A modelagem de distribuição de espécies tem como objetivo induzir um modelo para predizer a distribuição potencial de uma dada espécie. O modelo é projetado em um mapa de distribuição potencial que representa a probabilidade da presença da espécie em cada ponto. Esse processo de indução está relacionado com a estimativa do nicho fundamental da espécie, através da busca por relações entre dados georreferenciados de ocorrência da espécie e variáveis ambientais. Vários algoritmos de modelagem podem ser utilizados nessa tarefa. Oferecer diversos algoritmos pode tornar as ferramentas de modelagem mais completas. Porém, surge uma questão importante: qual algoritmo de modelagem escolher? Essa questão está relacionada com o desempenho preditivo das técnicas implementadas pelos algoritmos. Nesse contexto, o objetivo principal do trabalho foi organizar e especificar um método de análise de desempenho preditivo dos algoritmos de modelagem de distribuição de espécies. Através do método proposto é possível ter uma visão completa, estruturada e sistemática das etapas previstas em projetos de análise de desempenho preditivo dos algoritmos. O método pode ser utilizado como referência em estudos de validação de novos algoritmos, de comparação entre técnicas e na seleção de um ou mais algoritmos de modelagem. Como estudo de caso, o método proposto foi adotado nos testes de validação de um algoritmo baseado em Redes Neurais, desenvolvido e integrado ao framework openModeller, através da comparação com outros algoritmos já utilizados na modelagem. Além da própria validação, os testes tiveram como objetivo demonstrar a aplicabilidade do método. Os resultados mostraram que o algoritmo de Redes Neurais apresentou desempenho semelhante ao desempenho dos demais algoritmos, tendo sido, portanto, validado como adequado à tarefa de modelagem. Ainda no contexto da pesquisa, um algoritmo baseado na técnica de amostragem denominada Jackknife foi integrado ao openModeller, para aplicação na etapa de pré-análise. Testes relacionados com o tempo de execução foram realizados e uma versão paralela desse algoritmo foi desenvolvida. / The species distribution modeling aim is to induce a model to predict the potential distribution of a given species. The model is projected onto a potential distribution map that represents the presence probability of the species at each point. This induction process is related to the fundamental niche estimation of the species, through the search for relationships between georeferenced data of species occurrence and environmental variables. Several modeling algorithms can be used for this task. Providing different algorithms can make the modeling tools more complete. However, an important question arises: what modeling algorithm to choose? This issue is related to the predictive performance of the techniques implemented by the algorithms. In this context, the aim of this research was to organize and to specify a predictive performance analysis method of the species distribution modeling algorithms. Through the proposed method, it is possible to have a complete and structured vision of the steps in the planning of predictive performance analysis of the algorithms. The method may be used as a reference in validation studies of new algorithms, in comparison among techniques and in choosing one or more modeling algorithms. As a case study, the proposed method was adopted in the validation tests of an algorithm based on Neural Networks, developed and integrated into the openModeller framework, which was compared with other algorithms already used in modeling. Besides the validation itself, the tests intended to demonstrate the applicability of the method. The results showed that the Neural Networks algorithm presented similar performance to those of other algorithms and was validated as adequate to the modeling task. Still in the research context, an algorithm based on a sampling technique called the Jackknife was integrated to the openModeller, to be applied in the pre-analysis step. Tests related to the running time were carried out and a parallel version of this algorithm was developed.

