La mer Méditerranée est un hotspot de biodiversité sous diverses influences où plusieurs perturbations agissent en synergie: réchauffement climatique, perte d'habitats et surpêche menacent la biodiversité marine et perturbent les équilibres écosystémiques. Afin d'assurer une gestion durable des écosystèmes marins côtiers, conformément aux prérogatives de l'Approche Ecosystémique des Pêches, il est nécessaire d'étudier les conséquences de ces perturbations sur les populations exploitées. Or, malgré la multiplicité des études relatives au changement global en Méditerranée, les conséquences écosystémiques de ces changements demeurent mal connues. Dans cette thèse, le Golfe de Gabès a été choisi comme modèle d'étude en raison des nombreuses perturbations qui y sont rencontrées et qui en font l'archétype de tendances plus généralisées en Mer Méditerranée. Cette thèse se propose d'abord de replacer l'écosystème du Golfe de Gabès dans son contexte biogéographique à travers l'étude de la phylobiogéographie des assemblages des poissons côtiers méditerranéens et la modélisation de la structure et du fonctionnement de l'écosystème du Golfe de Gabès. Par la suite, nous proposons de modéliser, en utilisant des modèles de niches écologiques, les modifications potentielles futures des assemblages biogéographiques d'espèces exploitées soumises aux changements climatiques et à la perte d'habitat, ainsi que les conséquences trophiques de ces modifications. En prenant en compte la taxonomie et l'histoire évolutive des espèces, nous avons mis en évidence le niveau de séparation entre les assemblages méditerranéens en proposant une nouvelle délimitation biogéographique du plateau continental. Par ailleurs, l'exploration des dissimilarités phylogénétiques à l'échelle des côtes tunisiennes a mis en évidence quatre zones biogéographiques majeures présentant une faible congruence avec le zonage adopté pour la gestion de la pêche en Tunisie. Les projections des futures aires de répartition des 60 principales espèces exploitées du Golfe de Gabès, grâce à l'implémentation du modèle climatique NEMOMED8, révèlent que pour la fin du siècle, 34 espèces pourraient contracter leurs aires de répartition parmi lesquelles 12 espèces pourraient s'éteindre à l'échelle du Golfe. Par ailleurs, en combinant des scénarios de régression d'herbier et de changement climatique, les projections montrent que les magnitudes des modifications d'aires de répartition induites par le changement climatique sont plus larges que celles résultant de la perte d'habitat. La mise en place d'un modèle trophique Ecopath nous a permis de décrire la structure et le fonctionnement de l'écosystème du Golfe de Gabès et de le comparer avec d'autres écosystèmes méditerranéens exploités. Ce modèle a intégré un large éventail d'espèces depuis le phytoplancton jusqu'aux top-prédateurs ainsi que les principales activités de pêche opérant dans la zone. Les résultats du modèle mettent en évidence que le chalutage benthique est l'activité ayant les conséquences écosystémiques les plus étendues avec un fort impact sur certaines espèces démersales exploitées. Enfin, pour étudier les conséquences trophiques des modifications des distributions spatiales des espèces exploitées, nous avons reconstruit les réseaux trophiques au sein des assemblages d'espèces en nous fondant sur la relation positive liant la taille du prédateur à celle de sa proie. Nous avons ainsi pu prédire les réseaux trophiques actuels et projeter les modifications potentielles de leurs structures. Nous avons constaté qu'une grande partie du Golfe pourrait connaître une augmentation de la connectance et un allongement des voies trophiques moyennes qui s'accompagnent d'une diminution du nombre de proies par prédateur et du nombre de prédateurs par proie. Cette thèse est une ouverture vers la compréhension du rôle de la biodiversité dans le maintien du fonctionnement des écosystèmes. / The Mediterranean Sea is a marine biodiversity hot spot highly affected by several sources of disturbances interacting synergistically: global warming, habitat loss and overfishing threaten marine biodiversity and disrupt the ecosystem balance. To ensure a sustainable management of coastal marine ecosystems according to the Ecosystem Approach to Fisheries, it is necessary to study the ecosystem responses to these disturbances. However, despite the variety of global change studies in Mediterranean areas, ecosystems responses to these changes remain poorly understood and particularly at the southern part of the Mediterranean Sea. In this PhD thesis, the Gulf of Gabes was chosen as study area since it is one of the most affected regions by global change which makes it a mesocosm model of more regional patterns that occur in the Mediterranean Sea. In this study, as a first step, we replaced the Gulf of Gabes in its biogeographic and ecosystem regional context. This was achievied through a phylogenetic-based delineation of biogeographical species pools of coastal Mediterranean fishes and using an ecosystem model to describe its structure and functioning in comparison with other Mediterranean ecosystem model properties. We therefore projected potential future geographic ranges and assemblages composition of biogeographical exploited species pool according to global warming and habitat loss scenarios. Then we assessed their effects on food web structure. Taking into account the taxonomy and inter-species evolutionary relationships, we generate a new bioregionalisation of the continental shelf based on the turnover of lineages. Our results showed that climate is the major driver of species distribution and assemblage's composition. In addition, the exploration of phylogenetic dissimilarity across the Tunisian coast highlighted four major biogeographic areas showing a low spatial congruence with zoning used for fisheries management in Tunisia.Projected range shifts of the 60 main exploited species of the Gulf of Gabes through the implementation of a new climate model (NEMOMED8) revealed that, by the end of the century, 34 species could contract their ranges including 12 species that could become locally extinct across the Gulf of Gabes. Furthermore, by combining Posidonia meadows loss scenarios and climate change projections, our results showed that the magnitudes of the changes range induced by climate change are larger than those resulting from the loss of habitat.The Ecopath mass-balance model allowed us to describe the structure and functioning of the ecosystem of the Gulf of Gabes in comparison with other Mediterranean ecosystems. These models encompass the entire trophic spectrum from phytoplankton to higher trophic levels as well as the main fishing activities in the area. The model results showed that, among the fishing activities studied, bottom trawling was identified as the activity having the widest-ranging impacts across the different functional groups and the largest impacts on some commercially-targeted demersal fish species. Finally, to study the effects of species range shift on food web structure, we used a new methodology to infer trophic interactions between species. Based on the robust relationship between the size of prey and predators, we predicted the current food webs and project potential changes in their structures. We found that a significant portion of the Gulf of Gabes would face an increase of connectance and an extension of trophic pathways in parallel with a decrease in the number of prey per predator and the number of predators per prey. This PhD thesis paves the way towards the understanding of the role of biodiversity in maintaining ecosystem functioning.

