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.

The aim of this thesis was to create potential distribution models for Dicranum majus (Greater Fork Moss) and Polytrichum alpinum (Alpine Haircap) in Bohemian Switzerland National Park. In the Czech Republic these bryophyte species occur in cold climatic regions typically with higher altitudes. In Bohemian and Saxon Switzerland they can occur in really low altitudes thanks to unique microclimatic conditions of deep inversion ravines. These bryophyte species had low number of occurence records in studied area before the start of my research (4 occurence localities for Dicranum majus, 8 occurence localities for Polytrichum alpinum). Predictive habitat suitability models can be an effective tool for selecting potential new occurence localities, planning field research or management design. During field research I recorded 34 new occurence localities for Dicranum majus and 29 new occurence localities for Polytrichum alpinum in Bohemian Switzerland National Park. I used 8 topographic parameters derived from digital elevation model with 1 m resolution as environmental data. Using these data I created models of potential distribution of the most suitable habitats for both species with algorithms Artificial neural networks (ANN), Generalised linear model (GLM) and Random forest (RF). RF algorithm had the...

L’Afrique centrale atlantique (ACA) englobe l’ensemble du domaine bas-guinéen, les îles du Golfe de Guinée et une partie de l’archipel afromontagnard. Plusieurs centres d’endémisme ont été identifiés en son sein et sont généralement considérés comme liés à la présence de refuges forestiers durant les périodes glaciaires. Cependant, l’origine de cet endémisme, sa localisation et les méthodes permettant d’identifier ces centres restent controversées. La localisation de ces zones d’endémisme et des plantes rares qu’elles abritent, est pourtant un prérequis indispensable pour la mise en place de politiques cohérentes de conservation et demeure une priorité pour les organisations privées, institutionnelles ou gouvernementales actives dans la gestion et le maintien durable de la biodiversité. Cette étude phytogéographique porte sur la famille des Orchidaceae et est basée sur l’analyse de la distribution des taxons endémiques de l’ACA. Elle s’appuie sur un jeu de données original résultant d’un effort d’échantillonnage important au Cameroun et d’un travail d’identification et de localisation de spécimens dans les principaux herbaria européens abritant des collections d’ACA. Durant cette étude, (i) nous avons tout d’abord identifié ces taxons endémiques et documenté leur distribution au travers de plusieurs contributions taxonomiques et floristiques, (ii) nous nous sommes ensuite intéressé aux nouvelles méthodes permettant d’analyser ces données d’herbier de plantes rares et donc pauvrement documentées, testant aussi l’intérêt des Orchidaceae comme marqueurs chorologiques, et finalement, appliquant ces méthodes à notre jeu de données, (iii) nous avons délimité des centres d’endémisme et identifié les territoires phytogéographiques des Orchidaceae en ACA. (i) Une révision taxonomique des genres Chamaeangis Schltr. et Stolzia Schltr. a été réalisée respectivement. Sept nouveaux taxons ont été décrits: Angraecum atlanticum Stévart & Droissart, Chamaeangis spiralis Stévart & Droissart, Chamaeangis lecomtei (Finet) Schltr. var. tenuicalcar Stévart & Droissart, Polystachya engogensis Stévart & Droissart, Polystachya reticulata Stévart & Droissart, Stolzia repens (Rolfe) Summerh var. cleistogama Stévart, Droissart & Simo et Stolzia grandiflora P.J.Cribb subsp. lejolyana Stévart, Droissart & Simo. Plusieurs notes taxonomiques, phytogéographiques et écologiques supplémentaires ont également été redigées. Au total, nous avons identifié 203 taxons d’Orchidaceae endémiques d’ACA parmi lesquels 193 sont pris en compte pour l’étude des patrons d’endémisme. (ii) Au Cameroun, les patrons de distribution des Orchidaceae et des Rubiaceae endémiques d’ACA ont été étudiés conjointement. Des méthodes de rééchantillonnage des données (raréfaction) ont été appliquées pour calculer des indices de diversité et de similarité. Elles ont permis de corriger les biais liés à la variation de l’effort d’échantillonnage. Un gradient de continentalité a été observé, les parties côtières étant les plus riches en taxons endémiques d’ACA. Contrairement à la région du Mont Cameroun et aux massifs de Kupe/Bakossi qui ont connu une attention particulière des politiques et des scientifiques, la partie côtière du sud Cameroun, presque aussi riche, reste mal inventoriée pour plusieurs familles végétales. Cette analyse à l’échelle du Cameroun a également permis de comparer les patrons d’endémisme des Orchidaceae et des Rubiaceae. Les différences observées seraient principalement dues à la présence d’Orchidaceae terrestres dans les végétations basses et les prairies montagnardes de la dorsale camerounaise alors que les Rubiaceae sont généralement peu représentées dans ces habitats. Au sein des habitats forestiers, la concordance entre les patrons d’endémisme des Orchidaceae et des Rubiaceae remet en question l’utilisation des capacités de dispersion des espèces comme critère pour choisir les familles permettant l’identification des refuges forestiers et semble ainsi confirmer la pertinence de l’utilisation des Orchidaceae comme marqueur chorologique. La distribution potentielle a été utilisée pour étudier en détail l’écologie, la distribution et le statut de conservation de Diceratostele gabonensis Summerh., une Orchidaceae endémique de la région guinéo-congolaise uniquement connue d’un faible nombre d’échantillons. Cette méthodologie semble appropriée pour compléter nos connaissances sur la distribution des espèces rares et guider les futurs inventaires en Afrique tropicale. (iii) En ACA, les Orchidaceae permettent d’identifier plusieurs centres d’endémisme qui coïncident généralement avec ceux identifiés précédemment pour d’autres familles végétales. Ces constats supportent aussi l’utilisation des Orchidaceae