Biodiversity, the variety of life on the planet, is declining due to climate change, population and species interactions and as the result f demographic and landscape dynamics. Integrated model-based assessments play a key role in understanding and exploring these complex dynamics and have proven use in conservation planning. Model-based assessments using Species Distribution Models constitute an efficient means of translating limited point data to distribution probability maps for current and future scenarios in support of conservation decision making. The aims of this doctoral study were to investigate; (1) the use of a hybrid genetic programming to build high quality models that handle noisy real-world presence and absence data, (2) the extension of this solution to exploit the parallelism inherent to genetic programming for fast scenario based decision making tasks, and (3) a conceptual framework to share models in the hope of enabling research synthesis. Subsequent to this, the quality of the method, evaluated with the true skill statistic, was examined with two case studies. The first with a dataset obtained by defining a virtual species, and the second with data extracted from the North American Breeding Bird Survey relating to mourning dove (Zenaida macroura). In these studies, the produced models effectively predicted the species distribution up to 30% of error rate both presence and absence samples. The parallel implementation based on a twenty-node c3.xlarge Amazon EC2 StarCluster showed a linear speedup due to the multiple-deme coarse-grained design. The hybrid fuzzy genetic programming algorithm generated under certain consitions during the case studies significantly better transferable models. / Biodiversidade, a variedade de vida no planeta, está em declínio às alterações climáticas, mudanças nas interações das populações e espécies, bem como nas alterações demográficas e na dinâmica de paisagens. Avaliações integradas baseadas em modelo desempenham um papel fundamental na compreensão e na exploração destas dinâmicas complexas e tem o seu uso comprovado no planejamento de conservação da biodiversidade. Os objetivos deste estudo de doutorado foram investigar; (1) o uso de técnicas de programação genética e fuzzy para construir modelos de alta qualidade que lida com presença e ausência de dados ruidosos do mundo real, (2) a extensão desta solução para explorar o paralelismo inerente à programação genética para acelerar tomadas de decisão e (3) um framework conceitual para compartilhar modelos, na expectativa de permitir a síntese de pesquisa. Subsequentemente, a qualidade do método, avaliada com a true skill statistic, foi examinado com dois estudos de caso. O primeiro utilizou um conjunto de dados fictícios obtidos a partir da definição de uma espécie virtual, e o segundo utilizou dados de uma espécie de pomba (Zenaida macroura) obtidos do North American Breeding Bird Survey. Nestes estudos, os modelos foram capazes de predizer a distribuição das espécies maneira correta mesmo utilizando bases de dados com até 30% de erros nas amostras de presença e de ausência. A implementação paralela utilizando um cluster de vinte nós c3.xlarge Amazon EC2 StarCluster, mostrou uma aceleração linear devido ao arquitetura de múltiplos deme de granulação grossa. O algoritmo de programação genética e fuzzy gerada em determinadas condições durante os estudos de caso, foram significativamente melhores na transferência do que os algoritmos do BIOMOD.

Os grandes carnívoros necessitam de vastos territórios para sobreviver em longo prazo, sendo que sua coexistência com humanos é fundamental, porém gera conflitos. O objetivo geral dessa tese é integrar a conservação de grandes carnívoros ao processo de planejamento de uso e ocupação da terra do estado de São Paulo. Para isso os objetivos específicos são: (1) sistematizar, espacializar e analisar a ocorrência de grandes carnívoros, estabelecendo correlações com os padrões de uso e ocupação da terra, variáveis climáticas e topográficas; (2) estabelecer áreas prioritárias para conservação de grandes carnívoros no estado de São Paulo; e (3) caracterizar os padrões de uso e conservação da terra nos municípios indicando necessidades e oportunidades para conservação (ênfase em Brotas-SP). O delineamento desse estudo foi feito buscando a aplicação de Modelos de Distribuição de Espécies - MDEs (espécies estudadas: Chrysocyon brachyurus, Leopardus Pardalis e Puma concolor) em uma abordagem de Planejamento Sistemático da Conservação - PSC. Para isso, foi aplicado o algoritmo MAXENT para as análises de distribuição das espécies e o algoritmo ZONATION para análises de priorização espacial e identificação de áreas prioritárias para conservação. Os modelos gerados mostraram alto desempenho (AUCs ≥ 0.8) e foram significantes (p ≤ 0.05) para o limite de corte mais inclusivo considerado \"minimum training