<p>U radu je izvr&scaron;ena podela 572 registrovane vrste osolikih muva sa područja jugoistočne Evrope na funkcionalne grupe, na osnovu registrovanih funkcionalnih karaktera. Za<br />odabrane 44 endemske i nativne ne-endemske vrste koje su svojim klimatskim ni&scaron;ama ograničene na istraživani prostor, kreirane su mape sada&scaron;nje i buduće potencijalne distribucije (za dva perioda, 2041 -2060 i 2061-2080) upotrebom MAXENT algoritma. Na osnovu dobijenih mapa, izračunata je potenijalna promena areala za odabrane vrste, čime je procenjen efekat klimatskih promena na distribuciju vrsta sirfida. Detektovane su vrste koje će najvi&scaron;e biti pogođene klimatskim promenama, kao i prostori sa najvećim potencijalnim bogatstvom vrsta u budućnosti i područja predviđena da će izgubiti deo diverziteta sirfida. Pokazano je da vrste sa ograničenim arealom neće u budućnosti iskusiti veće smanjenje areala u odnosu na &scaron;iroko rasprostranjene vrste. Takođe, na osnovu mapa potenicijalne sada&scaron;nje distribucije i procenjene retkosti vrsta, izvr&scaron;ena je prioretizacija područja značajnih za opstanak osolikih muva u jugoistočnoj Evropi. Primenom linearnih regresionih i linearnih modela sa me&scaron;ovitim efektom ispitana je međuzavisnost&nbsp; funkcionalnih karaktera vrsta i procenjene promene veličine areala. Definisani su&nbsp; funkcionalni karakteri koji utiču na promenu veličine areala osolikih muva. Ustanovljeni koncept može biti upotrebljen za detekciju vrsta koje se jo&scaron; uvek ne smatraju ugroženim, ali zbog svojih biolo&scaron;ko-ekolo&scaron;kih karakteristika imaju potencijal da to postanu, te stoga zaslužuju pažnju konzervacionista. Dobijeni rezultati mogu u velikoj meri poslužiti za kreiranje sistematskog konzervacionog plana za očuvanje osolikih muva na teritoriji jugoistočne Evrope.</p> / <p>In this paper, the division of 572 species of hoverflies registered in Southeast Europe into functional groups was conducted, based on their functional traits. For 44 selected&nbsp; endemic and native non-endemic species that have their climatic niches limited in the study area, maps of current and future potential distributions were created (for the periods, 2041-2060 and 2061-2080) using MAXENT algorithm. Based on the obtained &nbsp; maps, changes in potential area of occupancy were calculated, in order to estimate the &nbsp; effect of climate change on the distribution of hoverfly species. Species that will be most affected by climate change were detected, as well as the areas with the greatest potential species richness in the future and areas predicted to lose part of the diversity of hoverflies. It is shown that species with limited distribution in the future will not experience a greater reduction of its area in relation to the widespread species. Also, based on the current maps of potential distribution and assessed rarity of species,priority areas important for the survival of hoverflies in Southeast Europe were established. By using linear regression and linear mixed effect models, the interdependence between functional traits and the estimated changes in the range size was tested. Traits affecting the changes in range size of hoverflies were determined. The established concept can be used for the detection of species that are not yet considered endangered, but because of their biological and ecological traits have the potential to become threatened, and therefore deserve the attention of conservationists.&nbsp; This results can largely be used to create a systematic conservation plan for the preservation of hoverflies in Southeast Europe.</p>

Estamos vivenciando o que pode ser considerado como o sexto evento de extinção global da Biodiversidade. Os anfíbios são os vertebrados mais ameaçados do mundo e ainda o número de espécies ameaçadas pode estar subestimado, pois 22% estão classificadas na categoria Dados Insuficientes (DD). O Brasil possui alta riqueza de anfíbios, porém inúmeras lacunas de conhecimento dificultam a elaboração de listas completas e prejudica a avalição do estado de conservação e o planejamento da conservação dos anfíbios brasileiros. Assim, visando contribuir efetivamente no direcionamento das ações de conservação dos anfíbios brasileiros avaliamos a influência da atitude de especialistas na classificação das espécies, e também identificamos e adaptamos ferramentas para melhor explorar os dados de distribuição disponíveis sobre as espécies DD. Foi proposto um framework de modelagem adaptativa para lidar