Les causes évolutives de certaines formes de vie en groupe sont bien identifiées mais pas celles des agrégations de diapause des arthropodes (rassemblements monospécifiques d'adultes dans des sites à localisation constante). Dans cette thèse, j'ai testé si, selon l'hypothèse du lek caché, les arthropodes se rassemblent pour trouver leurs partenaires sexuels chez la coccinelle Hippodamia undecimnotata. J'ai montré que les coccinelles se rassemblent dans des endroits avec un repère proéminent et où le risque de pesticides est faible, puis que les conditions abiotiques dans les sites sont défavorables à la survie des coccinelles. Ensuite, j'ai mis en évidence l'occurrence de nombreux accouplements dans les sites d'agrégation. Enfin, j'ai montré que ces accouplements sont peu coûteux en énergie pour les femelles, qui conservent de l'énergie pour les comportements post-agrégation. Cette thèse atteste que les agrégations de diapause font partie du système de reproduction des arthropodes. / The evolutionary significance of some kinds of group living are well-known, some others such as the diapause aggregations remain poorly known although widespread. In this thesis, I tested if the arthropods form diapause aggregations to find their mates according to the hidden lek hypothesis with the ladybird Hippodamia undecimnotata. By using a Species Distribution Model, I showed that ladybirds aggregate in places with a prominent object and where the risk of being sprayed by pesticides is low. Then, I highlighted that abiotic conditions are unfavourable to ladybirds' survival. In a third part, I found that mating is widespread activity in the aggregation sites. Finally, I showed that energetic costs linked to mating are low, and thus allow the ladybirds to disperse and display post aggregations behaviour. This thesis shows that the diapause aggregations are part of the mating system of the arthropods and that sexual selection can be a driver of the evolution of diapause aggregations.

Understanding species-habitat relationships for endangered species is critical for their conservation. However, many studies have limited value for conservation because they fail to account for habitat associations at multiple spatial scales, anthropogenic variables, and imperfect detection. We addressed these three limitations by developing models for an endangered wetland bird, Yuma Ridgway's rail (Rallus obsoletus yumanensis), that examined how the spatial scale of environmental variables, inclusion of anthropogenic disturbance variables, and accounting for imperfect detection in validation data influenced model performance. These models identified associations between environmental variables and occupancy. We used bird survey and spatial environmental data at 2473 locations throughout the species' U.S. range to create and validate occupancy models and produce predictive maps of occupancy. We compared habitat-based models at three spatial scales (100, 224, and 500 m radii buffers) with and without anthropogenic disturbance variables using validation data adjusted for imperfect detection and an unadjusted validation dataset that ignored imperfect detection. The inclusion of anthropogenic disturbance variables improved the performance of habitat models at all three spatial scales, and the 224-m-scale model performed best. All models exhibited greater predictive ability when imperfect detection was incorporated into validation data. Yuma Ridgway's rail occupancy was negatively associated with ephemeral and slow-moving riverine features and high-intensity anthropogenic development, and positively associated with emergent vegetation, agriculture, and low-intensity development. Our modeling approach accounts for common limitations in modeling species-habitat relationships and creating predictive maps of occupancy probability and, therefore, provides a useful framework for other species.

Orientador: Luís Felipe de Toledo Ramos Pereira / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Biologia / Made available in DSpace on 2018-08-27T11:16:08Z (GMT). No. of bitstreams: 1 Oliveira_IgorSoaresde_D.pdf: 4104401 bytes, checksum: 76046f01be0657270cbc44223cd762b9 (MD5) Previous issue date: 2015 / Resumo: As mudanças climáticas possuem potencial para alterar o funcionamento dos ecossistemas através da extinção de espécies e das conexões entre a biota e o ambiente, alterando os padrões aos quais estamos acostumados e exigindo adaptação. As alterações climáticas terão como uma de suas consequências a elevação oceânica, que pode redesenhar as costas de todos os continentes terrestres e afetar a biota associada. Nesse contexto, sobressaem-se os anfíbios como um grupo sensível que sofre diversas pressões e apresenta declínios populacionais, se destacando como vertebrados mais ameaçados da atualidade, com diversas espécies pouco conhecidas. Sendo assim, nesse trabalho analisamos múltiplos efeitos que dificultam a conservação dos anfíbios. Avaliamos os potenciais efeitos das mudanças climáticas e da elevação oceânica sobre os anfíbios com distribuição costeira. Também desenvolvemos um índice para classificar espécies com dados insuficientes com a finalidade de oferecer uma alternativa para a busca de informações para esses taxa e mudar sua classificação atual. Por fim, analisamos a disponibilidade histórica de clima adequado para uma linhagem endêmica do fungo quitrídio em busca de padrões que pudessem explicar sua distribuição