Aim: Identifying how climate change, habitat loss, and corridors interact to influence species survival or extinction is critical to understanding macro-scale biodiversity dynamics under changing environments. In North America, the ice-free corridor was the only major pathway for northward migration by megafaunal species during the last deglaciation. However, the timing and interplay among the late Quaternary megafaunal extinctions, climate change, habitat structure, and the opening and reforestation of the ice-free corridor have been unclear. Location: North America. Time period: 15–10 ka. Major taxa studied: Woolly mammoth (Mammuthus primigenius). Methods: For central North America and the ice-free corridor between 15 and 10 ka, we used a series of models and continental-scale datasets to reconstruct habitat characteristics and assess habitat suitability. The models and datasets include biophysical and statistical niche models Niche Mapper and Maxent, downscaled climate simulations from CCSM3 SynTraCE, LPJ-GUESS simulations of net primary productivity (NPP) and woody cover, and woody cover based upon fossil pollen from Neotoma. Results: The ice-free corridor may have been of limited suitability for traversal by mammoths and other grazers due to persistently low productivity by herbaceous plants and quick reforestation after opening 14 ka. Simultaneously, rapid reforestation and decreased forage productivity may have led to declining habitat suitability in central North America. This was possibly amplified by a positive feedback loop driven by reduced herbivory pressures, as mammoth population decline led to the further loss of open habitat. Main conclusions: Declining habitat availability south of the Laurentide Ice Sheet and limited habitat availability in the ice-free corridor were contributing factors in North American extinctions of woolly mammoths and other large grazers that likely operated synergistically with anthropogenic pressures. The role of habitat loss and attenuated corridor suitability for the woolly mammoth extinction reinforce the critical importance of protected habitat connectivity during changing climates, particularly for large vertebrates.

Forests in the southern United States with diverse forest ownership entities are facing threats associated with climate change and natural disturbances. This study represented the relationship between climate and species dominance, predicted future species distribution probability under a changing climate, and projected forest dynamics under ownership-based management regimes. Correlative statistics and mechanistic modeling approaches are implemented. Temporal scale includes the recent past 40 years and the future 60 years; spatial scale downscaled from southern United States to the coastal region of the northern Gulf of Mexico. In the southern United States, dominance of four major pine species experienced shifts from 1970 to 2000; quantile regression models built on the relationships among pine dominance and climatic variables can be used to predict future southern pine dominance. Furthermore, multiple climate envelope models (CEMs) were constructed for nineteen native and one invasive tree species (Chinese tallow, Triadica sebifera) to predict species establishment probabilities (SEPs) on the various land types from 2010 to 2070. CEMs achieved both predictive consistency and ecological conformity in estimating SEPs. Chinese tallow was predicted to have the highest invasionability in longleaf/slash pine and oak/gum/cypress forests during the next 60 years. Forest dynamics, in the coastal region, was projected by linking CEMs and forest landscape model (LANDIS) to evaluate ownership-based management regimes under climate change and natural disturbances. The dominance of forest species will diminish due to climate change and natural disturbances at both spatial scales—in the coastal region and non-industrial private forest (NIPF). No management on NIPF land was predicted to substantially increase the ratio of occupancy area between pines and oaks, but moderate and intensive management regimes were not significantly different. Pines are expected to be more resistant than oaks by maintaining stable age structures, which matched the forest inventory records. Overall, this study projected a future of southern forests on climate-species relationship, invasion risks, and forest community dynamics under multiple scenarios in the United States. Such knowledge could assist forest managers and landowners in foreseeing the future and making effective management prescriptions to mitigate potential threats.

No description available.

No description available.