comme marqueur chorologique. La délimitation des aires d’endémisme des Orchidaceae a ainsi permis de proposer une nouvelle carte phytogéographique de l’ACA. Les éléments phytogéographiques propres à chacune des dix phytochories décrites ont été identifiés et leurs affinités floristiques discutées. Les résultats phytogéographiques obtenus (a) soutiennent l’existence d’une barrière phytogéographique matérialisée par la rivière Sanaga entre les deux principaux centres et aires d’endémisme de l’ACA, (b) étendent l’archipel afromontagnard situé principalement au Cameroun au plateau de Jos (Nigeria) et (c) montrent l’importance de la chaîne montagneuse morcelée Ngovayang-Mayombe pour la distribution de l’endémisme en ACA. Cette chaîne de montagne, qui s’étend le long des côtes de l’océan du sud Cameroun au Congo-Brazzaville et qui correspond à plusieurs refuges forestiers identifiés par de nombreux auteurs, est ici considérée comme une seule aire d’endémisme morcelée./ Atlantic central Africa (ACA) covers the Lower Guinean Domain, the four islands of the Gulf of Guinea and a part of the afromontane archipelago. Different centres of endemism have been identified into this area and are usually considered as related to glacial forest refuges. However, the origin of this endemism, the localization of the centres and the methods employed to identify these centres are subject to debate. Yet, the localization of these centres of endemism and the identification of the rare plants they harbor is an essential prerequisite to setting up rational conservation policies, and remains a priority for private, institutional and governmental organizations which are dealing with the sustainable management of biodiversity. This phytogeographical study focuses on Orchidaceae and analyses the distribution of the taxa endemic to ACA. We use an original dataset resulting from an important sampling efforts and the identification of specimens coming from all the principal herbaria where collections from ACA are housed. During this study, (i) we first identified the taxa endemic to ACA and documented their distribution through several taxonomic and floristic contributions, (ii) we used and developed new methods allowing to correct for sampling bias associated with the use of rare and poorly documented taxa, testing at the same time the use of Orchidaceae as chorological markers, and finally, applying these methods to our dataset, (iii) we delimited the centres of endemism and identified the phytogeographical territories of Orchidaceae in ACA. (i) A taxonomic revision of Chamaeangis Schltr. and Stolzia Schltr. respectively was carried out. Seven new taxa were described: Angraecum atlanticum Stévart & Droissart, Chamaeangis spiralis Stévart & Droissart, Chamaeangis lecomtei (Finet) Schltr. var. tenuicalcar Stévart & Droissart, Polystachya engogensis Stévart & Droissart, Polystachya reticulata Stévart & Droissart, Stolzia repens (Rolfe) Summerh var. cleistogama Stévart, Droissart & Simo and Stolzia grandiflora P.J.Cribb subsp. lejolyana Stévart, Droissart & Simo. Several additional taxonomic, phytogeographical and ecological notes were also published. We finally identified 203 Orchidaceae taxa endemic to ACA, among which 193 were used to study the patterns of endemism. (ii) In Cameroon, the distribution patterns of both Orchidaceae and Rubiaceae endemic to ACA were studied. Subsampling methods (rarefaction) were applied to calculate diversity and similarity indices and to correct potential bias associated with heterogeneous sampling intensity. A gradient of continentality was confirmed in Cameroon, the coastal part being the richest in taxa endemic to ACA. The Cameroon Mountain and the Kupe/Bakossi mountain massifs have received a great consideration of politics and scientists. On the contrary, the Southern coastal part of Cameroon, though almost as rich as the Northern part, remains poorly known for several plant families. This analysis also allowed us to compare patterns of endemism of Orchidaceae and Rubiaceae. The differences observed could be mainly due to the terrestrial habit of some Orchidaceae, which are only found in the grasslands of the highest part of the Cameroonian volcanic line where endemic Rubiaceae are rare. Within forest habitats, the concordance between the patterns of endemism of Orchidaceae and Rubiaceae question the widespread use of dispersal ability as a selection criterion for the families used to identify forest refuges. This also confirms the relevance of Orchidaceae as chorological marker. Species distribution modelling was used of an in depth study of the ecology, the distribution and the conservation status of Diceratostele gabonensis Summerh., an Orchidaceae endemic to the Guineo-Congolian regional centre of endemism which is only known from very few collections. This method is proved to be appropriate to complete our knowledge on the distribution of rare plant species and to guide the future inventories in tropical Africa. (iii) In ACA, an analysis of the distribution of endemic Orchidaceae confirmed the presence and location of several centres of endemism previously identified on the basis of other plant families. This result again supports the use of Orchidaceae as a chorological marker. The chorological study of the endemic Orchidaceae allowed us to propose a new phytogeographical map for ACA. Phytogeographical elements for each of the ten phytochoria described were identified and their floristic affinities were also discussed. Our results (a) support the existence of a phytogeographical barrier, materialized by the Sanaga River, between the two main centres and area of endemism of the ACA, (b) extend the limits of the afromontane archipelago to the Jos Plateau in Nigeria and (c) show the importance of the Ngovayang-Mayombe line to explain the distribution of endemism in ACA. This mountainous line, stretching along the ocean coast from Southern Cameroon to Congo-Brazzaville, corresponds to several forest refuges identified by many authors, and is here considered as an unique but discontinuous area of endemism.

