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.

<p>Human use of the oceans is increasingly in conflict with conservation of endangered species. Methods for managing the spatial and temporal placement of industries such as military, fishing, transportation and offshore energy, have historically been post hoc; i.e. the time and place of human activity is often already determined before assessment of environmental impacts. In this dissertation, I build robust species distribution models in two case study areas, US Atlantic (Best et al. 2012) and British Columbia (Best et al. 2015), predicting presence and abundance respectively, from scientific surveys. These models are then applied to novel decision frameworks for preemptively suggesting optimal placement of human activities in space and time to minimize ecological impacts: siting for offshore wind energy development, and routing ships to minimize risk of striking whales. Both decision frameworks relate the tradeoff between conservation risk and industry profit with synchronized variable and map views as online spatial decision support systems.</p><p>For siting offshore wind energy development (OWED) in the U.S. Atlantic (chapter 4), bird density maps are combined across species with weights of OWED sensitivity to collision and displacement and 10 km2 sites are compared against OWED profitability based on average annual wind speed at 90m hub heights and distance to transmission grid. A spatial decision support system enables toggling between the map and tradeoff plot views by site. A selected site can be inspected for sensitivity to a cetaceans throughout the year, so as to capture months of the year which minimize episodic impacts of pre-operational activities such as seismic airgun surveying and pile driving.</p><p>Routing ships to avoid whale strikes (chapter 5) can be similarly viewed as a tradeoff, but is a different problem spatially. A cumulative cost surface is generated from density surface maps and conservation status of cetaceans, before applying as a resistance surface to calculate least-cost routes between start and end locations, i.e. ports and entrance locations to study areas. Varying a multiplier to the cost surface enables calculation of multiple routes with different costs to conservation of cetaceans versus cost to transportation industry, measured as distance. Similar to the siting chapter, a spatial decisions support system enables toggling between the map and tradeoff plot view of proposed routes. The user can also input arbitrary start and end locations to calculate the tradeoff on the fly.</p><p>Essential to the input of these decision frameworks are distributions of the species. The two preceding chapters comprise species distribution models from two case study areas, U.S. Atlantic (chapter 2) and British Columbia (chapter 3), predicting presence and density, respectively. Although density is preferred to estimate potential biological removal, per Marine Mammal Protection Act requirements in the U.S., all the necessary parameters, especially distance and angle of observation, are less readily available across publicly mined datasets.</p><p>In the case of predicting cetacean presence in the U.S. Atlantic (chapter 2), I extracted datasets from the online OBIS-SEAMAP geo-database, and integrated scientific surveys conducted by ship (n=36) and aircraft (n=16), weighting a Generalized Additive Model by minutes surveyed within space-time grid cells to harmonize effort between the two survey platforms. For each of 16 cetacean species guilds, I predicted the probability of occurrence from static environmental variables (water depth, distance to shore, distance to continental shelf break) and time-varying conditions (monthly sea-surface temperature). To generate maps of presence vs. absence, Receiver Operator Characteristic (ROC) curves were used to define the optimal threshold that minimizes false positive and false negative error rates. I integrated model outputs, including tables (species in guilds, input surveys) and plots (fit of environmental variables, ROC curve), into an online spatial decision support system, allowing for easy navigation of models by taxon, region, season, and data provider.</p><p>For predicting cetacean density within the inner waters of British Columbia (chapter 3), I calculated density from systematic, line-transect marine mammal surveys over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007) conducted by Raincoast Conservation Foundation. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. Abundance estimates are provided on a stratum-specific basis. Steller sea lions and harbour seals are further differentiated by ‘hauled out’ and ‘in water’. This analysis updates previous estimates (Williams & Thomas 2007) by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.</p><p>Starting with marine animal observations at specific coordinates and times, I combine these data with environmental data, often satellite derived, to produce seascape predictions generalizable in space and time. These habitat-based models enable prediction of encounter rates and, in the case of density surface models, abundance that can then be applied to management scenarios. Specific human activities, OWED and shipping, are then compared within a tradeoff decision support framework, enabling interchangeable map and tradeoff plot views. These products make complex processes transparent for gaming conservation, industry and stakeholders towards optimal marine spatial management, fundamental to the tenets of marine spatial planning, ecosystem-based management and dynamic ocean management.</p> / Dissertation