com a escassez de dados de distribuição destas espécies e incluir a capacidade de dispersão nos modelos de distribuição de espécies. Além disso, para preencher lacunas de conhecimento dos aspectos biológicos e ecológicos das espécies de anfíbios da Mata Atlântica considerados como DD foi realizado busca na literatura e em coleções científicas, bem como a indicação de áreas prioritárias para obter informações adicionais sobre essas espécies. Identificamos que a linha de atuação dos avaliadores influencia na determinação da categoria DD, aumentando ou reduzindo a probabilidade de classificar uma espécie nesta categoria. Com isso, ressalta-se a necessidade de compor equipes multidisciplinares para avaliar o estado de conservação das espécies. O framework aqui proposto tem o potencial de inovar o processo de modelagem com poucos dados disponíveis a partir da inclusão de um dos aspectos mais difíceis de mensurar, a capacidade de dispersão da espécie. O conjunto de informações sobre as espécies DD da Mata Atlântica aumentou consideravelmente com o levantamento de dados e os modelos de distribuição de espécies, e ainda foi possível obter áreas prioritárias para aumentar o conhecimento empírico em mais de 180 municípios. Dentre as categorias de unidades de conservação mais frequentes como áreas prioritárias, destacam-se as Reservas Particulares do Patrimônio Natural nas regiões nordeste e sul, e as Áreas de Preservação permanente na região sudeste. Os resultados deste estudo contribuem efetivamente para o processo de avaliação do estado de conservação dos anfíbios brasileiros, especialmente das espécies DD da Mata Atlântica, de modo que possa ser utilizado no planejamento sistemático da conservação deste grupo. As abordagens utilizadas neste estudo podem servir de modelos para outras espécies ou grupos taxonômicos, reduzindo lacunas e incertezas no processo de avaliação do estado de conservação de espécies. / We are experiencing what could be considered as the sixth global biodiversity extinction event. Amphibians are the most threatened vertebrates in the world, and still the number of endangered species might be underestimated because 22% are classified in the category data deficient (DD). Brazil has a high richness of amphibians, but several knowledge gaps make it difficult to compile complete lists and impair the evaluation of the conservation status and the conservation planning of Brazilian amphibians. Thus, in order to contribute effectively in directing conservation actions for Brazilian anphibians we evaluated the influence of experts attitude on species classification, and also identified and adapted tools to better explore the available data on DD species. It was proposed an adaptive modeling framework to deal with the scarcity of these species distribution data and include dispersion capacity in species distribution modeling. In addition, to fill knowledge gaps of biological and ecological aspects of amphibian species of the Atlantic forest considered as DD literature search and in scientific collections were conducted, as well as the indication of priority areas for gathering additional information about these species. We identified that the line of action of the evaluators influences the determination of the DD category, increasing or reducing the probability of classifying a species in this category. Thereby, it`s emphasized the need to compose multidisciplinary teams to assess species conservation status. The framework proposed here has the potential to innovate the modeling process through the inclusion of one of the most difficult aspects to be measured, the species dispersion capacity. The set of information about DD species of the Atlantic forest has increased considerably with the survey and the species distribution models, and it was still possible to obtain priority areas to increase the empirical knowledge in more than 180 municipalities. Among the categories of protected areas most frequent as priority areas, Private Reserves stands out in the Northeast and South regions and Areas of Permanent Preservation the Southeast. Results of this study contribute effectively to the process conservation status assessment of amphibians, especially DD species from the Atlantic forest, so that it could be used in conservation systematic planning of this group. The approaches used in this study could serve as models for other species or taxonomic groups, reducing gaps and uncertainties in the process of evaluation of species conservation status.