presence\". Apesar da plasticidade das espécies estudadas, a variável porcentagem de vegetação nativa foi uma das três mais importantes para os modelos gerados. A distribuição das espécies abrange tanto paisagens naturais quanto paisagens antropizadas, porém as áreas com alta adequabilidade ambiental (acima de 0.5) se concentram em regiões com vegetação nativa remanescente e em sua maior parte não estão protegidas em Unidades de Conservação de Proteção Integral. Os resultados das análises de priorização espacial mostraram prioridades altas para os carnívoros concentradas na região central do estado de São Paulo, onde existem conflitos entre a demanda por áreas para conservação e a demanda por áreas para desenvolvimento humano. Recomenda-se a ampliação das UCPIs nessa região e ações de manejo e conservação em propriedades privadas (ex. Reservas Legais e Áreas de Preservação Permanente). Tanto as prioridades para conservação como as prioridades para desenvolvimento são muito diferentes entre os municípios do estado de São Paulo. Sendo assim, as estratégias precisam ser elaboradas caso a caso em escala municipal. Brotas possui localização estratégica na conservação de grandes carnívoros com alta porcentagem de áreas núcleo e alto potencial ecoturístico, sendo recomendada a expansão de UCPIs e a restauração da vegetação nativa para ampliar a proteção de grandes carnívoros. Os resultados desse estudo devem informar o processo de tomada de decisão (Ex. Planos de Ação para Conservação de Espécies Ameaçadas; Zoneamentos; Avaliações de Impactos Ambientais) e a abordagem metodológica serve como um modelo para orientar processos semelhantes que visam à conservação de espécies em outras regiões. / Large carnivores need large territories to survive in long term, requiring the use of existing protected areas and private properties with many land uses types and human occupation levels for dispersion and as additional habitat. Thus, the coexistence between large carnivores and humans is essential. However, it leads to conflicts of interest. The overall objective of this thesis is to integrate the conservation of large mammals to land use planning process in São Paulo State, Brazil. For this, the specific objectives are: (1) to systematize, to spatialize and to analyze the occurrence of large mammals, establishing correlations between large mammals distribution and land use patterns, climatic and topographic variables; (2) to establish priority areas for conservation of large mammals in São Paulo State; and (3) to characterize the land use and conservation patterns in São Paulo\'s municipalities (emphasis in Brotas-SP). The design of this study aimed to apply Species Distribution Models tools (species studied: Chrysocyon brachyurus, Leopardus Pardalis and Puma concolor) in an approach of Systematic Conservation Planning. For this, MAXENT algorithm was applied for species distribution modelling and Zonation algorithm was applied for spatial prioritization analysis and conservation priority areas identification. All models were significant (p ≤ 0.05) considering the minimum training presence threshold showing high performance (AUC ≥ 0.8). Despite the plasticity of the species, the variable percentage of native vegetation was one of the top three most important for all models. The distribution of the species covers both natural and disturbed landscapes, but high environmental suitability areas (up to 0.5) concentrate in regions with native vegetation fragments. However the most part of these areas are not protected by law. Spatial prioritization results showed high priorities for carnivores concentrate in the central region of São Paulo, where there are conflicts there are both high demand for carnivore conservation and high demand for human development. Conservation strategies need to be developed case by case because both priorities for conservation and priorities for development were showed very different between the municipalities. For example, Brotas is strategic for carnivore\'s conservation, having high percentage of core areas in its territory and high ecotourism potential. However the percent of native vegetation cover is low. Therefore, it is recommended protected areas expansion and native vegetation restoration to increase the protection of large carnivores in Brotas. This study highlights the importance of a landscape planning approach to improve the conservation outlook for large mammals, including not only the establishment and management of protected areas, but also native habitat conservation and management on private lands. Importantly, the results may inform environmental policies and land use planning in São Paulo State, Brazil (e.g. Action Plan for Conservation of Endangered Species; Zoning; Reviews of Environmental Impacts), and it serves as a useful model to guide similar process for other large-carnivore species world-wide.