Environmental factors influence species and habitats on multiple scales creating a mosaic of distribution patterns. Studying factors shaping these patterns are central to our understanding of population dynamics and ultimately ecosystem functioning. Information on the distribution of resources and conservation values are also highly needed in marine management as coastal areas are increasingly influenced by human activities. In this thesis, large-scale field data is used to explore how strong environmental gradients found on multiple scales in the coastal areas of the Baltic Sea influence fish habitats. The underlying concepts are based in the field of species distribution modelling, whereby habitat maps can be produced using environmental layers in a geographic information system. Distribution modelling is further used to address both ecological and applied questions by examining effects of habitat limitation on fish population sizes and to evaluate management actions aimed at habitat conservation. I show that specific habitat requirements for fish species of both freshwater and marine origin can be described using environmental variables and that species-environment relationships can be used to predict the distribution of early life-stages of fish in the Baltic Sea archipelagos. Further, predicted habitat availability of a specific life-stage was directly related to adult population size of Eurasian perch Perca fluviatilis, signifying that the abundance of large predatory fish can be limited by specific recruitment habitats. Lastly, by predicting the distribution of an assemblage of coastal fish species and their associated habitats, an assessment of a network of marine protected areas was performed. Results revealed large gaps in the current network and identified areas suitable for future protection. By demonstrating how current habitat protection can be improved by including critical habitats for coastal fish population sizes this thesis points to the benefits of integrating nature conservation and fisheries management. Based on these findings I conclude that species distribution modelling provides a suitable analytical framework for assessing the habitat requirements of organisms. An increased understanding of habitat-population relationships and an ability to accurately map ecologically important features will be of great value for an ecosystem-based marine management. ­ / Felaktigt tryckt som Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 709

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Os fatores que explicam a distribuição observada em plantas e animais é uma pergunta que intriga naturalistas, biogeógrafos e ecólogos há mais de um século. Ainda nos primórdios da disciplina de ecologia, as tolerâncias ambientais já haviam sido apontadas como as grandes responsáveis pelo padrão observado da distribuição dos seres vivos, o que mais tarde levou à concepção de nicho ecológico das espécies. Nos últimos anos, o estudo das distribuições dos organismos ganhou grande impulso e destaque na literatura. O motivo foi a maior disponibilidade de catálogos de presença de espécies, o desenvolvimento de bancos de variáveis ambientais de todo o planeta e de ferramentas computacionais capazes de projetar mapas de distribuição potencial de um dado organismo. Estes instrumentos, coletivamente chamados de Modelos de Distribuição de Espécies (MDEs) têm sido desde então amplamente utilizados em estudos de diferentes escopos. Um deles é a avaliação de potenciais áreas suscetíveis à invasão de organismos exóticos. Este estudo tem, portanto, o objetivo de compreender, através de MDEs, os fatores subjacentes à distribuição de duas espécies de corais escleractíneos invasores nativos do Oceano Pacífico e ambas invasoras bem sucedidas de diversas partes do Oceano Atlântico, destacadamente o litoral fluminense. Os resultados mostraram que os modelos preditivos da espécie Tubastraea coccinea (LESSON, 1829), cosmopolita amplamente difundida na sua região nativa pelo Indo- Pacífico demonstraram de maneira satisfatória suas áreas de distribuição nas áreas invadidas do Atlântico. Sua distribuição está basicamente associada a regiões com alta disponibilidade de calcita e baixa produtividade fitoplanctônica. Por outro lado, a aplicação de MDEs foi incapaz de predizer a distribuição de T. tagusensis (WELLS,1982) no Atlântico. Essta espécie, ao contrário de sua congênere, tem distribuição bastante restrita em sua região nativa, o arquipélago de Galápagos. Através de análises posteriores foi possível constatar a mudança no nicho observado durante o processo de invasão. Finalmente, o sucesso preditivo para T. coccinea e o fracasso dos modelos para T. tagusensis levantam importantes questões sobre quais os aspectos ecológicos das espécies são mais favoráveis à aplicação de MDEs. Adicionalmente, lança importantes ressalvas na utilização recentemente tão difundida destas ferramentas como forma de previsão de invasões biológicas e em estudos de efeitos de alterações climáticas sobre a distribuição das espécies. / The factors underpinning the observed distribution of plants and animals across time and space are a central question in ecology and has intrigued scientists for over a century. But even back on those early times, the role of climatic tolerances of the species were recognized as one of the main explanations for such distributional patterns. Later, these assumptions gave rise to the concept of niche which triggered several advances in the study of natural history. Recently, these studies were addressed in the light of novel computational techniques capable of providing potential distributional maps for a given species, generically called Species Distribution Models (SDMs). This coupled with the broader availability of species occurrence records and of environmental data from international databases made studies with SDMs very popular and ubiquitous in the literature. One of the main uses of the SDMs approach is the assessment of potentially susceptible areas of invasion by non- indigenous species. Therefore, here we used SDMs to better understand the major factors related to the current distribution of two well established invasive scleractinian coral species in the Atlantic, both from the Pacific Ocean. The results showed that the models were successful in predicting the potentially invaded sites by the cosmopolitan Tubastraea coccinea (LESSON, 1829), broadly distributed throughout the Pacific. This species distribution was basically associated with increasing concentrations of calcite and lower levels of phytoplankton activity. However, the models were incapable of predicting the survival and establishment of T. tagusensis (WELLS, 1982) in the Atlantic. This species, unlike its congener, has a very restricted distribution in its native regions, the Galapagos Islands. A posterior analyzes indeed showed a niche shift during the invasion event of T. tagusensis in the Atlantic. Finally, the good modelling results for T. coccinea contrasted with the failure of modelling T. tagusensis invasion highlight important explanations on methodological procedures in SDMs. It also helps to better understand which ecological aspects of the species are favourable toward good modelling performance. In addition to that, these results calls for precaution when analyzing SDMs results, particularly in invasion and climate change scenarios studies.