Approximately 25% of bats globally are threatened, but limited data on African bats, which account for 20% of bat species, hinders our understanding of their conservation status across this ecologically diverse continent. This study combined: modelling techniques, to predict current species distributions for 58 southern African bat species and project past, current and future distributions of 22 endemic and near-endemic species; bat acoustic surveys, to assess landscape features influencing bat activity in arid and semi-arid regions; and conservation planning software to design a large-scale monitoring network for bats across this subcontinent. Species distribution models were employed using a robust and well established presence-only modelling technique (Maximum Entropy – Maxent) to model the current distributions of 58 species in southern Africa. Although the important eco-geographical variables were species- or in some cases family-specific, overall water availability (both temporary and permanent), seasonal precipitation, vegetation and karst (caves/limestone) areas were the most important factors associated with distribution patterns. These species distributions were then used to identify range-restricted and narrow niche breadth species, alongside other life-history strategies considered to put species at risk, such as Old World pteropodids and cave-dwelling bats to identify species most at risk. Nine of the 58 species in this study were identified as ‘at risk’. Considering range-restriction and endemism separately, the results showed that range-restricted species were a higher proportion (50%) of ‘at risk’ species than endemics (41%) but six of the nine identified species were endemic and range restricted (67%). If only areas of high species richness are prioritised, important areas with low species richness but rare, ‘at risk’ or endemic species would be excluded. Species distributions are not fixed but may shift due to changes in environmental conditions. Accurately predicting changes in species’ distributions due to anthropogenic climate change remains a fundamental challenge for conservation biologists, and this is amplified when dealing with taxa such as bats that are inherently difficult to study and in areas, such as Africa, with sparse ecological data. To better understand endemic bat species risk to climate change in southern Africa and to highlight historical and future likely refugia, Maxent was employed to forecast range-shifts for 22 southern African endemic or near-endemic species. Species distributions were projected during the Last Glacial Maximum (LGM ~22,000 BP), present (1950-2000) and future (2070: averaged 2061-2080, using IPCC5 scenarios) climatic conditions. Climate change was predicted to change species composition extensively within a relatively short timescale (within 60 years). By 2070, 86% of species modelled are predicted to have range contractions and six species were highlighted to be most at risk, with range contractions of more than 20%. The majority of southern Africa is composed or arid or semi-arid regions. Generally arid and semi-arid areas are overlooked and understudied due to low species richness, yet these areas are known to have a high proportion of endemic species. As part of this study, driven transects were carried out across arid and semi-arid areas to assess bat activity in these areas. Bat activity was recorded at 94% of the acoustic surveys, demonstrating that driven transects are an effective method of surveying bats in southern Africa. Bat activity increased at lower altitudes and higher latitudes, which characteristically have more rainfall, permanent water and vegetation. Although water has been shown in other studies to be important for bats, temporary water was not shown to influence bat activity and permanent water was positively correlated with bat activity for hipposiderids and rhinolophids and FM bats, which may reflect the fact that water features important for bats at smaller scale. The same two vegetation types that were consistently negatively correlated with bat activity were drier vegetation types (Karoo-Namib shrubland) and high salinity halophytic vegetation. Finally, a systematic conservation planning software tool (Marxan) was used to design multi-species monitoring networks that incorporated all 58 target species across the 11 ecoregions found in southern Africa. To ensure rare, endemic and range-restricted species were monitored at the same level as widespread species, species distributions (mapped using Maxent) were extracted by ecoregion. Monitoring targets (i.e. a percentage of species distribution across ecoregions) were standardised to ensure the same percentage of predicted distribution was included across all species (rare and widespread). To account for different resources and capacity, three optimal monitoring networks (minimum monitoring stations to achieve the monitoring targets) were proposed to survey 1, 5 or 10% of all species distributions within each ecoregion. The optimal solution for monitoring 1% of species distributions within ecoregions was found by monitoring 1,699 stations (survey sites), or for 5% 8,486 stations and finally for 10% 17,867 stations would be needed. In conclusion, the findings presented in this thesis have important conservation implications and have the potential to inform the practical steps required towards the introduction of a bat monitoring programme in southern Africa. While this study has highlighted challenges to African bat conservation, it has also demonstrated that an integrated and multi-disciplinary approach, using emerging techniques and conservation tools (e.g. conservation planning and automated call analysis software) can be used to fill knowledge gaps and inform conservation priorities in the absence of systematically collected data.