[Truncated abstract] The malleefowl (Leipoa ocellata) is a large, ground-dwelling bird that is listed as threatened in all states of Australia in which it occurs. Its range encompasses much of southern Australia; however, much of it has been cleared for agriculture. Malleefowl are thought to have suffered substantial decline owing to multiple threats that include habitat loss, predation from exotic predators, grazing of habitat by introduced herbivores and fire - common threats in the decline of many Australian vertebrate species. The malleefowl has an unmistakeable appearance, unique biology, and widespread distribution across Australia. Consequently, it has been the focus of much scientific and community interest. In the Western Australian wheatbelt, community groups are working to conserve the species and have been actively collecting data on its distribution for over 15 years. The vast majority of these data are presence-only and have been collected in an opportunistic manner but, combined with long-term data from government agencies and museums spanning over 150 years, they present a significant opportunity to inform ecological questions relevant to the conservation of the species. The purpose of this study was to answer key ecological questions regarding the distribution, status and habitat preferences of malleefowl using unstructured occurrence records supplemented by reliable absences derived from Bird Atlas data sets and targeted surveys. Malleefowl in the Western Australian wheatbelt were used as a case study to illustrate: 1) how the decline of a species can be quantified and causes of that decline identified; and 2) how threats can be identified and responses to threats explored. I used bioclimatic modelling to define and explore variation within the climatic niche of the Malleefowl across Australia. '...' This thesis provides substantial additional knowledge about the ecology, distribution and status of malleefowl in Western Australia. It also illustrates how opportunistic and unstructured data can be augmented to investigate key aspects of a species' ecology. Despite the limitations of these data, which primarily relate to variation in observer effort across time and space, they can provide important outcomes that may not be achieved using standard survey and data collection techniques. The utility of opportunistic data is greatest in situations where the species: is recognisable and easily observed; is relatively sedentary; and occurs within a landscape containing consistent land use and habitat types. The approaches used in this study could be applied by researchers to situations where community interest exists for species with these attributes. At a national scale, the malleefowl is predicted to decline by at least 20% over the next three generations. The findings of this thesis suggest that the future for the species in the Western Australian wheatbelt may not be as dire as predicted elsewhere within its range, owing largely to the easing and cessation of threatening processes (e.g. land clearing, grazing of habitat by livestock) and the ability of the species to occupy a variety of habitat types. Despite this perceived security, some caution must be exercised until there is a more complete knowledge of the impact of fox predation and reduced rainfall due to climate change on malleefowl populations. Furthermore, the status of the species beyond the agricultural landscapes in Western Australia requires closer examination.

To characterise the habitat preferences of ring ouzel (Turdus torquatus) and blackbird (T. merula) in Switzerland, we adopt species distribution modelling and predict the species’ spatial distribution. We model on two different scales to analyse in how far downscaling leads to a different set of predictors to describe the realised habitat best. While the models on macroscale (grid of one square kilometre) cover the entire country, we select a set of smaller plots for modelling on territory scale. Whereas ring ouzels occur in altitudes above 1’000 m a.s.l. only, blackbirds occur from the lowlands up to the timber line. The altitudinal range overlap of the two species is up to 400 m. Despite both species coexist on macroscale, a direct niche overlap on territory scale is rare. Small-scale differences in vegetation cover and structure seem to play a dominant role for habitat selection. On macroscale however, we observe a high dependency on climatic variables mainly representing the altitudinal range and the related forest structure preferred by the two species. Applying the models for climate change scenarios, we predict a decline of suitable habitat for the ring ouzel with a simultaneous median altitudinal shift of +440 m until 2070. In contrast, the blackbird