Cord-forming fungi (CFF) are an assemblage of saprotrophic fungi which can use complex foraging organs of longitudinally arranged hyphae to join up disparate substrates in a patchy resource environment. Their importance to woodlands lies, mainly, in their ability to modify nutrient cycling and soil structure. Therefore, in order to enable woodlands to continue to thrive in terms of their health and ecosystem function, it is necessary to understand the factors contributing to the establishment, success and diversity of this group. Whilst work to date on CFF has focussed on their physiology and interactions in laboratory conditions, little work has been carried out on their taxonomy and establishment/presence in the field. The work in this thesis begins to address these crucial unanswered questions in CFF ecology. By carrying out investigations at a range of scales, from phylogenetic analysis to UK wide Species Distribution Modelling, this thesis reaches a number of surprising results with potentially important implications for woodland management. This is most evident in Chapter 3 where our hypothesis that fungal communities develop over time in plantations of different woodland ages was disproved, illustrating that even 13 years after planting, fungal communities in plantations on ex-agricultural land had not begun to reach those in established ASNW. These unexpected results continue into Chapter 4, where the thesis demonstrates that dominant canopy species has a greater impact on community composition than any other woodland factor. Chapter 5 continues this theme, by showing that removal of invasive species is not always beneficial for the cord-forming fungal communities, especially if it involves removing the woody substrate. The work described, detailed and analysed in this thesis has initiated further investigations, proposed changes to woodland management practices and laid the foundations for future work relating to CFF and their role and function in British woodlands.

Cyclopoids are together with Calanoids and Harpacticoids a part of the largest, very diverse group of crustaceans and the most numerous aquatic metazoans of the world. The history of their research goes as far back as to the beginning of 19th century when the first cyclopoid copepods were described. The taxonomy of cyclopoids started to develop gradually since that time, adding new and more detailed methods and morphological characters, as well as a certain degree of taxonomical confusion. In last decades, the molecular-genetic techniques of DNA sequencing have become available offering a new independent tool for taxonomists. This work contains different studies concerning the morphology, taxonomy, ecology, distribution and colonisation of cyclopoid copepods, with the use of molecular tools as a uniting element. Chapter 1 of this thesis summarizes basic knowledge about the taxonomy, morphology and biology of cyclopoid copepods and introduces the following chapters containing four studies presented as single publications. The taxonomy of copepods of the genus Cyclops is based mainly on the morphology which is sometimes ambivalent and some of the most problematic species groups are presented here. Chapter 2 presents our unique results, the first reconstruction of phylogenetic relationships among 15...

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.

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.

O interesse em valorizar os serviços ecossistêmicos fornecidos pela vegetação natural aumentou em um esforço para mitigar os efeitos da mudança do uso da terra. Nesta linha de pensamento, desenvolvemos um índice para valorar as comunidades de árvores - do ponto de vista antropocêntrico - da savana brasileira (Cerrado). O índice e a cartografia produzida servirão como ferramenta para a priorização da conservação, bem como para revelar como a colonização e a expansão da agricultura tem ocorrido. Para desenvolver o índice, foram produzidas novas camadas ambientais com resolução de 90m; A distribuição das 93 espécies mais comuns foi modelada; e a cartografia da distribuição de cada uso humano das árvores (alimentos, aromáticos, fibras, cosméticos, cortiça, etc., totalizando 20 usos) e um índice de valor total fo desenvolvido. O novo índice de valor, nomenado a Soma de Usos (SoU, Sum of Uses), representa o número esperado de usos para a montagem de espécies potenciais que poderia estar ocorrendo no lugar em condições ideais. O impacto da agricultura foi avaliado pela contabilização da área que foi convertida em lavouras. Nossos resultados indicam fortemente que a colonização humana e a expansão de terras cultivadas eliminaram as árvores de áreas que antes eram melhores prestadores de serviços ambientais. Por outro lado, observamos também que as áreas protegidas no Cerrado estão localizadas onde esperamos encontrar valor marginal para as espécies ótimas. Esses resultados nos levam a pensar que a estratégia de conservação pode estar longe de ser ideal para o maior remanescente arável do mundo. / The interest in valuing the ecosystem services provided by the natural vegetation has increased in an effort to mitigate the effects of land use change. In this line of thinking, we developed an index to value the tree communities -from an anthropocentric point of view- of the Brazilian savannah (Cerrado). The index and the cartography produced will serve as a tool for prioritization of conservation, has well as to unveil how colonization and agriculture expansion has taken place. In order to develop the index: new environmental layers at 90m resolution were produced; the most common 93 species’ distribution was modelled; and cartography for each use humans derive from the trees (food, aromatic, fiber, cosmetic, cork, etc., totaling 20 uses) and a total value index were developed. The new index of value, namely the Sum of Uses (SoU), represent the expected number of uses for the potential species assemblage that could be taking place under optimal conditions. The impact of agriculture was assessed by accounting for the area that has been converted to croplands. Our results strongly indicate that human settlement and cropland expansion have cleared the trees of areas that once were better than average ecosystem service providers. On the other hand, we also observe that protected areas in the Cerrado are located where we expect to find marginal value for the optimal communities. These results lead us to think that the conservation strategy might be far from optimal for the largest remaining arable patch in the world.