No description available.

A UGRHI-17 da bacia hidrográfica do Médio Paranapanema (São Paulo, Brasil) é reconhecidamente uma área de alta biodiversidade de espécies de Biomphalaria e possui grande vulnerabilidade a acometimentos ambientais e em saúde, no caso da esquistossomose. O objetivo do estudo foi identificar áreas de maior risco para a ocorrência da esquistossomose utilizando dados de transmissão da esquistossomose e de diversidade genética molecular, associando-os às ferramentas geoespaciais, e com isso estabelecer áreas potenciais para a vigilância malacológica e da infecção em coleções de água doce na região do Médio Paranapanema. Os moluscos do gênero de Biomphalaria foram identificados por meio de características morfológicas e moleculares; enquanto os outros grupos taxonômicos (Drepanotrema, Lymnaea, Melanoides, Physa e Pomacea) foram identificados por características conchiológicas ou morfológicas. A análise filogenética das espécies de Biomphalaria foi realizada por meio da análise de sequências dos genes mitocondriais COI, 16S rRNA e COI+16S. As sequências do gene COI referentes ao trecho DNA Barcode foram testadas quanto à similaridade com sequências depositadas no GenBank e analisadas em ABDG, bPTP e GMYC para delimitação de espécies putativas. Na análise espacial foram utilizadas as estatísticas de varredura, Gi e de fluxo. Foram utilizadas as fichas notificação e investigação dos casos de esquistossomose na região de estudo entre 1978-2016. Foi calculado as taxas de incidência e foi avaliado a dependência espacial entre os casos autóctones e importados com a função K12 de Ripley. Foram gerados mapas da distribuição espacial dos caramujos do gênero Biomphalaria; dos casos de esquistossomose ocorridos na região de estudo; e da diversidade genética em haplótipos do gene 16S. Além disso, foi realizada modelagem de nicho para estimar cenários futuros de alteração na distribuição dos caramujos, utilizado o algoritmo de máxima entropia. Foram utilizados os dados de variáveis climáticas e topográficas obtidas no WorldClim, HydroSHEDS e TOPODATA e o modelo climático regional HadGEM2-ES do período de 2041-2060, considerando dois cenários de mudança climática possíveis: RCP2.6 e RCP8.5. Foram identificados aglomerados de alto risco para ocorrência de esquistossomose em Ourinhos, Assis e Ipaussu. Entretanto, ao longo dos anos, os casos passaram a ocorrer em baixa densidade em Ourinhos e deixaram de ocorrer nos demais municípios da região. Dos caramujos coletados, 75.5% eram Biomphalaria, 11.2% Drepanotrema e 13.3% de outros gêneros não planorbídeos. O modelo de máxima entropia mostrou que há probabilidade futura da espécie B. glabrata permanecer nos municípios de Ourinhos e Assis, e uma probabilidade em torno de 50% de a espécie expandir sua colonização a corpos de água doce de outros municípios da região de estudo, isto em função das mudanças climáticas. Os resultados para B. straminea mostram que esta espécie tem maior probabilidade de expansão de colonização no futuro, especialmente nos municípios próximos a Ourinhos. A análise filogenética mostrou árvores com cinco ramos monofiléticos com alto suporte estatístico. A diversidade de haplótipos está distribuída de forma diferente em cada um dos cinco taxa analisados. Conclui-se, em um dos resultados deste trabalho, que atualmente a esquistossomose, como problema de saúde pública no Médio Paranapanema, está restrita a Ourinhos. Tal fato pode estar relacionado à presença de B. glabrata em pontos específicos e à cobertura deficiente do saneamento básico. Desta forma, o estudo contribuiu para eleger áreas prioritárias para o combate