Atualmente estamos presenciando mudanças climáticas ao nível global sem precedentes, as quais se tornarão mais severas no decorrer dos anos, podendo causar danos irreversíveis à biodiversidade. Como as espécies irão reagir a essas mudanças e quais ações de conservações devem ser tomadas estão entre os tópicos mais significantes na ecologia atualmente. As mudanças climáticas têm sido apontadas como uma das principais causas de reduções (e alterações) na distribuição geográfica e abundância de muitas espécies, e até mesmo a extinção. Os modelos de nicho ecológico têm sido uma ferramenta muito utilizada a fim de compreender como a distribuição das espécies pode ser afetada pelas mudanças climáticas. Os modelos fornecem valiosas informações sobre o potencial efeito das mudanças climáticas na distribuição futura das espécies, podendo assim ser usado para a compreensão de como e quais espécies podem ser mais afetadas, além dos locais adequados para sua conservação. Uma vez que informações importantes sobre os organismos não são incorporadas nos modelos, é fundamental o conhecimento sobre a biologia e história natural das espécies para a interpretação dos resultados. No presente estudo é aprestada uma revisão sobre o atual estado de conhecimento das quatro espécies do gênero Eunectes em relação à distribuição geográfica, uso do habitat e microhabitat, atividade diária e sazonal, reprodução, tamanho corporal, dieta e status de conservação. Adicionalmente aspectos da história natural de uma população da sucuri verde, Eunectes murinus, foram estudados em locais florestados, na cidade de Bonito, MS, e aqui são apresentados dados sobre movimentação, uso do microhabitat, reprodução e dieta. Ainda, foram desenvolvidos modelos de nicho climático para cada uma das quatro espécies a fim de entender os possíveis impactos das mudanças climáticas nessas espécies em dois cenários futuros. Foram assumidas duas abordagens de dispersão, com livre dispersão e sem dispersão. A partir dos resultados foi possível reconhecer padrões na biologia das espécies de Eunectes, identificar as principais lacunas de conhecimento e sugerir onde esforços em pesquisa devem ser focados. Além disso, importantes dados sobre a história natural da sucuri verde (E. murinus) foram registrados. Foi observado que, em relação à movimentação, dieta e reprodução, aparentemente a espécie mantém o padrão já registrado em estudos anteriores. Entretanto, o uso do microhabitat diferiu substancialmente, tendo sido encontrado um número muito elevado de indivíduos utilizando árvores. As projeções futuras indicam que, para o intervalo entre os anos de 2061-2080, todas as espécies, menos E. notaeus, perderão grande quantidade de hábitat climaticamente adequado, sendo E. deschauenseei a mais afetada (100% de perda com e sem dispersão no pior cenário). Ainda, as análises apontam que haverá uma mudança de local adequado para a potencial ocorrência de três espécies. Sem dispersão, todas as espécies perderão área, sendo que E. beniensis perderá 100% de habitat adequado em ambos os cenários de alterações climáticas. As informações geradas por este estudo ajudam a melhorar a compreensão da ecologia, história natural e distribuição das espécies do gênero, bem como indica quais as espécies poderão ser mais prejudicadas pelas mudanças climáticas em curso. Finalmente, os resultados fornecem subsídios para a formulação de planos de conservação, indicando importantes áreas que poderão servir de refúgio climático para as espécies / We are currently witnessing unprecedented global climate change, which will become more severe over the years and can cause irreversible damage to biodiversity. How species will react to these changes and what conservation actions should be taken are among the most significant topics in ecology today. Climate change has been identified as a major cause of reductions (and changes) in geographic distribution and abundance of many species, and even extinction. Ecological niche models have been widely used in order to understand how the distribution of species can be affected by climate change. The models provide valuable information on the potential effect of climate change on the future distribution of species and can be used to assess how and which species may be most affected, as well as the appropriate sites for their conservation. Since important information about the species is not incorporated into the models, the knowledge about their biology and natural history is crucial for interpretating the results. In the present study a review is presented on the current state of knowledge about the four species of the genus Eunectes in relation to geographic distribution, habitat and microhabitat use, daily and seasonal activity, reproduction, body size, diet and conservation status. In addition, natural history aspects of a green anaconda (E. murinus) population were studied in forested sites in the Bonito municipality, Mato Grosso do Sul state, Brazil, where data on movement, microhabitat use, reproduction and diet are presented. Furthermore, climate niche models were developed for each of the four species in order to understand the possible impacts of climate change under two future scenarios.Two dispersion approaches were performed, with \"free dispersion\" and \"no dispersion\". It was possible to recognize patterns in the biology of Eunectes species, identify the main knowledge gaps and to suggest where research efforts should be focused. Moreover, important data on the natural history of the green anaconda (E. murinus) were recorded. It was observed that, in relation to movement, diet and reproduction, the species apparently maintains the pattern recorded in previous studies. However, the use of the microhabitat differed substantially, with a very high number of individuals being found on trees. Future projections indicate that, for the interval between the years 2061-2080, all species, but E. notaeus, will lose a large amount of climatically suitable habitat, with E. deschauenseei being the most affected (100% loss with and without dispersion in the worst scenario). Future projections also indicate that there will be a shift in the distribution of suitable habitat for the potential occurrence of three species. Without dispersion, all species will lose area, and E. beniensis will lose 100% of suitable habitat in both climate change scenarios. The information generated by this study helps to improve the knowledge about the ecology, natural history and distribution of the species of Eunectes, as well as indicates which species may be most affected by ongoing climate change. Finally, the results provide subsidies for the formulation of conservation plans, indicating important areas that could serve as a climate refuge for the species