O Eragrostis plana Nees (capim-annoni-2 ou capim annoni) é uma gramínea exótica trazida da África do Sul nos anos cinquenta e atualmente tem presença em aproximadamente 10% da área total do bioma Pampa, sendo a espécie mais invasiva desse bioma. Tendo em conta a grande capacidade desta espécie para se estabelecer em uma ampla variedade de condições ambientais, os efeitos ambientais e econômicos negativos envolvidos, bem como sua dificuldade de erradicação, é importante identificar as áreas mais suscetíveis à invasão em um futuro próximo, para assim aprimorar os planos de manejo e evitar a expansão de áreas infestadas. O presente trabalho foi desenvolvido no município de Aceguá – RS, com o objetivo de identificar quais áreas são as mais suscetíveis à invasão. Foram aplicados os modelos de distribuição de espécies MAXENT e GARP tendo como dados de entrada as variáveis ambientais calculadas a partir imagens espectrais, modelo numérico de elevação, mapa de solos e mapa de vias. Como algumas variáveis originalmente têm resolução espacial de 250 m e outras de 30 m, foi feita uma reamostragem tanto a 30 m como a 250 m para comparar os resultados dos modelos nas duas resoluções espaciais. Para diminuir o número de variáveis de entrada foi feita uma análise de correlação para eliminar as variáveis com alta correlação. Também foi feito o teste Jackknife para avaliar quais variáveis contribuem mais na modelagem espacial da distribuição do capim annoni. Os dois modelos, tanto no treinamento como na validação, nas duas resoluções espaciais, apresentam valores médios de ajuste de AUC acima de 0,7, sendo considerado um bom ajuste. Foram empregados três métodos para calcular os limiares ótimos de corte para cada um dos modelos: 1) sensibilidade igual à especificidade; 2) soma entre a sensibilidade e a especificidade máxima; Os limiares obtidos foram 42 para MAXENT_250, 39 para MAXENT_30, 69 para GARP_250 e 68 para GARP_30. Após a aplicação dos limiares, verificou-se que o modelo GARP prediz uma área maior que o MAXENT, 33,20% em comparação com 24,60% na resolução espacial de 250 m, e 35,83% contra 27,17% na resolução espacial de 30 m. Verificou-se também que o GARP possui melhor capacidade de generalização, o qual é importante para modelar espécies invasoras. Os dois modelos predizem com presença uma área comum de 21,23% e 23,94% nas resoluções espaciais de 250 m e 30 m respectivamente. As pastagens são as classes de uso que apresentam uma maior suscetibilidade à invasão de capim anonni. Ao cruzar os resultados dos modelos de suscetibilidade à invasão de capim annoni, com resolução espacial de 30 m, e as áreas de pastagens que estão sob alta pressão de pastejo, verificou-se que o modelo MAXENT consegue predizer uma suscetibilidade à invasão em 24,51% das áreas e o modelo GARP prediz 37,95% de suscetibilidade à invasão. As comparações entre as duas resoluções espaciais demonstrou que não há muitas diferenças em termos de quantificação de área, sendo que o principal ganho foi o detalhamento espacial, o qual foi obtido com um alto custo computacional. / The Eragrostis plana Nees (South African lovegrass), is an exotic grassy plant originally from South Africa, introduced in the 50s and is currently present in approximately 10% of the total area of the Pampa biome, being the most invasive species in this biome. Considering the large capacity of the South African lovegrass establishing itself in a wide variety of environmental conditions, the negative effects, both environmental and economical that it involves, as well as its difficulty of eradication, it is important to identify the invasion most susceptible areas in the near future, in order to improve the management to prevent the spread of infested areas. This research was developed in the municipality of Aceguá – RS, with the objective of identifying which areas are most susceptible to invasion. The MAXENT and GARP models of distribution of species were applied, having as input data the environmental variables calculated from spectral images, digital elevation model, soil map and road map. As some variables originally had spatial resolution of 250m and others of 30m, a resample was done at both 30m and 250m in order to compare the models results in these two spatial resolutions. To reduce the input variables amount, a correlation analysis was performed to eliminate the high correlation variables. The Jackknife test was also used to evaluate which variables contribute most to the South African lovegrass distribution spatial modeling. Both models, at the two spatial resolutions, during the training and the validation steps, present mean values of AUC adjustment above 0.7, being considered a good fit. Three methods were used to calculate the optimal thresholds for each model: 1) the sensitivity equals to the specificity; 2) the sum between sensitivity and specificity is the maximum; 3) the distance between the ROC curve and left top corner is minimum. The calculated thresholds were 42 for MAXENT_250, 39 for MAXENT_30, 69 for GARP_250 and 68 for GARP_30. After applying these thresholds, it was verified that the GARP model predicts an area greater than MAXENT, 33.20% compared to 24.60% for the spatial resolution of 250m, and 35.83% against 27.17% in the spatial resolution of 30m. It was also verified that GARP has a better generalization capacity, which is important for modeling invasive species patterns. Both models predict a common area with susceptible to invasion of 21.23% and 23.94% in spatial resolutions of 250m and 30m respectively. The grasslands are the land cover that presents a South African lovegrass invasion greater susceptibility. Cross-referencing the susceptibility invasion models with the overgrazing areas at 30m of spatial resolution, it was verified that the model MAXENT can predict a susceptibility to invasion in 24.51% of the areas and the GARP model predicts 37.95% susceptibility to invasion. Comparisons between the two spatial resolutions showed that there are not many differences in terms of area quantification, where the main gain was spatial detailing, which was obtained with a high computational cost.