is predicted to benefit from higher temperatures and expand its range to higher elevations. / Unter Verwendung von Habitatmodellen beschreiben wir die Habitatpräferenz von Amsel (Turdus merula) und Ringdrossel (T. torquatus) in der Schweiz. Mit Hilfe verschiedener Klimaszenarien prognostizieren wir zudem die künftige potentielle Verbreitung beider Arten. Zur Beschreibung eines eventuell auftretenden Skalensprungs, d.h. einer Änderung in der Beschreibungskraft der Variablen auf verschiedenen räumlichen Ebenen, erstellten wir Modelle auf zwei unterschiedlichen Skalen. Während das Modell auf Makroskala mit einer Maschenweite von einem Quadratkilometer die gesamte Schweiz abdeckt, erstellten wir zudem eine Auswahl an Untersuchungsgebieten auf Revierebene. Ringdrosseln zeigen ihren Verbreitungsschwerpunkt in der subalpinen Lage, während Amseln vornehmlich das Tiefland und die Tallagen besiedeln und nur vereinzelt in hohe Lagen vordringen. In einem Gürtel von ungefähr 400 Höhenmetern siedeln beide Arten parallel.Trotz dieses auf der Makroskala erkennbaren Überschneidungsbereiches konnten wir in unserer Untersuchung auf Revierebene, von einer Ausnahme abgesehen, keine Koexistenz beobachten. Kleinräumige Unterschiede in der Habitatstruktur, insbesondere in der Vegetationsbedeckung scheinen demnach für die Habitatselektion von maßgeblicher Bedeutung zu sein. Auf Makroebene hingegen wurde der Einfluss klimatischer Variablen deutlich, die neben der Höhenlage auch dort typische Vegetationsstrukturen widerspiegeln. Wie die Klimaszenarien zeigen, nehmen geeignete Ringdrosselhabitate bei steigenden Temperaturen ab und die Art weicht im Mittel um 440 m in höhere Lagen zurück. Für Amseln scheint sich eine zunehmende Erwärmung jedoch positiv auszuwirken, während das Verbreitungsgebiet im Tiefland beibehalten wird, dringt sie von den Tälern ausgehend zunehmend in höhere Lagen vor.

Species respond to environmental change by dynamically adjusting their geographical ranges. Robust predictions of these changes are prerequisites to inform dynamic and sustainable conservation strategies. Correlative species distribution models (SDMs) relate species’ occurrence records to prevailing environmental factors to describe the environmental niche. They have been widely applied in global change context as they have comparably low data requirements and allow for rapid assessments of potential future species’ distributions. However, due to their static nature, transient responses to environmental change are essentially ignored in SDMs. Furthermore, neither dispersal nor demographic processes and biotic interactions are explicitly incorporated. Therefore, it has often been suggested to link statistical and mechanistic modelling approaches in order to make more realistic predictions of species’ distributions for scenarios of environmental change. In this thesis, I present two different ways of such linkage. (i) Mechanistic modelling can act as virtual playground for testing statistical models and allows extensive exploration of specific questions. I promote this ‘virtual ecologist’ approach as a powerful evaluation framework for testing sampling protocols, analyses and modelling tools. Also, I employ such an approach to systematically assess the effects of transient dynamics and ecological properties and processes on the prediction accuracy of SDMs for climate change projections. That way, relevant mechanisms are identified that shape the species’ response to altered environmental conditions and which should hence be considered when trying to project species’ distribution through time. (ii) I supplement SDM projections of potential future habitat for black grouse in Switzerland with an individual-based population model. By explicitly considering complex interactions between habitat availability and demographic processes, this allows for a more direct assessment of expected population response to environmental change and associated extinction risks. However, predictions were highly variable across simulations emphasising the need for principal evaluation tools like sensitivity analysis to assess uncertainty and robustness in dynamic range predictions. Furthermore, I identify data coverage of the environmental niche as a likely cause for contrasted range predictions between SDM algorithms. SDMs may fail to make reliable predictions for truncated and edge niches, meaning that portions of the niche are not represented in the data or niche edges coincide with data limits. Overall, my thesis contributes to an improved understanding of uncertainty factors in predictions of range dynamics and presents ways how to deal with these. Finally I provide preliminary guidelines for predictive modelling of dynamic species’ response to