Understanding how climate determines species’ geographic distributions is an important question in ecology with direct implications for predicting climate change-driven range shifts. For Lepidoptera, growing degree-days, a measure of growing season length, has been shown to be an important predictor of species’ distributions in some cases. Most studies use a standardized estimate of base development temperature in their calculations of growing degree-days instead of a species-specific threshold so past investigations of the influence of growing degree-days on Lepidoptera distributions may not have been optimal. Species distribution models (SDMs) are a commonly used approach in ecology that typically only implicitly capture the underlying processes that limit a species’ distribution. A species-specific estimate of growing degree-days should better characterize these processes than standard thermal thresholds and thus improve the accuracy of species distribution models. In this thesis, I use species distribution modelling to model the geographic distribution of 30 moth species native to North America. I ask whether a) growing degree-days are the best climatic predictor of these moth species distributions at broad scales; b) a lab-estimated biological threshold (i.e., BDT) can scale up and improve the predictive ability of SDMs; and c) the quality of experiments used to estimate species-specific BDT influences the predictive accuracy of SDMs. To do so, I compare the predictive accuracy of a correlative model based on a commonly-used thermal threshold to define growing degree-days to a hybrid model with degree-days defined based on a species-specific thermal threshold. I found that the predictive performance of the hybrid models was indistinguishable from the correlative models likely because growing degree-days was not the best climatic predictor of the geographic distributions of the majority of these moth species. I also found that there was no link between the quality of the lab experiments and the difference in performance of the hybrid and correlative models. My findings suggest that lab-estimated thermal thresholds may not always scale up to be predictive at a broad scale and that more work is needed to leverage the data from lab experiments into broad scale SDMs. Determining the ultimate factors that limit species’ distributions will be critical in accurately predicting species’ range shifts response to future climate change.

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Made available in DSpace on 2016-06-02T19:26:23Z (GMT). No. of bitstreams: 1 TOCHET_Caroline_2013_V_ 1.pdf: 367702 bytes, checksum: e45cebba8c597ec047bc77ddd848aef5 (MD5) Previous issue date: 2013-11-29 / Universidade Federal de Sao Carlos / The Cerrado biome is located in Central Brazil Plateau occupying 2,036.448 km². Its weather is characterized by seasonality and the landscape by a vegetation mosaic. Those factors contribute for Cerrado to be known as the richest savanna in the world. It is considered one of the 20 World Hotspots, because of its high level of diversity and threat. The Cerrado is still poorly known, especially in relation to its history, origin and distribution through time, which are important factors to comprehend its recent diversity. This project aims to determine the historically stable areas within Cerrado by modelling 14 marsupial and small rodent species potential distribution for past and present scenarios, to relate the detected areas with endemism levels, to compare the identified patterns with known biogeography hypothesis of other Cerrado organism groups, and to suggest priority areas for inventory. To generate the potential distribution maps I used the digital bases available by WWF and IBGE and the SIG ARCMAP 10.1 software. The potential distribution modelling was implemented by maximum-entropy algorithm (MAXENT), using WORLDCLIM 1.4 and PALEOCLIMATE MODELING INTERCOMPARISON PROJECT (PMIP) climate variables data. The open vegetation biomes of South America were the base area for modelling, with 2.5 layers resolution (ca. 5 km²). To statistically evaluate model performance, I used the area under the curve (AUC) of the receiver operating characteristic (ROC) plot. All models presented high AUC values. The hypothesis that during the Last Glacial Maximum (LGM) the open formations expanded and the forest ones retracted, while the open formations retracted and forests expanded during the Last Interglacial (LIG) were supported by 20 of the 28 proposed models. The historically stable areas include the Parecis , Chapada dos Guimarães, Chapada Diamantina and Central Brazil Plateaus, the western Minas Gerais and the Espinhaço range. Those areas agree to other historically stable areas and/or endemism areas already proposed for other taxa, such as birds, squamate reptiles, anuran, lepdoptera and plants. They also reflect lack of inventory data. So, the fauna of those areas should be better investigated and its material used in future phylogenetic and phylogeographic studies. Conservation should also be considered in the light of their climatic stability, resulting in the possible creation, increasing or maintaining of Conservation Units. / O bioma Cerrado localiza-se no planalto do Brasil Central e ocupa uma área de 2.036.448 km²; tem seu clima marcado pela sazonalidade e é constituído por um mosaico de diferentes fitofisionomias, um dos fatores que mais contribui para que seja a savana com maior riqueza de espécies do mundo. Por ser um bioma com alto nível de diversidade e estar dentre os mais ameaçados do planeta, é considerado um dos 20 hotspots mundiais. Apesar disto, pouco se conhece a respeito do Cerrado, em especial sobre sua história, incluindo sua origem e distribuição ao longo do tempo, fatores muito importantes para a compreensão da atual diversidade presente no bioma. Este projeto tem como objetivos determinar áreas historicamente estáveis no Cerrado a partir de modelos de distribuição potencial de 14 espécies de marsupiais e pequenos roedores para cenários passados e atuais, relacionar as áreas detectadas com aquelas que atualmente possuem maior concentração de espécies endêmicas, e comparar os padrões levantados em relação a hipóteses biogeográficas já propostas para outros organismos que habitam o Cerrado, além de sugerir áreas prioritárias para inventário. Para produzir os mapas de distribuição potencial foram utilizadas bases digitalizadas disponibilizadas pela WWF e pelo IBGE e o software SIG ARCMAP 10.1. Para a modelagem foi utilizado o algoritmo de máxima entropia (MAXENT). As variáveis climáticas foram obtidas a partir da base de dados do WORLDCLIM 1.4 e do PALEOCLIMATE MODELING INTERCOMPARISON PROJECT (PMIP) e a área considerada para gerar os modelos foi aquela que incluiu as formações abertas da América do Sul, conhecida como Diagonal Seca , com resolução das camadas ambientais de 2.5 (ca. 5 km²). Para verificar o desempenho dos modelos produzidos foi utilizada a análise da área sob a curva (area under the curve, AUC) ROC (Receiver Operating Characteristic). Todos os modelos gerados apresentaram alto valor de AUC. A hipótese de que durante os períodos glaciais, como o Último Máximo Glacial (Last Glacial Maximum LGM), as formações abertas teriam se expandido e as áreas florestadas se retraído, e durante os períodos inter-glaciais, como o Último Inter-glacial (Last Interglacial LIG), o oposto teria acontecido, isto é, expansão das formações florestais e retração das áreas abertas, foi corroborada por 20 dos 28 modelos propostos. As áreas historicamente estáveis geradas pelos modelos das 14 espécies incluem o Planalto dos Parecis e a Chapada dos Guimarães (MT), o Planalto Central brasileiro (GO e DF), o oeste de Minas Gerais, na região leste do Triângulo Mineiro, a Serra do Espinhaço (MG) e a Chapada Diamantina (BA). Essas áreas aqui identificadas condizem com áreas historicamente estáveis e/ou áreas de concentração de endemismos anteriormente propostas para outros táxons como aves, répteis Squamata, anuros, lepidópteros e plantas. Os modelos também apontaram estas áreas como áreas de lacunas de amostragem, representando regiões a serem melhor investigadas em campo quanto à sua fauna e possível fonte de material para estudos futuros de filogenia e filogeografia. Além disso, são importantes para conservação, tendo em vista sua estabilidade climática, representando possíveis áreas alvo de criação, ampliação e manutenção de Unidades de Conservação.