aos caramujos e à doença para evitar ou reduzir transmissões futuras nesta região. / The UGRHI-17 of the Middle Paranapanema watershed (São Paulo, Brazil) is recognized as an area of high biodiversity of Biomphalaria species and great vulnerability to environmental and health impacts for schistosomiasis. The objective of the study is to identify areas of greatest risk for the occurrence of schistosomiasis using transmission data from schistosomiasis and molecular genetic diversity, associating them with the geospatial tools, and thereby establishing potential areas for malacological surveillance and infection in collections of freshwaters in the region of Middle Paranapanema. Molluscs of the genus Biomphalaria were identified by morphological and molecular characteristics; while the other taxonomical groups (Drepanotrema, Lymnaea, Melanoides, Physa and Pomacea) were identified through conchiological or morphological characteristics. Molecular genetic analysis of the species was done through sequence analysis of the mitochondrial genes COI, rRNA16S and COI+16S. The COI gene sequences related to DNA Barcode portions were tested for similarity to sequences deposited in GenBank and analyzed ABDG, BPTP and GMYC for delimiting putative species. In the spatial analysis we used the scan statistics, Gi and flow maps. Reporting and investigation records of cases schistosomiasis in the study regions between 1978 and 2016 were used. Incidence were calculated and the existence of spatial dependence between autochthonous and imported cases was evaluated using Ripley\'s K12-function. Maps of the spatial distribution of snails of the genus Biomphalaria; cases of schistosomiasis occurred in the study region; and the genetic diversity in haplotypes of the 16S gene were generated. In addition, the ecological niche modeling to estimate future scenarios of alteration in the distribution of snails, used the maximum entropy algorithm in MaxEnt software. Climate and altitude data obtained from WorldClim, HydroSHEDS and TOPODATA and the regional climate model HadGEM2-ES from the period of 2041-2060 were used, considering two possible scenarios of climate change: Representative Concentration Pathways - RCP2.6 and RCP8.5. High-risk clusters were identified for the occurrence of schistosomiasis in Ourinhos, Assis and Ipaussu. However, over the years, cases occurred in low density in Ourinhos and ceased to occur in other municipalities in the region. Of the snails collected, 75.5% were Biomphalaria, 11.2% Drepanotrema and 13.3% of other non-planorbid genera. The maximum entropy model showed that B. glabrata is a future likely to remain in the municipality of Ourinhos and Assis and a probability around 50% of species to expand their colonization to freshwater bodies of other municipality of the study region, due to the climatic changes. The results for B. straminea showed that this is the species most likely to expand colonization in the future, especially in the municipalities near Ourinhos. The phylogenetic analysis showed trees with five monophyletic branches with high statistical support. The diversity of haplotypes is distributed differently at each of the five taxa analyzed. As one of the results of this work it was concluded that, currently, schistosomiasis as a public health problem in the Middle Paranapanema is restricted to Ourinhos. This may be related to the presence of B. glabrata at specific point and poor coverage of basic sanitation. In this way, the study contributed to the selection of priority areas for combating snails and disease in order to avoid or reduce future transmissions in this region.