O tamanduá-bandeira (Myrmecophaga tridactyla) se distribui amplamente ao longo da região Neotropical, porém é provável que esteja extinto da maior parte de sua extensão original, notadamente na América Central e nos limites austrais de sua distribuição. O táxon está ameaçado de extinção globalmente (IUCN) e também em âmbito nacional. Embora historicamente a espécie ocorra em todos os biomas brasileiros, hoje é considerada extinta nos Pampas, quase extinta na Mata Atlântica, sendo que na Caatinga sua presença necessita de confirmação e no Cerrado suas populações vem sofrendo drásticas reduções. Atualmente não há estudos de revisão da distribuição da espécie nos biomas brasileiros, tão pouco foi avaliado se as áreas mais adequadas à espécie estão sendo protegidas e o conhecimento existente é insuficiente para adotar estratégias de conservação adequadas. Dessa maneira, o presente estudo teve como principal objetivo modelar a distribuição potencial e atual do tamanduá-bandeira no Brasil e nos biomas brasileiros, a fim de identificar quais variáveis preditoras melhor explicam a ocorrência da espécie em diferentes escalas. Além disso, a partir dos modelos de distribuição atual, os biomas foram avaliados quanto à adequabilidade ambiental (i.e. probabilidade de presença) e foram realizadas uma análise de lacunas e a identificação de áreas prioritárias para a conservação. A distribuição potencial do tamanduá-bandeira foi melhor explicada em escala continental, por variáveis bioclimáticas (sazonalidade de temperatura e precipitação) e topográficas (altitude), enquanto que a distribuição atual foi bem explicada nas duas escalas, por variáveis de uso e cobertura da terra (porcentagens de cobertura arbórea, de silvicultura e de cana-de-açúcar). O Cerrado foi o bioma de maior adequabilidade ambiental à espécie, seguido da Amazônia, Pantanal, Mata Atlântica e Caatinga, sendo que não foram obtidos registros recentes para os Pampas. Menos de 10% da distribuição atual do tamanduá-bandeira no Cerrado e Pantanal encontra-se protegida por Unidades de Conservação, existindo uma lacuna parcial de conservação. Áreas prioritárias para a espécie incluem um corredor central no Cerrado, grande parte do Pantanal e áreas de transição (ecótonos) com outros biomas. Os resultados obtidos neste estudo permitiram preencher lacunas de conhecimento acerca da distribuição do tamanduá-bandeira, bem como dar suporte para o planejamento de sua conservação. / The giant anteater (Myrmecophaga tridactyla) is widely distributed throughout the Neotropical region, but is probably extinct from most of its range, notably in Central America and the southern limits of its distribution. The species is listed as Vulnerable on the IUCN and national Red Lists. Although historically present in all Brazilian biomes, there are no studies reviewing its distribution, nor has it been evaluated if the Brazilian federal conservation units are protecting the areas most suitable to the species. Thus, the aim of this study was to model the potential and current distribution of the giant anteater in Brazil and Brazilian biomes, to identify which predictor variables best explain the occurrence of the species at different scales. Current distribution models were used to evaluate the biomes environmental suitability (i.e. probability of presence) and a gap analyses were performed. Also, priority areas for conservation were identified. The potential distribution of the anteater was better explained on a continental scale by bioclimatic (seasonality of temperature and precipitation) and topographic (altitude) variables, while the current distribution was well predicted in both scales, by land cover variables (percentages of tree cover, silviculture, and sugarcane). The Cerrado was the biome of greater environmental suitability to the species, followed by the Amazon, the Pantanal, the Atlantic Forest and the Caatinga. No recent records were obtained for the Pampas. Conservation units protect less than 10% of the current distribution of the giant anteater in the Cerrado and Pantanal. Priority areas for the species include a central corridor in the Cerrado, much of the Pantanal and ecotones. The results obtained in this study helped to fill knowledge gaps on the distribution of the giant anteater in Brazil, supporting actions for its conservation.