environmental change, identify key challenges for future research and discuss emerging developments. / Das Vorkommen von Arten wird zunehmend bedroht durch Klima- und Landnutzungswandel. Robuste Vorhersagen der damit verbundenen Arealveränderungen sind ausschlaggebend für die Erarbeitung dynamischer und nachhaltiger Naturschutzstrategien. Habitateignungsmodelle erstellen statistische Zusammenhänge zwischen dem Vorkommen einer Art und relevanten Umweltvariablen und erlauben zügige Einschätzungen potentieller Arealveränderungen. Dabei werden jedoch transiente Dynamiken weitgehend ignoriert sowie demographische Prozesse und biotische Interaktionen. Daher wurden Vorschläge laut, diese statistischen Modelle mit mechanistischeren Ansätzen zu koppeln. In der vorliegenden Arbeit zeige ich zwei verschiedene Möglichkeiten solcher Kopplung auf. (i) Ich beschreibe den sogenannten ‚Virtuellen Ökologen’-Ansatz als mächtiges Validierungswerkzeug, in dem mechanistische Modelle virtuelle Testflächen bieten zur Erforschung verschiedener Probenahmedesigns oder statistischer Methoden sowie spezifischer Fragestellungen. Auch verwende ich diesen Ansatz, um systematisch zu untersuchen wie sich transiente Dynamiken sowie Arteigenschaften und ökologische Prozesse auf die Vorhersagegüte von Habitateignungsmodellen auswirken. So kann ich entscheidende Prozesse identifizieren welche in zukünftigen Modellen Berücksichtigung finden sollten. (ii) Darauf aufbauend koppele ich Vorhersagen von Habitateignungsmodellen mit einem individuen-basierten Populationsmodell, um die Entwicklung des Schweizer Birkhuhnbestandes unter Klimawandel vorherzusagen. Durch die explizite Berücksichtigung der Wechselwirkungen zwischen Habitat und demographischer Prozesse lassen sich direktere Aussagen über Populationsentwicklung und damit verbundener Extinktionsrisiken treffen. Allerdings führen verschiedene Simulationen auch zu hoher Variabilität zwischen Vorhersagen, was die Bedeutung von Sensitivitätsanalysen unterstreicht, um Unsicherheiten und Robustheit von Vorhersagen einzuschätzen. Außerdem identifiziere ich Restriktionen in der Datenabdeckung des Umweltraumes als möglichen Grund für kontrastierende Vorhersagen verschiedener Habitateignungsmodelle. Wenn die Nische einer Art nicht vollständig durch Daten beschrieben ist, kann dies zu unrealistischen Vorhersagen der Art-Habitat-Beziehung führen. Insgesamt trägt meine Arbeit erheblich bei zu einem besseren Verständnis der Auswirkung verschiedenster Unsicherheitsfaktoren auf Vorhersagen von Arealveränderungen und zeigt Wege auf, mit diesen umzugehen. Abschließend erstelle ich einen vorläufigen Leitfaden für Vorhersagemodelle und identifiziere Kernpunkte für weitere Forschung auf diesem Gebiet.

With exploding human populations and landscapes that are changing, an increasing number of wildlife species are brought to the brink of extinction. In Canada, the eastern hog-nosed snake, 'Heterodon platirhinos', is found in a limited portion of southern Ontario. Designated as threatened by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC), this reptile has been losing its habitat at an alarming rate. Due to the increase in development of southern Ontario, it is crucial to document what limits the snake’s habitat to direct conservation efforts better, for the long-term survival of this species. The goals of this study are: 1) to examine what environmental parameters are linked to the presence of the species at a landscape scale; 2) to predict where the snakes can be found in Ontario through GIS-based habitat suitability models (HSMs); and 3) to assess the role of biotic interactions in HSMs. Three models with high predictive power were employed: Maxent, Boosted Regression Trees (BRTs), and the Genetic Algorithm for Rule-set Production (GARP). Habitat suitability maps were constructed for the eastern hog-nosed snake for its entire Canadian distribution and models were validated with both threshold dependent and independent metrics. Maxent and BRT performed better than GARP and all models predict fewer areas of high suitability when landscape variables are used with current occurrences. Forest density and maximum temperature during the active season were the two variables that contributed the most to models predicting the current distribution of the species. Biotic variables increased the performance of models not by representing a limiting resource, but by representing the inequality of sampling and areas where forest remains. Although habitat suitability models rely on many assumptions, they remain useful in the fields of conservation and landscape management. In addition to help identify critical habitat, HSMs may be used as a tool to better manage land to allow for the survival of species at risk.