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Os fatores que explicam a distribuição observada em plantas e animais é uma pergunta que intriga naturalistas, biogeógrafos e ecólogos há mais de um século. Ainda nos primórdios da disciplina de ecologia, as tolerâncias ambientais já haviam sido apontadas como as grandes responsáveis pelo padrão observado da distribuição dos seres vivos, o que mais tarde levou à concepção de nicho ecológico das espécies. Nos últimos anos, o estudo das distribuições dos organismos ganhou grande impulso e destaque na literatura. O motivo foi a maior disponibilidade de catálogos de presença de espécies, o desenvolvimento de bancos de variáveis ambientais de todo o planeta e de ferramentas computacionais capazes de projetar mapas de distribuição potencial de um dado organismo. Estes instrumentos, coletivamente chamados de Modelos de Distribuição de Espécies (MDEs) têm sido desde então amplamente utilizados em estudos de diferentes escopos. Um deles é a avaliação de potenciais áreas suscetíveis à invasão de organismos exóticos. Este estudo tem, portanto, o objetivo de compreender, através de MDEs, os fatores subjacentes à distribuição de duas espécies de corais escleractíneos invasores nativos do Oceano Pacífico e ambas invasoras bem sucedidas de diversas partes do Oceano Atlântico, destacadamente o litoral fluminense. Os resultados mostraram que os modelos preditivos da espécie Tubastraea coccinea (LESSON, 1829), cosmopolita amplamente difundida na sua região nativa pelo Indo- Pacífico demonstraram de maneira satisfatória suas áreas de distribuição nas áreas invadidas do Atlântico. Sua distribuição está basicamente associada a regiões com alta disponibilidade de calcita e baixa produtividade fitoplanctônica. Por outro lado, a aplicação de MDEs foi incapaz de predizer a distribuição de T. tagusensis (WELLS,1982) no Atlântico. Essta espécie, ao contrário de sua congênere, tem distribuição bastante restrita em sua região nativa, o arquipélago de Galápagos. Através de análises posteriores foi possível constatar a mudança no nicho observado durante o processo de invasão. Finalmente, o sucesso preditivo para T. coccinea e o fracasso dos modelos para T. tagusensis levantam importantes questões sobre quais os aspectos ecológicos das espécies são mais favoráveis à aplicação de MDEs. Adicionalmente, lança importantes ressalvas na utilização recentemente tão difundida destas ferramentas como forma de previsão de invasões biológicas e em estudos de efeitos de alterações climáticas sobre a distribuição das espécies. / The factors underpinning the observed distribution of plants and animals across time and space are a central question in ecology and has intrigued scientists for over a century. But even back on those early times, the role of climatic tolerances of the species were recognized as one of the main explanations for such distributional patterns. Later, these assumptions gave rise to the concept of niche which triggered several advances in the study of natural history. Recently, these studies were addressed in the light of novel computational techniques capable of providing potential distributional maps for a given species, generically called Species Distribution Models (SDMs). This coupled with the broader availability of species occurrence records and of environmental data from international databases made studies with SDMs very popular and ubiquitous in the literature. One of the main uses of the SDMs approach is the assessment of potentially susceptible areas of invasion by non- indigenous species. Therefore, here we used SDMs to better understand the major factors related to the current distribution of two well established invasive scleractinian coral species in the Atlantic, both from the Pacific Ocean. The results showed that the models were successful in predicting the potentially invaded sites by the cosmopolitan Tubastraea coccinea (LESSON, 1829), broadly distributed throughout the Pacific. This species distribution was basically associated with increasing concentrations of calcite and lower levels of phytoplankton activity. However, the models were incapable of predicting the survival and establishment of T. tagusensis (WELLS, 1982) in the Atlantic. This species, unlike its congener, has a very restricted distribution in its native regions, the Galapagos Islands. A posterior analyzes indeed showed a niche shift during the invasion event of T. tagusensis in the Atlantic. Finally, the good modelling results for T. coccinea contrasted with the failure of modelling T. tagusensis invasion highlight important explanations on methodological procedures in SDMs. It also helps to better understand which ecological aspects of the species are favourable toward good modelling performance. In addition to that, these results calls for precaution when analyzing SDMs results, particularly in invasion and climate change scenarios studies.

Small Island Developing States (SIDS) of the Caribbean are one of the world’s ‘hottest’ ‘biodiversity hotspots’. However, this biodiversity continues to be threatened by habitat loss, and now, by climate change. The research reported here investigated the potential of species distribution modelling (SDM) as a plant conservation tool within Caribbean SIDS, using Trinidad as a case study. Prior to the application of SDM, ancillary analyses including: (i) quantification and mapping of forest cover change (1969 to 2007) and deforestation rates, and (ii) assessment of the island’s vegetation community distribution and associated drivers were carried out. Community distribution and commercial importance and global/regional rarity were used to generate a list of species for assessing the potential of SDM within Trinidad. Species occurrence data were used to generate species distribution models for present climate conditions within the SDM algorithm, MaxEnt. These results were assessed through expert appraisal and concurrence with results of ecological analyses. These models were used to forecast suitable species climate space forty years into an SRES A2 future. Present and future models were then combined to produce a ‘collective change map’ which showed projected areas of species’ range expansion, contraction or stability for this group of species with respect to Trinidad’s Protected Areas (PAs) network. Despite the models being indicative rather than accurate, it was concluded that species’ climate space is likely to decrease or disappear across Trinidad. Extended beyond Trinidad into the remainder of the Caribbean region, SDM may be a crucial tool in identifying which PAs within the region (and not individual islands) will facilitate future survival of given target species. Consideration of species conservation from a regional, rather than an individual island perspective, is strongly recommended for aiding the Caribbean SIDS to adapt in response to climate change.

The work describes the processing and analysis of remote sensing time series data for a comparative assessment of changes in different tropical rainforest areas in East Africa. In order to assess the effects of the derived changes in land cover and forest fragmentation, the study made use of spatially explicit modelling approaches within a geographical information system (GIS) to extrapolate sets of biological field findings in space and time. The analysis and modelling results were visualised aiming to consider the requirements of three different user groups. In order to evaluate measures of forest conservation and to derive recommendations for an effective forest management, quantitative landscape-scale assessments of land cover changes and their influence on forest biodiversity patterns are needed. However, few remote sensing studies have accounted for all of the following aspects at the same time: (i) a dense temporal sequence of land cover change/forest fragmentation information, (ii) the coverage of several decades, (iii) the distinction between multiple forest formations and (iv) direct comparisons of different case studies. In regards to linkages of remote sensing with biological field data, no attempts are known that use time series data for quantitative statements of long-term landscape-scale biodiversity changes. The work studies three officially protected forest areas in Eastern Africa: the Kakamega-Nandi forests in western Kenya (focus area) and Mabira Forest in south-eastern Uganda as well as Budongo Forest in western Uganda (for comparison purposes). Landsat imagery of in total eight or seven dates in regular intervals from 1972/73 to 2003 was used. Making use of supervised multispectral image classification procedures, in total, 12 land cover classes (six forest formations) were distinguished for the Kakamega-Nandi forests and for Budongo Forest while for Mabira Forest ten classes could be realised. An accuracy assessment via error matrices revealed overall classification accuracies between 81% and 85%. The Kakamega-Nandi forests show a continuous decrease between 1972/73 and 2001 of 31%, Mabira Forest experienced an abrupt loss of 24% in the late 1970s/early 1980s, while Budongo Forest shows a relatively stable forest cover extent. An assessment of the spatial patterns of forest losses revealed congruence with areas of high population