A modelagem de distribuição de espécies é uma técnica cuja finalidade é estimar modelos baseados em nichos ecológicos. Esses modelos podem auxiliar nos processos de tomadas de decisões, no planejamento e na realização de ações que visem a conservação e a preservação ambiental. Existem diversas ferramentas projetadas para modelagem de distribuição de espécies, dentre elas o framework openModeller, na qual este trabalho está inserido. Várias técnicas de Inteligência Artificial já foram utilizadas para desenvolver algoritmos de modelagem de distribuição de espécies, como Entropia Máxima. No entanto, as ferramentas estatísticas tradicionais não disponibilizam pacotes com o algoritmo de Entropia Máxima, o que é comum para outras técnicas. Além disso, apesar de existir um software gratuito específico para modelagem de distribuição de espécies com o algoritmo de Entropia Máxima, esse software não possui código aberto. Assim, a base deste trabalho é a investigação acerca da modelagem de distribuição de espécies utilizando Entropia Máxima. Desta forma, o objetivo principal é definir diferentes estratégias para o algoritmo de Entropia Máxima no contexto da modelagem de distribuição de espécies. Para atingir esse objetivo, foram estabelecidos um conjunto de alternativas possíveis a serem exploradas e um conjunto de métricas de avaliação e comparação das diferentes estratégias. Os resultados mais importantes desta pesquisa foram: um algoritmo adaptativo de Entropia Máxima, um algoritmo paralelo de Entropia Máxima, uma análise do parâmetro de regularização e um método de seleção de variáveis baseado no princípio da Descrição com Comprimento Mínimo (MDL Minimum Description Length), que utiliza aprendizagem por compressão de dados. / Species distribution modeling is a technique the purpose of which is to estimate models based on ecological niche. These models can assist decision making processes, planning and carrying out actions aiming at environmental conservation and preservation. There are several tools designed for species distribution modeling, such as the open- Modeller framework, in which this work is inserted. Several Artificial Intelligence techniques have been used to develop algorithms for species distribution modeling, such as Maximum Entropy. However, traditional statistical tools do not offer packages with the Maximum Entropy algorithm, which is common to other techniques. Furthermore, although there is specific free software for species distribution modeling with the Maximum Entropy algorithm, this software is not open source. The basis of this work is the investigation of the species distribution modeling using Maximum Entropy. Thus, its aim is to define different strategies for the Maximum Entropy algorithm in the context of the species distribution modeling. For this, a set of possible alternatives to be explored and a set of metrics for evaluation and comparison of the different strategies were established. The most important results were: an adaptive Maximum Entropy algorithm, a parallel Maximum Entropy algorithm, an analysis of the regularization parameter and a variable selection method based on the Minimum Description Length principle, which uses learning by data compression.

Les modifications environnementales qui affectent aujourd'hui les milieux marins recouvrent des problématiques scientifiques et sociétales majeures, d'autant que ces changements devraient s'accélérer au cours du 21ème siècle. Comprendre et anticiper la réponse de la biodiversité marine à ces changements représente un enjeu scientifique d'actualité. Les approches biogéographiques et macroécologiques constituent un cadre scientifique dans lequel il est possible d'étudier, de décrire, et de comprendre les motifs de distribution des espèces à large échelle et d'estimer leur évolution possible face aux changements environnementaux. C'est notamment le cas dans l'océan Austral où les effets du changement climatique se font déjà sentir et où les modifications environnementales associées pourraient avoir des effets profonds sur la structure et le fonctionnement des écosystèmes. Malgré de récents efforts d'échantillonnage, nos connaissances sur la distribution des espèces dans l’océan Austral comptent encore de nombreuses lacunes attribuables au caractère récent des découvertes, à l'isolement et à l'éloignement de cet océan d'accès difficiles. Dans ce contexte, les objectifs de cette thèse consistaient à mieux comprendre les motifs de distribution d'espèces à l’échelle de l’océan Austral, à mettre en évidence les facteurs qui en sont à l’origine et enfin, à évaluer l’impact du changement climatique sur leur distribution. Pour cela, différents types de modèles de niche écologique (MNE) ont été employés. Les échinides (oursins), organismes communs des communautés benthiques de l’océan Austral ont servi de modèle d'étude pour ce travail. / Current environmental changes, which impact marine environments, cover major scientific and societal issues, especially as these environmental changes are expected to accelerate along the 21st century. Understanding and forecasting the response of marine biodiversity to these changes is a pregnant scientific issue. Biogeographic and macroecological approaches provide a scientific framework for that purpose. They allow describing and understanding species distribution patterns at large spatial scale as well as estimating their potential shift with regards to environmental change. This is particularly true in the Southern Ocean, where the effects of climate change are already occurring and where environmental changes could have a deep and manifold impact on the structure and functioning of marine ecosystems. Despite recent sampling efforts, our knowledge of the Southern Ocean species distributions still faces many shortcomings due to the rather recent discovery of this ocean, its isolation and remoteness along with difficult access conditions. In this context, the aims of this thesis are to better understand the factors that drive species distribution patterns at the Southern Ocean scale, and to assess the impact of climate change on their distribution. For this purpose, different types of Species Distribution Models (SDM) have been used. Echinoids (sea urchins), which are common organisms of benthic communities in the Southern Ocean, have been used as a biological model for this work.