Submitted by Milena Rubi (milenarubi@ufscar.br) on 2017-02-15T14:11:09Z No. of bitstreams: 1 FERREIRA_Larissa_2015.pdf: 46221411 bytes, checksum: ae8a0358ebf5e33024f58e5c75dae037 (MD5) / Approved for entry into archive by Milena Rubi (milenarubi@ufscar.br) on 2017-02-15T14:11:21Z (GMT) No. of bitstreams: 1 FERREIRA_Larissa_2015.pdf: 46221411 bytes, checksum: ae8a0358ebf5e33024f58e5c75dae037 (MD5) / Approved for entry into archive by Milena Rubi (milenarubi@ufscar.br) on 2017-02-15T14:11:31Z (GMT) No. of bitstreams: 1 FERREIRA_Larissa_2015.pdf: 46221411 bytes, checksum: ae8a0358ebf5e33024f58e5c75dae037 (MD5) / Made available in DSpace on 2017-02-15T14:11:38Z (GMT). No. of bitstreams: 1 FERREIRA_Larissa_2015.pdf: 46221411 bytes, checksum: ae8a0358ebf5e33024f58e5c75dae037 (MD5) Previous issue date: 2015-11-11 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Some conservation actions require the knowledge of the geographical distribution of species, however, this knowledge is far from being achieved for most species. The species distribution models (SDMs) have proved a useful tool to predict the distribution of species and guide field research to find new records. The SDMs using field data occurrence and environmental variables to indicate potential sites for the occurrence of a species. The quality and quantity of the data used are important to a successful result prediction models and application to conservation. The choice of environmental data and the algorithm and their settings are important for the development of models, the choice of these variables have directly influences to the quality of the models. Another very important step in modeling is the quality assessment and validation of the model, is that it may decrease the risk of accepting as true models with gross errors. The objective of this study is to evaluate the applicability of models generated by MaxEnt to find new populations of plants considering different data configurations used. For this, considering that the field validation is the most appropriate in the literature, but the most costly, the first chapter proposes a validation methodology of the models as easy application field. The methodology was able to find new records in the field, therefore, indicated for the validation of models. In the second chapter, knowing of the existence of a wide variety of variables that influence the performance of the models, the aim was to test the influence of the sample size, the spatial bias, the set of climate data and settings available for the MaxEnt algorithm in the areas of prediction potential distribution. The results demonstrated that the use of sampling and climate data restricted to the limit of the study area and also the use of soil data generate more accurate models. / Algumas ações conservacionistas necessitam do conhecimento da distribuição geográfica das espécies, porém, esse conhecimento está longe de ser alcançado para a maioria das espécies. Os modelos de distribuição de espécies (MDEs) têm se mostrado uma ferramenta útil para prever a distribuição das espécies e guiar pesquisas de campo para encontrar novos registros. Os MDEs utilizam dados de ocorrência e variáveis ambientais para indicar locais potenciais para a ocorrência de uma espécie. A precisão e quantidade dos dados utilizados são importantes para um bom resultado de predição dos modelos e aplicação à conservação. A escolha dos dados ambientais e do algoritmo e suas configurações são essenciais para o desenvolvimento dos modelos, pois influenciam diretamente na qualidade dos mesmos. Outra etapa bastante importante na modelagem é a validação do modelo, pois é ela que diminui o risco de aceitar como verdadeiros modelos que possuem erros grosseiros. O objetivo principal deste estudo é avaliar a aplicabilidade de modelos gerados pelo MaxEnt para encontrar populações de plantas, considerando diferentes configurações dos dados utilizados. Para isso o primeiro capítulo propõe uma metodologia de validação dos modelos em campo de fácil aplicação, uma vez que a validação em campo é a mais indicada pela literatura. A metodologia proposta no capítulo um é uma adaptação ao método de “caminhamento” ou método expedito de levantamento e caracterização da vegetação. A metodologia proposta foi eficaz para a localização das espécies em campo e mostrou que a caracterização da vegetação é uma etapa importante para a interpretação dos resultados, uma vez que explicou a ausência de duas espécies em áreas onde o modelo havia previsto presença. Apresenta como principal desvantagem a necessidade de pessoas experientes para o reconhecimento das espécies de plantas para a sua aplicação de forma agilizada. No segundo capítulo, foi testada a influência da área de amostragem, do conjunto de dados climáticos e das configurações do algoritmo Maxent na predição de áreas potenciais de distribuição. Os resultados obtidos demonstraram que o uso de dados amostrais e climáticos restritos aos limites da área de interesse para a busca das espécies e a inclusão de dados de solo geram modelos mais acurados. Mostrou também que as diferentes configurações do Maxent geraram modelos muito similares.

Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-07-17T13:30:07Z No. of bitstreams: 1 MarcioJoaquimDaSilva_TESE.pdf: 6572053 bytes, checksum: 24e9484e2537c31f4a72339d474f1faa (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-07-20T11:14:03Z (GMT) No. of bitstreams: 1 MarcioJoaquimDaSilva_TESE.pdf: 6572053 bytes, checksum: 24e9484e2537c31f4a72339d474f1faa (MD5) / Made available in DSpace on 2017-07-20T11:14:04Z (GMT). No. of bitstreams: 1 MarcioJoaquimDaSilva_TESE.pdf: 6572053 bytes, checksum: 24e9484e2537c31f4a72339d474f1faa (MD5) Previous issue date: 2017-04-12 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / Os ecossistemas aqu?ticos dulc?colas est?o entre os mais ricos, em termos de n?mero de esp?cies, e amea?ados por altera??es antr?picas no mundo. Impactos como a introdu??o de esp?cies n?o nativas e as transposi??es de ?guas entre bacias distintas (como ? o caso do Projeto de Transposi??o do rio S?o Francisco-PISF) amea?am a conserva??o das esp?cies. A preocupa??o com a conserva??o das esp?cies fomentou a cria??o das chamadas Unidades de Conserva??o (UCs - No Brasil foram criadas a partir de 1930 e tem n?veis de restri??o de usos diversos). Provavelmente, estes mecanismos t?m sido insuficientes na conserva??o dos peixes, pois mesmo ap?s suas cria??es, a contribui??o das esp?cies n?o nativas nas comunidades naturais s? tem crescido ao longo dos anos e ? apontada como a segunda causa de extin??o de esp?cies do planeta. Nesse contexto, o presente estudo buscou estabelecer uma padroniza??o da nomenclatura das esp?cies nas bacias envolvidas no PISF, antes da conex?o artificial, evidenciando o atual n?vel de conhecimento da ictiofauna e construir uma linha de base para detectar futuros impactos da obra. Al?m disso, objetivamos avaliar a efetividade das UCs em proteger os peixes das bacias envolvidas no projeto e modelar o risco de invas?o de esp?cies exclusivas da bacia doadora nas receptoras. Para tanto, foram utilizados registros prim?rios e secund?rios das esp?cies. Os resultados apontam para baixa similaridade entre a composi??o de esp?cies das bacias doadora e receptoras do PISF, al?m de indicar a import?ncia das UCs para conserva??o dos peixes da regi?o, que mesmo com tamanho reduzido (~1% da Caatinga) abrigam porcentagem significativa da fauna associada (entre 24 e 31% das esp?cies de cada bacia). Ademais, foi obtido que as bacias receptoras do PISF, apresentam adequabilidade para 11 esp?cies (sete fam?lias e tr?s ordens) exclusivas da bacia doadora (Leporinus friderici, Megaleporinus obtusidens, Pamphorichthys hollandi? Pimelodus maculatus, Moenkhausia sanctaefilomenae, Hemigrammus brevis, Pimelodella laurenti, Cichlasoma sanctifranciscense, Centromochlus bockmanni, Conorhynchos conirostris e Pseudoplatystoma corruscans, ordem decrescente de adequabilidade geral). Por fim, refor?amos a necessidade da cria??o/amplia??o das UCs nas bacias envolvidas, para que estas cumpram melhor o seu objetivo conservacionista e, corroboramos a necessidade do monitoramento constante da invas?o de esp?cies nas bacias receptoras das ?guas do PISF, a fim de garantir a preserva??o das comunidades ?cticas nativas. / Freshwater ecosystems are within the richest in terms of species number and are threatened by anthropic transformations worldwide. Impacts such as non-native species introduction and interbasin water transfer (like S?o Francisco River Interbasin Water Transfer Project ? SFIBWT, PISF ? in Portuguese) put species conservation in peril. The concern with this matter promoted the creation of Conservation Unities (UCs ? created from 1930?s onward in Brazil and have distinct restriction levels). Possibly, these mechanisms have been insufficient in species conservation, because even after their creation, non-native species contribution to natural communities has only grown over years and it is pointed as the second main cause of planet?s species extinction. Regarding this issue, we hereby tried to establish a species nomenclatural pattern in basins encompassed by PISF, previous to the artifitial connection, demonstrating the current ichthyofaunal knowledge level and building a baseline for future identification of the project?s impacts. Besides, we aim to evaluate the effectivity of UCs in protecting fish of the basins included in the project and model the invasiveness risk of exclusive species of donor basins to receptor ones. Therefore, we used primary and secondary records of species. The results showed a low similarity among species composition of donor and receptor basins of PISF, besides indicating the UCs? importance for regional fish species conservation. Even though these UCs have a small size (~1% of Caatinga), they contain a significant percentage of associated fauna (between 24 and 31% of each basin?s species). Lastly, we noticed the PISF receptor basins show adequability to 11 species (seven families and three orders) which were exclusive to donor basin (Leporinus friderici, Megaleporinus obtusidens, Pamphorichthys hollandi? Pimelodus maculatus, Moenkhausia sanctaefilomenae, Hemigrammus brevis, Pimelodella laurenti, Cichlasoma sanctifranciscense, Centromochlus bockmanni, Conorhynchos conirostris e Pseudoplatystoma corruscans, decending order of general suitability). Within this context, we strengthen the need of creation/enlargement of UCs in encompassed basins so these can better fulfill their conservational goals, and we also corroborate the need of constant monitoring of invasive species in receptor basins of PISF?s water in order to guarantee the preservation of native ichthyc communities.