density while a spatially explicit forest fragmentation index indicates a strong correlation of forest fragmentation with forest management regime and forest accessibility by roads. For the Kenyan focus area, three sets of biological field abundance data on keystone species/groups were used for a quantitative assessment of the influence of long-term changes in tropical forests on landscape-scale biodiversity patterns. For this purpose, the time series was extended with another three land cover data sets derived from aerial photography (1965/67, 1948/(52)) and old topographic maps (1912/13). To predict the spatio-temporal distribution of the army ant Dorylus wilverthi and of ant-following birds, GIS operators (i.e. focal and local functions) and statistical tests (i.e. OLS or SAR regression models) were combined into a spatial modelling procedure. Abundance data on three guilds of birds differing in forest dependency were directly extrapolated to five forest cover classes as distinguished in the time series. The results predict declines in species abundances of 56% for D. wilverthi, of 58% for ant-following birds and an overall loss of 47% for the bird habitat guilds, which in all three cases greatly exceed the rate of forest loss (31%). Additional extrapolations on scenarios of deforestation and reforestation confirmed the negative ecological consequences of splitting-up contiguous forest areas but also showed the potential of mixed indigenous forest plantings. The visualisation of the analysis and modelling results produced a mixture of different outcomes. Map series and a matrix of maps both showing species distributions aim to address scientists and decision makers. The results of the land cover change analysis were synthesised in a map of land cover development types for each study area, respectively. These maps are designed mainly for scientists. Additional maps of change, limited to a single class of forest cover and to three dates were generated to ensure an easy-to-grasp communication of the major forest changes to decision makers. Additionally, an easy-to-handle visualisation tool to be used by scientists, decision makers and local people was developed. For the future, an extension of this study towards a more complete assessment including more species/groups and also ecosystem functions and services would be desirable. Combining a framework for land cover simulation with a framework for running empirical extrapolation models in an automated manner could ideally result in a GIS-based, integrated forest ecosystem assessment tool to be used as regional spatial decision support system. / Die Arbeit beschreibt die Prozessierung und Analyse von Fernerkundungs-Zeitreihendaten für eine vergleichende Abschätzung von Veränderungen verschiedener tropischer Waldökosysteme Ostafrikas. Um Effekte der Veränderungen bzgl. Landbedeckung und Waldfragmentierung auf Biodiversitätsmuster abzuschätzen, wurden verschiedene räumlich explizite Modellierungssätze innerhalb eines geographischen Informationssystems (GIS) zur räumlichen und zeitlichen Extrapolation biologischer Felderhebungsdaten benutzt. Die Visualisierung der Analyse- und Modellierungsergebnisse erfolgte unter Berücksichtigung der Bedürfnisse von drei verschiedenen Nutzergruppen. Um Waldschutzmaßnahmen zu evaluieren und Empfehlungen für ein effektives Waldmanagement abzuleiten, sind quantitative Abschätzungen von Landbedeckungsveränderungen sowie von deren Einfluss auf tropische Waldbiodiversitätsmuster nötig. Wenige fernerkundungsbasierte Studien haben jedoch bislang alle der folgenden Faktoren berücksichtigt: (i) Informationen zu Veränderungen von Landbedeckung und Waldfragmentierung in dichter zeitlicher Sequenz, (ii) die Abdeckung mehrerer Jahrzehnte, (iii) die Unterscheidung zwischen mehreren Waldformationen, und (iv) direkte Vergleiche von unterschiedlichen Fallstudien. Hinsichtlich Verknüpfungen von Fernerkundung mit biologischen Felddaten sind bisher keine Studien bekannt, die Zeitreihendaten für quantitative Aussagen zu Langzeitveränderungen von Biodiversität auf Landschaftsebene verwenden. Die Arbeit untersucht drei offiziell geschützte Gebiete: die Kakamega-Nandi forests in Westkenia (Hauptuntersuchungsgebiet) sowie Mabira Forest in Südost-Uganda und Budongo Forest in West-Uganda (zu Vergleichszwecken). Es wurden Landsat-Daten für insgesamt acht bzw. sieben Zeitpunkte zwischen 1972/73 und 2003 in ungefähr gleichen Abständen erworben. Mit Hilfe von überwachten, multispektralen Klassifizierungsverfahren wurden für die Kakamega-Nandi forests und Budongo Forest jeweils 12 Landbedeckungsklassen (sechs Waldformationen) und für Mabira Forest zehn Klassen unterschieden. Eine Genauigkeitsprüfung mit Hilfe von Fehlermatrizen ergab Gesamtklassifizierungsgenauigkeiten zwischen 81% und 85%. Die Kakamega-Nandi forests sind durch eine kontinuierliche Waldabnahme von 31% zwischen 1972/73 und 2001 gekennzeichnet, Mabira Forest zeigt einen abrupten Waldverlust von 24% in den späten 1970ern/frühen 1980ern, während die Ergebnisse für Budongo Forest eine relativ stabile Waldbedeckung ausweisen. Während eine Abschätzung der räumlichen Muster von Waldverlusten eine hohe Deckungsgleichheit mit Gebieten hoher Bevölkerungsdichte ergab, deutet die Anwendung eines räumlich expliziten Waldfragmentierungsindexes auf eine starke Korrelation von Waldfragmentierung mit der Art von Waldmanagement sowie mit der Erreichbarkeit von Wald über Straßen hin. Um den Einfluss von Langzeit-Landbedeckungsveränderungen auf Biodiversitätsmuster auf Landschaftsebene für das kenianische Hauptuntersuchungsgebiet quantitativ abzuschätzen wurden drei Datensätze mit biologischen Felderhebungen zur Abundanz von Schlüsselarten/-gruppen verwendet. Zu diesem Zweck wurde die Zeitreihe zunächst um drei weitere Landbedeckungs-Datensätze ergänzt, die aus Luftbildern (1965/67, 1948/(52)) bzw. alten topographischen Karten (1912/13) gewonnen wurden. Zur Vorhersage der raum-zeitlichen Verteilung der Treiberameise Dorylus wilverthi wurden GIS-Operatoren und statistische Tests (OLS bzw. SAR Regressionsmodelle) in einem räumlichen Modellierungsablauf kombiniert. Abundanzdaten von drei sich hinsichtlich ihrer Abhängigkeit von Wald unterscheidenden Vogelgilden wurden direkt auf fünf Waldbedeckungsklassen hochgerechnet, die in der Zeitreihe unterschieden werden konnten. Die Ergebnisse prognostizieren Abundanzabnahmen von 56% für D. wilverthi, von 58% für Ameisen-folgende Vögel und einen Gesamtverlust von 47% für die Vogelgilden, was in allen drei Fällen eine deutliche Überschreitung der Waldverlustrate von 31% darstellt. Zusätzliche Extrapolationen basierend auf Szenarien bestätigten die negativen ökologischen Konsequenzen der Zerteilung zusammenhängender Waldflächen bzw. zeigten andererseits das Potential von Aufforstungen mit einheimischen Arten auf. Die Visualisierung der Analyse- bzw. Modellierungsergebnisse führte zu unterschiedlichen Darstellungen: mit einer Reihe von nebeneinander positionierten Einzelkarten sowie einer Matrix von Einzelkarten, die jeweils Artenverteilungen zeigen, sollen Wissenschaftler und Entscheidungsträger angesprochen werden. Aus den Ergebnissen der Landbedeckungsanalyse für die drei Untersuchungsgebiete wurden Landbedeckungsveränderungstypen generiert und jeweils in einer synthetischen Karte dargestellt, die hauptsächlich für Wissenschaftler gedacht sind. Um die wesentlichen Waldveränderungen auch auf einfache Weise zu den Entscheidungsträgern zu kommunizieren, wurden zusätzliche Karten erstellt, die nur eine aggregierte Klasse „Waldbedeckung“ zeigen und jeweils auf drei Zeitschritte der Zeitreihen begrenzt sind. Zusätzlich wurde ein leicht zu bedienendes Visualisierungstool entwickelt, das für Wissenschaftler, Entscheidungsträger und die lokale Bevölkerung gedacht ist. Für die Zukunft wäre eine umfassendere Abschätzung unter Berücksichtigung zusätzlicher Arten/-gruppen sowie auch Ökosystemfunktionen und –dienstleistungen wünschenswert. Die Verknüpfung einer Applikation zur Landbedeckungsmodellierung mit einer Applikation zur Ausführung von empirischen Extrapolationsmodellen (in stärkerem Maße automatisiert als in dieser Arbeit) könnte im Idealfall in ein GIS-basiertes Tool zur integrativen Bewertung von Waldökosystemen münden, das dann als räumliches Entscheidungsunterstützungssystem verwendet werden könnte.