Anthropogenic climate warming is predicted to accelerate over the next century, with potentially dramatic consequences for wildlife. It is important to understand as well as possible how different organisms will respond to this stress. This project seeks to gain a better mechanistic understanding of the thermal biology of the Glanville Fritillary butterfly (Melitaea cinxia) at the latitudinal and elevational extremes of its range. Investigation of the temperatures at which adult butterflies took spontaneous flight revealed a significant difference between populations from the elevational extremes, with insects from high elevation taking flight at lower thoracic temperatures than those from low elevation. Contrary to expectation, there was no systematic effect of latitude on takeoff temperature. If these measures represent adaptation to climate, then these effects are not simple and the influences of elevation and latitude are not the same. Investigation of thermal tolerance across all life cycle stages found no difference in larval performance between the populations tested. There was however an effect of treatment. This suggests that in M. cinxia, even populations from different extremes of the range may not differ in their thermal tolerance. The effect of treatment suggests that there is temperature-induced plasticity. The adaptive significance of this has been explored to some extent. Investigation of heat shock protein expression between the latitudinal extremes finds no difference in Hsp21.4 expression when exposed to heat stress, however both Hsp20.4 and Hsp90 were upregulated in response to heat stress. For Hsp20.4, there were significant differences in expression between the populations. Finally, a species distribution model using maximum entropy techniques was conducted for M. cinxia, predicting both the current and future (2100) distributions of the species. The model closely matches the known current distribution, and predicts a clear northward range shift in response to climate change. / text

No description available.

Habitat loss and fragmentation are recognised worldwide as contributing to declines and extinctions of species. However, the biological factors underlying the effects of fragmentation are still often poorly understood, possibly due to the diversity of scales and approaches taken by researchers. I propose in this thesis an integrative approach that can be applied to any taxa and landscape, using a metapopulation of North Island robins (Petroica longipes) inhabiting forest patches of a fragmented agricultural landscape of New Zealand. In particular, I attempt to integrate the effects of habitat fragmentation on both habitat quality and the dispersal-driven broad scale dynamics of populations. I first analysed the distribution of robins based on presence-absence data, relating presence-absence to local habitat factors as well as size and isolation of forest patches (Chapter 2). Their distribution was found to be primarily limited by the isolation of forest patches, but was also related to some habitat factors. However, habitat fragmentation was not found to affect habitat quality, as the factors found to affect survival and productivity were unrelated to size and isolation, independent from the size or isolation of forest patches (Chapter 3). Based on the radio-tracking of juvenile robins, I applied a choice analysis technique to show that robins need woody vegetation for their natal dispersal and that they are unlikely to cross stretches of pasture greater than 150 m (Chapter 4). Juveniles dispersed a median Euclidean distance of 1129 m with a maximum of 11 km, whereas I predicted from the data that they would have dispersed a median distance of 3 km in continuous forest with a maximum of 20 km (Chapter 5). The consequences of this dispersal limitation and of variations in habitat quality were assessed using a spatially-explicit individual-based metapopulation model that incorporated realistic gap-limited dispersal behaviour of juvenile robins (Chapter 6). Whereas the movement of individuals between patches is commonly assumed to improve the persistence of populations, I found that a weaker gap-crossing ability, and therefore reduced landscape connectivity, increased the metapopulation size at equilibrium. This study highlights the complex effects of habitat loss and fragmentation on the distribution of species, but also the limits of excessive model simplification.