e raridade atuais. Utilizamos ferramentas como modelos de distribuição de espécies e sistema de informação geográfica em busca de respostas às nossas questões. Nossos resultados corroboram as mudanças climáticas como um fenômeno com potencial devastador e alertam para potenciais perigos da elevação oceânica. Além disso, nosso índice para espécies deficientes em dados pode auxiliar a direcionar esforços em busca de novas informações. Por fim, nossas análises com relação ao fungo quitrídio corroboram a hipótese de endemismo para a linhagem Bd-Brazil e também evidenciam hábitat adequado passado para o Bd-GPL. Além disso, verificamos baixa sobreposição de nicho climático entre essas duas linhagens, indicando possibilidade de competição. Assim, esperamos que nossos resultados tenham contribuído para o conhecimento de múltiplas ameaças à conservação dos anfíbios e sirvam para direcionar futuros estudos / Abstract: Climate change has the potential to change ecosystem functioning through species extinction and disrupting connection between biota and environment, thus changing natural patterns and requiring adaptation. One certain consequence of climate change is the sea level rise, which is expected to redraw coastal shorelines worldwide and broadly affect coastal-associated biota. In this context, amphibians represent a sensitive group under several current pressures, exhibiting population decline, highlighted as the most current threaten vertebrates on Earth, and also, with several "data deficient" species. Thus, herein we analyzed multiple effects that hamper amphibian conservation. We evaluated potential climate change effects and sea level rise on amphibians with coastal distribution. Also, we developed an index to classify data deficient species in order to offer an alternative further research of such species to gather sufficient information to change their current status. Finally, we analyzed historical availability of suitable habitat for and endemic lineage of the chytrid fungus searching for patterns that explain its current distribution and rarity. We used tools as species distribution models and geographic information system to answer our questions. Our results corroborate climate change as a potentially devastating phenomena and we stress potential threatens derived from sea level rise. Moreover, the index we developed for data deficient species seems to work properly and may drive further effort in searching for further information for those species. Finally, our analyzes related to the chytrid fungus supported the hypothesis of endemism of Bd-Brazil, and also showed past environmental suitability for Bd-GPL. In addition, we verified low environmental niche overlap these two lineages, indicating possibility of competition. Thus, we expect our results may improve current knowledge about multiple threats to amphibian conservation, as well as, they may be used to guide further research / Doutorado / Ecologia / Doutor em Ecologia

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When we develop and use species distribution models to predict species' current or potential distributions, we are faced with the trade-offs between model generality, precision, and realism. It is important to know how to improve and validate model generality while maintaining good model precision and realism. However, it is difficult for ecologists to evaluate species distribution models using field-sampled data alone because the true species response function to environmental or ecological factors is unknown. Species distribution models should be able to approximate the true characteristics and distributions of species if ecologists want to use them as reliable tools. Simulated data provide the advantage of being able to know the true species-environment relationships and control the causal factors of interest to obtain insights into the effects of these factors on model performance. I used a case study on Bythotrephes longimanus distributions from several hundred Ontario lakes and a simulation study to explore the effects on model performance caused by several factors: the choice of predictor variables, the model evaluation methods, the quantity and quality of the data used for developing models, and the strengths and weaknesses of different species distribution models. Linear discriminant analysis, multiple logistic regression, random forests, and artificial neural networks were compared in both studies. Results based on field data sampled from lakes indicated that the predictive performance of the four models was more variable when developed on abiotic (physical and chemical) conditions alone, whereas the generality of these models improved when including biotic (relevant species) information. When using simulated data, although the overall performance of random forests and artificial neural networks was better than linear discriminant analysis and multiple logistic regression, linear discriminant analysis and multiple logistic regression had relatively good and stable model sensitivity at different sample size and detection limit levels, which may be useful for predicting species presences when data are limited. Random forests performed consistently well at different sample size levels, but was more sensitive to high detection limit. The performance of artificial neural networks was affected by both sample size and detection limit, and it was more sensitive to small sample size.