Submitted by Franciele Moreira (francielemoreyra@gmail.com) on 2017-08-17T18:33:27Z No. of bitstreams: 2 Dissertaçao - Lara de Macedo Monteiro - 2017.pdf: 68300760 bytes, checksum: ba7fbce35b9ab3e46180337ae3129580 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2017-08-18T12:02:30Z (GMT) No. of bitstreams: 2 Dissertaçao - Lara de Macedo Monteiro - 2017.pdf: 68300760 bytes, checksum: ba7fbce35b9ab3e46180337ae3129580 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-08-18T12:02:30Z (GMT). No. of bitstreams: 2 Dissertaçao - Lara de Macedo Monteiro - 2017.pdf: 68300760 bytes, checksum: ba7fbce35b9ab3e46180337ae3129580 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-03-15 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Earth is facing the highest species' extinction rates of its history, and humans are the major stressar. Adding up to this biodiversity crisis, species-rich areas, which also coincide with areas highly transformed by humans (e.g. biodiversity hotspots), are poorly covered by protected areas. ln Brazil this reality is not different. Responsible for harbouring a third of all plant species already classified under a threat category (n= 645), the Brazilian Cerrado has only 8.3% of its area legally protected. ln this biorne, the campos rupestres, a mountaintop grassland ecosystem, stands out for its high number of threatened species currently underrepresented in conservation strategies. ln chapter 1, we aimed at indicating priority areas to secure protection of the threatened plant species from the southern Espinhaço mountains, a region that encampasses large areas of campos rupestres. We found that it is possible to protect, on average, more than 25% of the threatened species' ranges, avoiding sites with extensive use for farming and mining and favouring areas with intensive fire frequency by constraining the management to a relatively small area of only 17% of the region. Conservation plans such as these proposed for campos rupestres represent important opportunities to fulfil the gap existent between research and implementation. However, we do not rule out the need for increasing sophisticated tools that account for the consequences of complex processes threatening biodiversity in the near future ( e.g. clima te change and deforestation) and especially the need for predictive and realistic conservation strategies that anticipate and mitigate their negative effects. Unfortunately, until now we have been relying species protection to a residual system of PAs that provide minimal conservation impact. Thus, in chapter 2 we aimed to select spatial conservation priorites that minimize the risk of deforestation while retaining sites with high plant biodiversity value threatened from climate change in the Brazilian Cerrado. We simulated two ways of spacing out priorities for conservation actions ("time-step action" and "acting now''), and two methods of setting priorities: one that minimizes expected habitat conversion and prioritizes high valuable sites to plant biodiversity at risk from climate change (maximum conservation impact) and another that prioritizes sites based only on their value for plant biodiversity at risk from climate change, regardless their vulnerability to land conversion ("usual approach''). We found that although the scenarios that maximize conservation impact avoided higher amounts of vegetation loss, they prevented least species' range loss. Moreover, the acting now scenarios always performed better in terms of range loss avoided compared to the time-step scenarios under the sarne method of prioritization. Finally, we believe that planning for vegetation loss avoidance is a more conservative strategy because vegetation information is less subjective to any source of bias and is a better surrogate for general biodiversity. We also recommend that acting as soon as possible is always the best strategy to guarantee biodiversity conservation in the Cerrado. / A Terra vem enfrentando as maiores taxas de extinção de espécies de sua história, e os humanos são a maior causa disso. Além da crise de biodiversidade, áreas ricas em espécies, que, por sua vez, coincidem com locais sob alta influência de atividades humanas (ex: hotspots de biodiversidade), são pouco representadas por Unidades de Conservação. No Brasil, essa realidade não é diferente. Responsável por abrigar um terço de todas as espécies de plantas já classificadas sob uma das categorias de ameaça (n=645), o Cerrado brasileiro possui somente 8.3% de sua área legalmente protegida. Nesse biorna, o ecossistema de campos rupestres destaca-se pelo seu alto número de espécies ameaçadas atualmente subrepresentadas em estratégias de conservação. No capítulo 1, nosso objetivo foi indicar áreas prioritárias para assegurar a proteção de espécies ameaçadas de plantas da Serra do Espinhaço Meridional, uma região que abrange grandes trechos de campos rupestres. Nós encontramos que é possível proteger, em média, mais de 25% da distribuição das espécies ameaçadas restringindo o manejo a uma área relativamente pequena de apenas 17% da região e evitando locais de uso extensivo do solo para agropecuária e mineração e favorecendo locais com alta ocorrência de queimadas. Planos de conservação como esse proposto para campos rupestres representam importantes oportunidades para preencher a lacuna existente entre pesquisa e implementação. No entanto, nós não descartamos a necessidade de ferramentas mais sofisticadas que considerem as consequências dos complexos processos que ameaçam a biodiversidade em um futuro próximo ( ex: mudanças climáticas e desmatamento) e, especialmente, a necessidade de estratégias de conservação preditivas e realistas que antecipem e mitiguem seus efeitos negativos. Infelizmente, até agora a proteção das espécies tem se restringido a um sistema residual de unidades de conservação de baixo impacto para a conservação. Portanto, no capítulo 2 nosso objetivo foi selecionar espacialmente locais de alto valor para a biodiversidade de plantas ameaçadas em um cenário de mudanças climáticas e ao mesmo tempo minimizar