Submitted by Jean Medeiros (jeanletras@uepb.edu.br) on 2016-04-13T13:48:54Z No. of bitstreams: 1 PDF - Juan Diego Lourenço de Mendonça.pdf: 998454 bytes, checksum: 8501c615cfe72cc28fd6b9193f796f82 (MD5) / Approved for entry into archive by Secta BC (secta.csu.bc@uepb.edu.br) on 2016-06-13T20:27:41Z (GMT) No. of bitstreams: 1 PDF - Juan Diego Lourenço de Mendonça.pdf: 998454 bytes, checksum: 8501c615cfe72cc28fd6b9193f796f82 (MD5) / Made available in DSpace on 2016-06-13T20:27:42Z (GMT). No. of bitstreams: 1 PDF - Juan Diego Lourenço de Mendonça.pdf: 998454 bytes, checksum: 8501c615cfe72cc28fd6b9193f796f82 (MD5) Previous issue date: 2015-03-24 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / The Atlantic Forest is one of the most important "hotspot" for conservation in the world, however the north of this forest have more fragmented and less studied portion. Due to lower species richness that ferns and Lycophytes have, compared with the angiosperms, and also its restriction on microhabitats, these groups has been receiving more attention in ecological studies, given the relative practicality to inventory. Thus, we analyze how some variables can influence the floristic richness and composition of these groups in 30 sample units. We applied a multiple regression, an ordinance (CAP) and the Mantel test to see how the factors are influencing the richness and species composition. We find that the richness of these groups had a significant relationship with the latitudinal gradient, tending to increased towards the lower latitudes and in places with fewer dry months and elevated localities. Separately the richness ferns also increased with the lowest levels of the average number of dry months and historical average rainfall. Already the lycophytes had their richness related to lower levels of vegetation. The composition of the sites shown to be influenced by the geographical distance, altitude, longitude and medium and minimum length of the dry months. Thus, our study emphasizes the deterministic aspects of the richness and composition species of ferns and Lycophytes in the Northeastern Atlantic Forest. / A Floresta Atlântica é um dos mais importantes “hotspots” para conservação da biodiversidade no mundo, no entanto ao norte desta Floresta temos a porção mais fragmentada e menos estudada. Devido a menor riqueza taxonômica que as samambaias e licófitas possuem, quando comparada com as angiospermas, e também a sua restrição à microhabitats, estes grupos vem recebendo maior atenção nos estudos ecológicos, dada a relativa praticidade em inventariamento. Desta forma, buscamos analisar como algumas variáveis podem influenciar na riqueza e composição destes grupos florísticos em 30 unidades amostrais. Aplicamos uma regressão múltipla, uma ordenação (CAP) e o Teste de Mantel, para observar como os fatores estariam influenciando na riqueza e composição das espécies. Encontramos que a riqueza desses grupos apresentaram uma relação significativa com o gradiente latitudinal, tendendo a aumentar na direção das menores latitudes, nas localidades com menor número de meses secos e localidades elevadas. Separadamente a riqueza das samambaias também aumentou com os menores índices do número médio de meses secos e com a precipitação média histórica. Já as licófitas tiveram sua riqueza relacionada com os menores índices de vegetação. A composição dos sítios mostrou ser influenciada pela distância geográfica, altitude, longitude e comprimento médio e mínimo de meses secos. Desta forma, nosso estudo enfatiza os aspectos determinísticos para a riqueza e composição das espécies de samambaias e licófitas na Floresta Atlântica Nordestina.