When we develop and use species distribution models to predict species' current or potential distributions, we are faced with the trade-offs between model generality, precision, and realism. It is important to know how to improve and validate model generality while maintaining good model precision and realism. However, it is difficult for ecologists to evaluate species distribution models using field-sampled data alone because the true species response function to environmental or ecological factors is unknown. Species distribution models should be able to approximate the true characteristics and distributions of species if ecologists want to use them as reliable tools. Simulated data provide the advantage of being able to know the true species-environment relationships and control the causal factors of interest to obtain insights into the effects of these factors on model performance. I used a case study on Bythotrephes longimanus distributions from several hundred Ontario lakes and a simulation study to explore the effects on model performance caused by several factors: the choice of predictor variables, the model evaluation methods, the quantity and quality of the data used for developing models, and the strengths and weaknesses of different species distribution models. Linear discriminant analysis, multiple logistic regression, random forests, and artificial neural networks were compared in both studies. Results based on field data sampled from lakes indicated that the predictive performance of the four models was more variable when developed on abiotic (physical and chemical) conditions alone, whereas the generality of these models improved when including biotic (relevant species) information. When using simulated data, although the overall performance of random forests and artificial neural networks was better than linear discriminant analysis and multiple logistic regression, linear discriminant analysis and multiple logistic regression had relatively good and stable model sensitivity at different sample size and detection limit levels, which may be useful for predicting species presences when data are limited. Random forests performed consistently well at different sample size levels, but was more sensitive to high detection limit. The performance of artificial neural networks was affected by both sample size and detection limit, and it was more sensitive to small sample size.

Macroecology is the study of relationships between organisms and the environment at large spatial and temporal scales. This field of research examines patterns in species abundance, distribution and diversity. Understanding patterns in species distribution and richness can contribute significantly to our knowledge of community assembly and macroecological patterns, as well as to the effective conservation of threatened species and habitats. Although there have been a plethora of studies on birds in India over the years, there is a critical need to accurately delineate species distributions and understand patterns of richness. The focus of this study was to understand the factors (abiotic and biotic) that influence the distribution and composition of bird species in the Western Ghats, as well as to explore patterns in their geographic range sizes. The objectives of this study were addressed at the scale of the entire Western Ghats using a combination of field surveys, secondary data collection and species distribution modeling. The specific approaches to address these questions and the findings are outlined below. Chapter 2: Bird species in the Western Ghats – Patterns in composition and richness Fine-scale data on species presence and abundance are essential for exploring patterns in species distribution and richness. Despite the fact that birds have been extensively studied in the Western Ghats, systematic data collection and compilation of information over the entire mountain range has not been carried out, especially for the purpose of testing macroecological questions. This chapter describes patterns in bird species presence, abundance, composition and richness within the Western Ghats. The study area, site selection protocol and the sampling technique have also been described in detail. This dataset establishes a baseline of information about birds in the Western Ghats and subsets of this larger dataset will be used to address various questions in the following chapters. Chapter 3: Predicting bird species distribution in the Western Ghats Detailed knowledge of species’ ecological and geographical distributions is fundamental for conservation, as well as for understanding ecological and evolutionary determinants of spatial patterns of biodiversity. However, occurrence data for a vast majority of species are sparse, resulting in information about species distributions that is inadequate for many purposes. Species distribution models attempt to provide detailed predictions of distributions by relating presence or abundance of species to environmental predictors. In this chapter, we describe the usage of Maxent, a species distribution modelling technique based on presence-only data, to predict the distributions of bird species within the Western Ghats. For this purpose, we put together primary locations of bird species presence along with a published dataset. Using a number of important environmental layers, predicted species distribution maps were derived for 98 bird species, including 13 endemics, in the Western Ghats. Additionally, we calculated predicted range sizes for each of these species and obtained percentage contributions of important environmental predictors to each species’ distribution. This is the first study to develop species distribution models for bird species within the Western Ghats. Chapter 4: Patterns of range size among bird species Understanding large-scale patterns of variation in species geographic range size is fundamental to questions in macroecology and conservation biology. In general, range is believed to be influenced by a combination of environmental factors, evolutionary history and biotic interactions, mediated by species specific traits. These patterns need to be examined even for well-studied taxa like birds, especially within biodiversity hotspots faced by persistent degradation due to anthropogenic activities such as the Western Ghats. In this chapter, we use a dataset of 98 bird species within the Western Ghats to examine trends in range sizes, measured as latitudinal extent of occurrence and predicted range size from species distribution models. We show a significant relationship between latitude and range size for these bird species, supporting Rapoport’s rule. As far as we know, this relationship has never been tested at such low latitudes for birds. We also find that species traits such as body size, mean abundance and diet do not seem to show any discernable effect on patterns of range size. Additionally, we found that widely-used bird species range maps (in this case, from BirdLife International) are inaccurate representations of species ranges in comparison to the predicted species distribution maps that were derived in the previous chapter. We quantitatively demonstrated that these expert-drawn maps need to re-evaluated, especially since they are used to make conservation decisions. This is the first study to quantify species range sizes of birds within the Western Ghats and assess such range maps that are used to determine conservation status of species. Chapter 5: Environmental predictors of bird species distribution One of the major goals in ecology is to understand patterns and processes that determine species diversity. The