What explains the geographic distribution of pathogens? Better understanding and characterising disease patterns will help scientists to identify areas likely to host future epidemics and epizootics and to prioritise surveillance and intervention. However, the use of disease surveillance data to assess the risk of transmission and generate risk maps raises conceptual and methodological issues. Indeed, pathogens and more particularly viruses aren't ”species” like others that live in the open environment and must be studied with methods and concepts of their own. Avian influenza (AI), a disease caused by a virus infecting bird populations, has been selected to study these issues. AI has a major economic impact on the poultry industry in many countries, raises concerns of livelihood in low and middle-income countries, and represents a major concern for human health. The aim of this PhD thesis was to improve the knowledge on the spatial epidemiology of AI in different settings and conditions (i). For this, recent epizootics caused by the subtypes A (H5N1) and A (H7N9) were selected as case studies. First, highly pathogenic subtypes of the A (H5N1) virus have been studied in poultry farms (ducks and chickens) at different spatial scales: at the continental scale and the regional scale in the Mekong (Cambodia, Laos, Vietnam, Thailand) and the Nile Delta in Egypt. All these cases occurred between 2003, the date on which the virus starts to spread outside China, and 2015; the HPAI A (H5N1) subtypes are still reported today in many countries. Human infections caused by the A (H7N9) virus in China from March 2013 to 2017 were also studied. Studied different AI subtypes at different spatial scales within different host species also allowed to develop a conceptual model of AI transmission and to discuss the issue of the transferability of results in epidemiology (ii). Lastly, this PhD thesis leads to a discussion about the transfer of methods and concepts from ecology to spatial epidemiology, with a particular emphasis on their possible limitations (iii). / Doctorat en Sciences agronomiques et ingénierie biologique / info:eu-repo/semantics/nonPublished

Les grands carnivores recolonisent l’Europe grâce à une augmentation des forêts et des populations d'ongulés sauvages ainsi que des mesures de conservation. Or, les carnivores entrent en interactions avec les activités humaines telles que l’élevage. Quantifier leur distribution peut aider à situer les impacts sur ces activités. Ces espèces sont très mobiles, difficiles à observer et vivent à de faibles densités. La modélisation de leur distribution présente plusieurs défis en raison 1) de leur détectabilité imparfaite, 2) de leur distribution dynamique dans le temps et 3) du suivi à grande échelle basé sur la collecte de données opportunistes sans mesure formelle de l'effort d'échantillonnage. Dans cette thèse, nous nous sommes concentrés sur deux espèces de grands carnivores, le loup et le lynx boréal, pour développer les méthodologies liées à la modélisation de la distribution d’espèces. Nous avons exploré l’application des modèles d’occupancy dans le contexte du suivi des grands carnivores en Europe. Ces modèles établissent le lien entre la présence d’une espèce et l’environnement dans le but d’établir la proportion d'une zone d'étude que l’espèce occupe, tout en prenant en compte une détectabilité imparfaite.Plus précisément, nous avons d'abord évalué la dynamique de la distribution des loups en France de 1994 à 2016, tout en prenant en compte leur détection imparfaite. Nous avons montré l'importance de prendre en compte l’effort d'échantillonnage variant dans le temps et dans l'espace à l’aide de de modèles d’occupancy dynamique.Deuxièmement, comme des faux positifs peuvent être présents lors de la surveillance d'espèces rares, nous avons développé un modèle dynamique d’occupancy qui tenait compte simultanément des faux négatifs et des faux positifs pour analyser conjointement des données qui contenaient à la fois des détections certaines et des détections incertaines. L'analyse des données sur le lynx boréal dans les pays alpins a suggéré que l'incorporation de détections incertaines produisait des estimations des paramètres écologiques plus précises.Troisièmement, nous avons développé un modèle qui prenait en compte l'hétérogénéité de la détection tout en traitant les faux positifs. En appliquant notre nouvelle approche au loup en France, nous avons démontré que l'hétérogénéité de la détection du loup était principalement due à un effort d'échantillonnage hétérogène dans l'espace.Quatrièmement, pour traiter des sources de données multiples, nous avons développé un modèle de processus ponctuel de Poisson qui permettait l'inclusion de différentes sources de données lors de la construction des SDMs. Nous avons montré comment la combinaison des données sur la distribution permettait d’optimiser un suivi en répondant à la question de savoir quelle(s) source(s) d'information apporterait l’essentiel de l’information lors du suivi du lynx en Norvège.Cinquièmement, pour comprendre les mécanismes sous-jacents de la colonisation des loups en France, nous avons développé un cadre statistique pour estimer l'occupation spatio-temporelle et la dynamique des effectifs en utilisant le cadre de diffusion écologique. Nous avons montré le potentiel de notre approche pour prédire la distribution future potentielle du loup à court terme, un élément qui pourrait contribuer à cibler des zones de gestion ou se concentrer sur des zones de conflit potentiel.Dans l'ensemble, nos travaux montrent que les données opportunistes peuvent être analysées à l'aide de modèles de distribution d’espèces qui prennent en compte les contraintes liées au type de suivi utilisé pour produire les données. Nos approches peuvent être utilisées par les gestionnaires pour optimiser la surveillance des grands carnivores, cibler des zones de présence potentielles et contribuer à proposer des mesures destinées à atténuer les conflits. / Large carnivores are recovering in Europe, due to an increasing forest cover, ungulate population and conservation measures. Tthis return poses challenges as carnivores can interact with livestock farming. Assessing their distributions can help