampled following classic methods, I built more complete interaction networks using the pollen found on insects. Finally, I studied the mechanism behind geographical variation of floral scents and among-populations differences linked to the variation in the pollinator community. Because of the complexity and variation of plant-pollinator interactions, our study highlighted the importance to consider the entire flowering season and insects flying period, using species-level identifications, to disentangle the ecological species' role and the network variations. The use of new methodological approach allowed us to make networks comparison along the environmental and diversity gradient avoiding data circularity. The high amount of data provided in this thesis permitted to make comparisons at different level, from the entire network to species-specific variation among-populations
Części książek na temat "Écologie – Réseaux d'interactions – Environnement"
AUBERT, Julie, Pierre BARBILLON, Sophie DONNET i Vincent MIELE. "Modèles à blocs latents pour la détection de structures dans les réseaux écologiques". W Approches statistiques pour les variables cachées en écologie, 131–50. ISTE Group, 2022. http://dx.doi.org/10.51926/iste.9047.ch6.
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