drivers of global species richness gradients have been studied, especially in the case of birds, in terms of contemporary and historical factors. Such broad scale processes may not always reflect the processes affecting richness and distribution at smaller scales. Therefore, understanding the factors that influence individual species distributions is the first step towards this larger goal. In this chapter, we examined the environmental predictors that contributed to the predicted distribution of bird species observed in the Western Ghats, using the variable importance contribution values derived in Chapter 3. We found that a large proportion of the 98 bird species studied were influenced by normalized differential vegetation index, annual precipitation and elevation. The predictors did not differ among birds of different diet guilds and body size classes. Using Prinicipal components analysis, we observed that all 98 bird species are spread out across the environmental ordination space depicted by the PC axes 1 and 2. These axes are governed by measures of habitat heterogeneity and water-energy related variables, consistent with other tropical studies. The insectivorous guild seemed to occupy a variety of environmental niches across this space and other guilds seemed to be nested within the insectivorous guild. Similarly, larger sized birds were spread across the entire environmental ordination space, with species of smaller sizes nested within. This is the first step in trying to understand environmental predictors acting on birds in the Western Ghats. Further detailed studies need to be carried out to come to definite conclusions. Chapter 6: Relative roles of floristics and vegetation structure on bird species composition On the basis of the hierarchical model of habitat selection, it is known that birds select suitable habitats based on vegetation structure (physiognomy) at coarse biogeographic scales, and plant species composition (floristics) at more local scales. This chapter examines the relative influence of tree species composition and vegetation structure on bird species composition in the Western Ghats. These relationships were specifically assessed across the entire Western Ghats, within regions of the Western Ghats as well as within specific forest types. We found that floristics had a strong association with bird species composition across the Western Ghats and within evergreen and mixed deciduous habitat types. This association seems to be independent of the structural variation in the region. There was a decrease in association strength from the southern to the northern Western Ghats, in terms of both floristics and structure. We did not find an association between vegetation structure and insectivore composition, whereas phytophage composition did show a stronger association with floristics than structure. This is the first study at the scale of the entire Western Ghats to test the relative roles of floristics and vegetation structure. Taken as a whole, this dissertation examines large-scale macroecological questions regarding species distribution, range size and patterns of composition using primary data at the scale of the Western Ghats. The findings of this study have established a foundation that will help further our understanding of species distribution and richness in the Western Ghats, and aid in the decision making for conservation strategies in the future.

Submitted by Cláudia Bueno (claudiamoura18@gmail.com) on 2016-05-19T19:46:17Z No. of bitstreams: 2 Dissertação - André Felipe Alves de Andrade - 2016.pdf: 2007118 bytes, checksum: 69341ce5bc6c459857d1feff5d92366e (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2016-05-20T13:54:17Z (GMT) No. of bitstreams: 2 Dissertação - André Felipe Alves de Andrade - 2016.pdf: 2007118 bytes, checksum: 69341ce5bc6c459857d1feff5d92366e (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2016-05-20T13:54:17Z (GMT). No. of bitstreams: 2 Dissertação - André Felipe Alves de Andrade - 2016.pdf: 2007118 bytes, checksum: 69341ce5bc6c459857d1feff5d92366e (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2016-02-26 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Coral reefs are of extreme importance to both nature and society, due to being responsible for several services and harbouring hundreds of species. Despite such critical importance, reef corals current suffered heavy losses since the Anthropocene, with 20% of world´s corals damaged beyond recovery due to human pressure and coastal development. This scenario is even worse, since corals are especially vulnerable to climate change and the entire ecosystem could go extinct by 2050. In this study we focus on comparing the already established impacts from human development and the yet happen losses from climate change on Brazilian corals, a unique fauna that still have gaps in knowledge. We created environmental suitability models for 24 species and quantified individual losses from both climate change and human activities. From the individual results we derived an overall pattern, in which we found out that future losses from climate alteration are equivalent to current losses from human activities. We then used the spatial distribution of those activities and key areas for conservation, determined with software Zonation, to select six areas in the Brazilian exclusive economic zone where proactive and reactive conservation strategies should be implanted, given its importance to biodiversity and concentrated anthropogenic impacts. Overall suitability losses were of approximately 30% for both sources and 60% of the areas will continue to be suitable in the future. Therefore, Brazilian corals will experience heavy losses from climate, especially the loss of highly suitable areas, which are compared to effects from human economic activities. Coral situation is likely to be even worse, if we were to consider bleaching, ocean acidification and diseases, events expected to increase with the rising temperature. / Ecological Niche Modelling (ENM) is widely used for conservation purposes, predicting species invasion, evolutionary aspects and a whole array of applications. However, for most cases, evaluating the efficiency of those models poses as problematic, as commonly used methods (i.e. random methods) do not assure the required independence between data used to create the model and data used to evaluate the model. We developed a new transferabilitybased framework that ensures the much-needed independence between subsets. We created an alternate approach that geographically splits occurrence datasets, while intrinsically controls issues related to previous transferability approaches, such as overfitting, extrapolation and sampling bias. We used 26 Atlantic coral species to perform three different geographical divisions quantifying the effect of different splits on model predictive efficiency. We demonstrate that transferability should be used as an effective method to evaluate ENMs. Geographical split of the area in deciles proved as a reliable evaluation method, assuring independence between datasets and being less prone to common transferability issues. Our odds-and-evens framework provides improvements to the ongoing debate of ENMs evaluating by its transferability. This new method corrects the issue of artificiality causing sampling bias and overfitting, common in previous methodologies, while also is less prone to extrapolation issues, a common problem in transferability approaches. Moreover, the framework appears as a feasible and useful alternative to the problematic and commonly used random partition of datasets evaluation.