o risco de conversão da vegetação desses locais. Nós simulamos duas formas de particionar as ações de conservação ("ação em intervalos de tempo" e "agir agora") e dois métodos de estabelecer prioridades: um que minimiza a conversão de hábitat esperada e prioriza locais altamente importantes para a biodiversidade de plantas ameaçadas em um cenário de mudanças climáticas ("máximo impacto da conservação") e outro que prioriza locais baseando-se somente no seu valor para a biodiversidade de plantas ameaçadas em um cenário de mudanças climáticas, independentemente de sua vulnerabilidade ao desmatamento ("abordagem habitual''). Nós encontramos que, embora os cenários que maximizem o impacto da conservação tenham evitado maiores perdas de vegetação, eles evitaram uma menor perda no tamanho médio da distribuição das espécies comparado às abordagens habituais. Além disso, constatamos que os cenários "agir agora" tiveram um melhor desempenho em termos de perda de distribuição evitada comparado aos cenários de implementação sequencial de ações considerando um mesmo método de priorização. Finalmente, nós acreditamos que planejar para evitar perda de vegetação é uma estratégia mais segura, porque a informação sobre vegetação é menos sujeita a qualquer viés e é um melhor indicador para biodiversidade em geral. Também recomendamos que agir o quanto antes é sempre a melhor estratégia para garantir a conservação da biodiversidade no Cerrado.

The work describes the processing and analysis of remote sensing time series data for a comparative assessment of changes in different tropical rainforest areas in East Africa. In order to assess the effects of the derived changes in land cover and forest fragmentation, the study made use of spatially explicit modelling approaches within a geographical information system (GIS) to extrapolate sets of biological field findings in space and time. The analysis and modelling results were visualised aiming to consider the requirements of three different user groups. In order to evaluate measures of forest conservation and to derive recommendations for an effective forest management, quantitative landscape-scale assessments of land cover changes and their influence on forest biodiversity patterns are needed. However, few remote sensing studies have accounted for all of the following aspects at the same time: (i) a dense temporal sequence of land cover change/forest fragmentation information, (ii) the coverage of several decades, (iii) the distinction between multiple forest formations and (iv) direct comparisons of different case studies. In regards to linkages of remote sensing with biological field data, no attempts are known that use time series data for quantitative statements of long-term landscape-scale biodiversity changes. The work studies three officially protected forest areas in Eastern Africa: the Kakamega-Nandi forests in western Kenya (focus area) and Mabira Forest in south-eastern Uganda as well as Budongo Forest in western Uganda (for comparison purposes). Landsat imagery of in total eight or seven dates in regular intervals from 1972/73 to 2003 was used. Making use of supervised multispectral image classification procedures, in total, 12 land cover classes (six forest formations) were distinguished for the Kakamega-Nandi forests and for Budongo Forest while for Mabira Forest ten classes could be realised. An accuracy assessment via error matrices revealed overall classification accuracies between 81% and 85%. The Kakamega-Nandi forests show a continuous decrease between 1972/73 and 2001 of 31%, Mabira Forest experienced an abrupt loss of 24% in the late 1970s/early 1980s, while Budongo Forest shows a relatively stable forest cover extent. An assessment of the spatial patterns of forest losses revealed congruence with areas of high population density while a spatially explicit forest fragmentation index indicates a strong correlation of forest fragmentation with forest management regime and forest accessibility by roads. For the Kenyan focus area, three sets of biological field abundance data on keystone species/groups were used for a quantitative assessment of the influence of long-term changes in tropical forests on landscape-scale biodiversity patterns. For this purpose, the time series was extended with another three land cover data sets derived from aerial photography (1965/67, 1948/(52)) and old topographic maps (1912/13). To predict the spatio-temporal distribution of the army ant Dorylus wilverthi and of ant-following birds, GIS operators (i.e. focal and local functions) and statistical tests (i.e. OLS or SAR regression models) were combined into a spatial modelling procedure. Abundance data on three guilds of birds differing in forest dependency were directly extrapolated to five forest cover classes as distinguished in the time series. The results predict declines in species abundances of 56% for D. wilverthi, of 58% for ant-following birds and an overall loss of 47% for the bird habitat guilds, which in all three cases greatly exceed the rate of forest loss (31%). Additional extrapolations on scenarios of deforestation and reforestation confirmed the negative ecological consequences of splitting-up contiguous forest areas but also showed the potential of mixed indigenous forest plantings. The visualisation of the analysis and modelling results produced a mixture of different outcomes. Map series and a matrix of maps both showing species distributions aim to address scientists and decision makers. The results of the land cover change analysis were synthesised in a map of land cover development types for each study area, respectively. These maps are designed mainly for scientists. Additional maps of change, limited to a single class of forest cover and to three dates were generated to ensure an easy-to-grasp communication of the major forest changes to decision makers. Additionally, an easy-to-handle visualisation tool to be used by scientists, decision makers and local people was developed. For the future, an extension of this study towards a more complete