Tanzania’s Ruaha landscape is an international priority area for large carnivore conservation, harbouring roughly 10% of the world’s lions, and important populations of leopards and spotted hyaenas. However, these large carnivore populations are threatened by intense retaliatory killing due to human-carnivore conflict on village land around Ruaha National Park (RNP), mostly as a result of livestock predation by lions, leopards and spotted hyaenas. Moreover, a current lack of ecological data on the distribution of these carnivores hinders the development of effective strategies for conservation and targeted conflict mitigation in this landscape. This study aimed to identify the most significant ecogeographical variables (EGVs) influencing the distribution of lions, leopards and spotted hyaenas across the Ruaha landscape, and to map areas of conservation importance for these species. In addition, the study assessed the influence of EGVs on livestock predation risk by these carnivores in the village land around RNP, and generated a predictive map of predation risk. The relative importance of livestock husbandry practices and EGVs in terms of influencing predation risk within enclosures was also investigated. Proximity to rivers was the most important variable influencing the distribution of large carnivores in Ruaha, and contributed to predation risk of grazing livestock. The traditional livestock husbandry adopted in bomas appeared insufficient to alleviate the inherent risk of predation by large carnivores. The study produced the first detailed maps of lion, leopard and spotted hyaena distribution in the critically important Ruaha landscape, and identified likely livestock depredation hotspots. These results will target conflict mitigation approaches around Ruaha, by identifying particularly high-risk areas for livestock enclosures and grazing stock. Improving husbandry in these areas could help reduce livestock depredation and retaliatory carnivore killing, therefore reducing one of the most significant conservation threats in this critically important landscape.

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.

Climate change is one of the most important factor determining species ranges. In Europe there is now evidence for northward areal expansion in many Mediterranean insects including the praying mantis (Mantis religiosa). This species is the only representative of the order Mantodea inhabiting central Europe. The northern edge of the species distribution currently reaches latitude 53ř North. Although, the praying mantis is well known insect there is not enough evidence about its phylogeography. In this work three mitochondrial genes (COI, COII, Cyt b) were selected for phylogenetic study. Results indicate three statistically supported distinct lineages in Europe: Eastern European, Central European and Western European. Presumably these lineages are consistent with isolation during the last glacial and re-colonization from glacial refugia. Reduced haplotype diversity on the northern edge suggests currently established populations at the northern distribution border. To validate mtDNA results it was also considered four microsatellite loci. Due to different type of inheritance mtDNA and nuclear DNA it is possible to compare two independent genetic datasets. Microsatellite analysis confirmed results obtained on mitochondrial data. Three major genetic clusters were found: east, west and central. Spatial...

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.

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.