Ecological niche modelling is a method designed to describe and predict the geographic distribution of an organism. This procedure aims to quantify the species-environment relationship by describing the association between the organism’s occurrence records and the environmental characteristics at these points. More simply, these models attempt to capture the ecological niche that a particular organism occupies. A popular application of ecological niche models is to predict the potential distribution of invasive alien species in their introduced range. From a biodiversity conservation perspective, a pro-active approach to the management of invasions would be to predict the potential distribution of the species so that areas susceptible to invasion can be identified. The performance of ecological niche models and the accuracy of the potential range predictions depend on the quality of the data that is used to calibrate and evaluate the models. Three different types of input data can be used to calibrate models when producing potential distribution predictions in the introduced range of an invasive alien species. Models can be calibrated with native range occurrence records, introduced range occurrence records or a combination of records from both ranges. However, native range occurrence records might suffer from geographical bias as a result of biased sampling or incomplete sampling. When occurrence records are geographically biased, the underlying environmental gradients in which a species can persist are unlikely to be fully sampled, which could result in an underestimation of the potential distribution of the species in the introduced range. I investigated the impact of geographical bias in native range occurrence records on the performance of ecological niche models for 19 invasive plant species by simulating two geographical bias scenarios (six different treatments) in the native range occurrence records of the species. The geographical bias simulated in this study was sufficient to result in significant environmental bias across treatments, but despite this I did not find a significant effect on model performance. However, this finding was perhaps influenced by the quality of the testing dataset and therefore one should be wary of the possible effects of geographical bias when calibrating models with native range occurrence records or combinations there of. Secondly, models can be calibrated with records obtained from the introduced range of a species. However, when calibrating models with records from the introduced range, uncertainties in terms of the equilibrium status and introduction history could influence data quality and thus model performance. A species that has recently been introduced to a new region is unlikely to be in equilibrium with the environment as insufficient time will have elapsed to allow it to disperse to suitable areas, therefore the occurrence records available would be unlikely to capture its full environmental niche and therefore underestimate the species’ potential distribution. I compared model performance for seven invasive alien plant species with different simulated introduction histories when calibrated with native range records, introduced range records or a combination of records from both ranges. A single introduction, multiple introduction and well established scenario was simulated from the introduced range records available for a species. Model performance was not significantly different when compared between models that were calibrated with datasets representing these three types of input data under a simulated single introduction or multiple introduction scenario, indicating that these datasets probably described enough of the species environmental niche to be able to make accurate predictions. However, model performance was significantly different for models calibrated with introduced range records and a combination of records from both ranges under the well established scenario. Further research is recommended to fully understand the effects of introduction history on the niche of the species. Copyright / Dissertation (MSc)--University of Pretoria, 2009. / Zoology and Entomology / unrestricted