This dissertation focused in the comprehensive analysis of the capabilities of some non-tested types of Artificial Neural Networks, specifically: the Probabilistic Neural Networks (PNN) and the Multi-Layer Perceptron (MLP) Ensembles. The analysis of the capabilities of these techniques was performed using the native brown trout (Salmo trutta; Linnaeus, 1758), the bermejuela (Achondrostoma arcasii; Robalo, Almada, Levy & Doadrio, 2006) and the redfin barbel (Barbus haasi; Mertens, 1925) as target species. The analyses focused in the predictive capabilities, the interpretability of the models and the effect of the excess of zeros in the training datasets, which for presence-absence models is directly related to the concept of data prevalence (i.e. proportion of presence instances in the training dataset). Finally, the effect of the spatial scale (i.e. micro-scale or microhabitat scale and meso-scale) in the habitat suitability models and consequently in the e-flow assessment was studied in the last chapter. / Esta tesis se centra en el análisis comprensivo de las capacidades de algunos tipos de Red Neuronal Artificial aún no testados: las Redes Neuronales Probabilísticas (PNN) y los Conjuntos de Perceptrones Multicapa (MLP Ensembles). Los análisis sobre las capacidades de estas técnicas se desarrollaron utilizando la trucha común (Salmo trutta; Linnaeus, 1758), la bermejuela (Achondrostoma arcasii; Robalo, Almada, Levy & Doadrio, 2006) y el barbo colirrojo (Barbus haasi; Mertens, 1925) como especies nativas objetivo. Los análisis se centraron en la capacidad de predicción, la interpretabilidad de los modelos y el efecto del exceso de ceros en las bases de datos de entrenamiento, la así llamada prevalencia de los datos (i.e. la proporción de casos de presencia sobre el conjunto total). Finalmente, el efecto de la escala (micro-escala o escala de microhábitat y meso-escala) en los modelos de idoneidad del hábitat y consecuentemente en la evaluación de caudales ambientales se estudió en el último capítulo. / Aquesta tesis se centra en l'anàlisi comprensiu de les capacitats d'alguns tipus de Xarxa Neuronal Artificial que encara no han estat testats: les Xarxes Neuronal Probabilístiques (PNN) i els Conjunts de Perceptrons Multicapa (MLP Ensembles). Les anàlisis sobre les capacitats d'aquestes tècniques es varen desenvolupar emprant la truita comuna (Salmo trutta; Linnaeus, 1758), la madrilla roja (Achondrostoma arcasii; Robalo, Almada, Levy & Doadrio, 2006) i el barb cua-roig (Barbus haasi; Mertens, 1925) com a especies objecte d'estudi. Les anàlisi se centraren en la capacitat predictiva, interpretabilitat dels models i en l'efecte de l'excés de zeros a la base de dades d'entrenament, l'anomenada prevalença de les dades (i.e. la proporció de casos de presència sobre el conjunt total). Finalment, l'efecte de la escala (micro-escala o microhàbitat i meso-escala) en els models d'idoneïtat de l'hàbitat i conseqüentment en l'avaluació de cabals ambientals es va estudiar a l'últim capítol. / Muñoz Mas, R. (2016). Multivariate approaches in species distribution modelling: Application to native fish species in Mediterranean Rivers [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/76168 / TESIS