assessment including more species/groups and also ecosystem functions and services would be desirable. Combining a framework for land cover simulation with a framework for running empirical extrapolation models in an automated manner could ideally result in a GIS-based, integrated forest ecosystem assessment tool to be used as regional spatial decision support system. / Die Arbeit beschreibt die Prozessierung und Analyse von Fernerkundungs-Zeitreihendaten für eine vergleichende Abschätzung von Veränderungen verschiedener tropischer Waldökosysteme Ostafrikas. Um Effekte der Veränderungen bzgl. Landbedeckung und Waldfragmentierung auf Biodiversitätsmuster abzuschätzen, wurden verschiedene räumlich explizite Modellierungssätze innerhalb eines geographischen Informationssystems (GIS) zur räumlichen und zeitlichen Extrapolation biologischer Felderhebungsdaten benutzt. Die Visualisierung der Analyse- und Modellierungsergebnisse erfolgte unter Berücksichtigung der Bedürfnisse von drei verschiedenen Nutzergruppen. Um Waldschutzmaßnahmen zu evaluieren und Empfehlungen für ein effektives Waldmanagement abzuleiten, sind quantitative Abschätzungen von Landbedeckungsveränderungen sowie von deren Einfluss auf tropische Waldbiodiversitätsmuster nötig. Wenige fernerkundungsbasierte Studien haben jedoch bislang alle der folgenden Faktoren berücksichtigt: (i) Informationen zu Veränderungen von Landbedeckung und Waldfragmentierung in dichter zeitlicher Sequenz, (ii) die Abdeckung mehrerer Jahrzehnte, (iii) die Unterscheidung zwischen mehreren Waldformationen, und (iv) direkte Vergleiche von unterschiedlichen Fallstudien. Hinsichtlich Verknüpfungen von Fernerkundung mit biologischen Felddaten sind bisher keine Studien bekannt, die Zeitreihendaten für quantitative Aussagen zu Langzeitveränderungen von Biodiversität auf Landschaftsebene verwenden. Die Arbeit untersucht drei offiziell geschützte Gebiete: die Kakamega-Nandi forests in Westkenia (Hauptuntersuchungsgebiet) sowie Mabira Forest in Südost-Uganda und Budongo Forest in West-Uganda (zu Vergleichszwecken). Es wurden Landsat-Daten für insgesamt acht bzw. sieben Zeitpunkte zwischen 1972/73 und 2003 in ungefähr gleichen Abständen erworben. Mit Hilfe von überwachten, multispektralen Klassifizierungsverfahren wurden für die Kakamega-Nandi forests und Budongo Forest jeweils 12 Landbedeckungsklassen (sechs Waldformationen) und für Mabira Forest zehn Klassen unterschieden. Eine Genauigkeitsprüfung mit Hilfe von Fehlermatrizen ergab Gesamtklassifizierungsgenauigkeiten zwischen 81% und 85%. Die Kakamega-Nandi forests sind durch eine kontinuierliche Waldabnahme von 31% zwischen 1972/73 und 2001 gekennzeichnet, Mabira Forest zeigt einen abrupten Waldverlust von 24% in den späten 1970ern/frühen 1980ern, während die Ergebnisse für Budongo Forest eine relativ stabile Waldbedeckung ausweisen. Während eine Abschätzung der räumlichen Muster von Waldverlusten eine hohe Deckungsgleichheit mit Gebieten hoher Bevölkerungsdichte ergab, deutet die Anwendung eines räumlich expliziten Waldfragmentierungsindexes auf eine starke Korrelation von Waldfragmentierung mit der Art von Waldmanagement sowie mit der Erreichbarkeit von Wald über Straßen hin. Um den Einfluss von Langzeit-Landbedeckungsveränderungen auf Biodiversitätsmuster auf Landschaftsebene für das kenianische Hauptuntersuchungsgebiet quantitativ abzuschätzen wurden drei Datensätze mit biologischen Felderhebungen zur Abundanz von Schlüsselarten/-gruppen verwendet. Zu diesem Zweck wurde die Zeitreihe zunächst um drei weitere Landbedeckungs-Datensätze ergänzt, die aus Luftbildern (1965/67, 1948/(52)) bzw. alten topographischen Karten (1912/13) gewonnen wurden. Zur Vorhersage der raum-zeitlichen Verteilung der Treiberameise Dorylus wilverthi wurden GIS-Operatoren und statistische Tests (OLS bzw. SAR Regressionsmodelle) in einem räumlichen Modellierungsablauf kombiniert. Abundanzdaten von drei sich hinsichtlich ihrer Abhängigkeit von Wald unterscheidenden Vogelgilden wurden direkt auf fünf Waldbedeckungsklassen hochgerechnet, die in der Zeitreihe unterschieden werden konnten. Die Ergebnisse prognostizieren Abundanzabnahmen von 56% für D. wilverthi, von 58% für Ameisen-folgende Vögel und einen Gesamtverlust von 47% für die Vogelgilden, was in allen drei Fällen eine deutliche Überschreitung der Waldverlustrate von 31% darstellt. Zusätzliche Extrapolationen basierend auf Szenarien bestätigten die negativen ökologischen Konsequenzen der Zerteilung zusammenhängender Waldflächen bzw. zeigten andererseits das Potential von Aufforstungen mit einheimischen Arten auf. Die Visualisierung der Analyse- bzw. Modellierungsergebnisse führte zu unterschiedlichen Darstellungen: mit einer Reihe von nebeneinander positionierten Einzelkarten sowie einer Matrix von Einzelkarten, die jeweils Artenverteilungen zeigen, sollen Wissenschaftler und Entscheidungsträger angesprochen werden. Aus den Ergebnissen der Landbedeckungsanalyse für die drei Untersuchungsgebiete wurden Landbedeckungsveränderungstypen generiert und jeweils in einer synthetischen Karte dargestellt, die hauptsächlich für Wissenschaftler gedacht sind. Um die wesentlichen Waldveränderungen auch auf einfache Weise zu den Entscheidungsträgern zu kommunizieren, wurden zusätzliche Karten erstellt, die nur eine aggregierte Klasse „Waldbedeckung“ zeigen und jeweils auf drei Zeitschritte der Zeitreihen begrenzt sind. Zusätzlich wurde ein leicht zu bedienendes Visualisierungstool entwickelt, das für Wissenschaftler, Entscheidungsträger und die lokale Bevölkerung gedacht ist. Für die Zukunft wäre eine umfassendere Abschätzung unter Berücksichtigung zusätzlicher Arten/-gruppen sowie auch Ökosystemfunktionen und –dienstleistungen wünschenswert. Die Verknüpfung einer Applikation zur Landbedeckungsmodellierung mit einer Applikation zur Ausführung von empirischen Extrapolationsmodellen (in stärkerem Maße automatisiert als in dieser Arbeit) könnte im Idealfall in ein GIS-basiertes Tool zur integrativen Bewertung von Waldökosystemen münden, das dann als räumliches Entscheidungsunterstützungssystem verwendet werden könnte.