to predict and mitigate conflicts with human activities. Because large carnivores are highly mobile, elusive and live at very low density, modeling their distributions presents several challenges due to 1) their imperfect detectability, 2) their dynamic ranges over time and 3) their monitoring at large scales consisting of opportunistic data without a formal measure of the sampling effort. In this thesis, we focused on two carnivore species, wolves (Canis lupus) and Eurasian lynx (Lynx lynx), to develop the methodological aspects related to the modelling of species distributions. We considered the application of occupancy models in the context of monitoring large carnivores in Europe. These models allow the establishment of a link between the species’ presence and environmental covariates while accounting for imperfect detectability, in order to establish the proportion of a study area occupied by the species.We first assessed wolf range dynamics in France from 1994 to 2016, while accounting for species imperfect detection and showed the importance of accounting for time- and space-varying sampling effort using dynamic site-occupancy models.Second, acknowledging that false positives may occur when monitoring rare species, we showcased a dynamic occupancy model that simultaneously accounts for false negatives and positives to jointly analyze data that include both unambiguous detections and ambiguous detections. The analysis of data on the Eurasian lynx in Alpine countries suggested that incorporating ambiguous detections produced more precise estimates of the ecological parameters.Third, we developed a model accounting for heterogeneity in detection while dealing with false positives. Applying our new approach to a case study with grey wolves in France, we demonstrated that heterogeneity in wolf detection was due to a heterogeneous sampling effort across space.Fourth, to deal with multiple data sources, we developed a Poisson point process approach which allows the inclusion of different data sources when building SDMs. By doing so, we also answered the question about which source(s) of information would provide most of the information when monitoring the lynx in Norway.Fifth and finally, to understand the underlying mechanisms of the colonization of wolves in France, we developed a statistical framework for estimating spatiotemporal occupancy and abundance dynamics using the ecological diffusion framework. We demonstrated the potential of our approach to predict the potential future distribution of wolves in the short term, an element that could contribute to target management areas or focus on areas of potential conflict.Overall our work shows that opportunistic data can be analyzed with species distribution models that control for issues linked to the type of monitoring used to produce the data. Our approaches have the potential for being used by decision-makers to optimize the monitoring of large carnivores and to target sites where carnivores are likely to occur and mitigate conflicts.

A modelagem de distribuição de espécies é uma técnica cuja finalidade é estimar modelos baseados em nichos ecológicos. Esses modelos podem auxiliar nos processos de tomadas de decisões, no planejamento e na realização de ações que visem a conservação e a preservação ambiental. Existem diversas ferramentas projetadas para modelagem de distribuição de espécies, dentre elas o framework openModeller, na qual este trabalho está inserido. Várias técnicas de Inteligência Artificial já foram utilizadas para desenvolver algoritmos de modelagem de distribuição de espécies, como Entropia Máxima. No entanto, as ferramentas estatísticas tradicionais não disponibilizam pacotes com o algoritmo de Entropia Máxima, o que é comum para outras técnicas. Além disso, apesar de existir um software gratuito específico para modelagem de distribuição de espécies com o algoritmo de Entropia Máxima, esse software não possui código aberto. Assim, a base deste trabalho é a investigação acerca da modelagem de distribuição de espécies utilizando Entropia Máxima. Desta forma, o objetivo principal é definir diferentes estratégias para o algoritmo de Entropia Máxima no contexto da modelagem de distribuição de espécies. Para atingir esse objetivo, foram estabelecidos um conjunto de alternativas possíveis a serem exploradas e um conjunto de métricas de avaliação e comparação das diferentes estratégias. Os resultados mais importantes desta pesquisa foram: um algoritmo adaptativo de Entropia Máxima, um algoritmo paralelo de Entropia Máxima, uma análise do parâmetro de regularização e um método de seleção de variáveis baseado no princípio da Descrição com Comprimento Mínimo (MDL Minimum Description Length), que utiliza aprendizagem por compressão de dados. / Species distribution modeling is a technique the purpose of which is to estimate models based on ecological niche. These models can assist decision making processes, planning and carrying out actions aiming at environmental conservation and preservation. There are several tools designed for species distribution modeling, such as the open- Modeller framework, in which this work is inserted. Several Artificial Intelligence techniques have been used to develop algorithms for species distribution modeling, such as Maximum Entropy. However, traditional statistical tools do not offer packages with the Maximum Entropy algorithm, which is common to other techniques. Furthermore, although there is specific free software for species distribution modeling with the Maximum Entropy algorithm, this software is not open source. The basis of this work is the investigation of the species distribution modeling using Maximum Entropy. Thus, its aim is to define different strategies for the Maximum Entropy algorithm in the context of the species distribution modeling. For this, a set of possible alternatives to be explored and a set of metrics for evaluation and comparison of the different strategies were established. The most important results were: an adaptive Maximum Entropy algorithm, a parallel Maximum Entropy algorithm, an analysis of the regularization parameter and a variable selection method based on the Minimum Description Length principle, which uses learning by data compression.

Submitted by PPG Ecologia e Evolu??o da Biodiversidade (eebpg.ciencias@pucrs.br) on 2018-10-16T17:56:11Z No. of bitstreams: 1 Tese - Pereira - Joana.pdf: 10961538 bytes, checksum: b96f5fee6d02e741124bc5a31abdb086 (MD5) / Approved for entry into archive by Sheila Dias (sheila.dias@pucrs.br) on 2018-10-18T12:48:41Z (GMT) No. of bitstreams: 1 Tese - Pereira - Joana.pdf: 10961538 bytes, checksum: b96f5fee6d02e741124bc5a31abdb086 (MD5) / Made available in DSpace on 2018-10-18T13:37:00Z (GMT). No. of bitstreams: 1 Tese - Pereira - Joana.pdf: 10961538 bytes, checksum: b96f5fee6d02e741124bc5a31abdb086 (MD5) Previous issue date: 2018-09-24 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES / Distribution models are considered important tools in biogeography and ecology studies as they allow spatial and temporal extrapolation of species distribution from a set of occurrence data points as function of environmental predictors. In this study, we aimed to propose logistic distribution models for 50 fish species along the Sinos River Basin (Rio Grande do Sul, Brazil), by using altitude and basin area as geomorphological descriptors. Upstream-downstream richness model for entire basin by using multiple and logistic regression was also presented. The dataset derived from several sampling programs performed from 1998 to 2014, comprising 86 sampled locations with fish collections with gillnets, electric fishing or both. Two logistic models were constructed using environmental data of altitude and upstream basin area, testing linear (Model 1) and nonlinear (Model 2) factor responses for each species. Performance of the two models was evaluated using sensitivity, specificity, AUC (Area Under Curve) and TSS (True Skill Statistical). The adjusted models presented sensitivity values ranging from 47,1 to 99,8, specificity from 49,94 to 98,10, AUC from 0,75 to 0,99 and TSS from 0,26 to 0,98. The linear response model, although simpler, proved to be effective in predicting species distribution, as observed in previous studies. The basin area had a positive effect on the distribution of most species according to the linear model, although this was not verified for nonlinear models due to the interaction between variables. In general, the nonlinear model presented higher performance values for the evaluated metrics for the majority of species, but suffered from overfitting and a patchy distribution estimation. The species richness increased along a longitudinal gradient, presenting its maximum value downstream of the basin. Of the four estimated richness models, models with six variables were the ones with the lowest residual variation. / Modelos de distribui??o s?o considerados como ferramentas importantes em estudos de biogeografia e ecologia, pois permitem a extrapola??o espacial e temporal da distribui??o de esp?cies a partir de um conjunto de dados de ocorr?ncia em fun??o de preditores ambientais. Neste estudo, objetivamos propor modelos de distribui??o log?stica para 50 esp?cies de peixes ao longo da bacia do rio dos Sinos (Rio Grande do Sul, Brasil), utilizando altitude e ?rea da bacia como descritores geomorfol?gicos. Modelos de riqueza montante-jusante para toda a bacia usando regress?o m?ltipla e log?stica tamb?m foram propostos. O conjunto de dados derivou de v?rios programas de amostragem realizados de 1998 a 2014, compreendendo 86 locais amostrados com coleta de peixes com redes de emalhar, pesca el?trica ou ambos. Dois modelos log?sticos foram constru?dos utilizando dados ambientais de altitude e ?rea de bacia a montante, testando respostas lineares (Modelo 1) e n?o lineares (Modelo 2) para cada esp?cie. O desempenho dos modelos foi avaliado usando sensibilidade, especificidade, AUC (Area Under Curve) e TSS (True Skill Statistical). Os modelos ajustados apresentaram valores de sensibilidade variando de 47,1 a 99,8, especificidade de 49,94 a 98,10, AUC de 0,75 a 0,99 e TSS de 0,26 a 0,98. O modelo de resposta linear, embora mais simples, mostrou-se eficaz na predi??o da distribui??o de esp?cies, como observado em estudos anteriores. A ?rea da bacia teve um efeito positivo na distribui??o da maioria das esp?cies de acordo com o modelo linear, embora isso n?o tenha sido verificado para os modelos n?o lineares devido ? intera??o entre as vari?veis. Em geral, o modelo n?o linear apresentou valores de desempenho mais altos para as m?tricas avaliadas para a maioria das esp?cies, mas sofreu de hiperajuste e uma estimativa de distribui??o fragmentada. A riqueza de esp?cies aumentou ao longo de um gradiente longitudinal, apresentando seu valor m?ximo a jusante da bacia. Dos quatro modelos estimados de riqueza, os modelos com seis vari?veis foram os que apresentaram a menor amplitude de varia??o dos res?duos.