L’intensification des pratiques agricoles de ces dernières décennies a engendré des modifications profondes des écosystèmes agricoles. Les oiseaux prairiaux sont particulièrement concernés par ces changements et ont fortement décliné. La mise en place de Mesures Agro-Environnementales (MAE) n’ont pas permis d’enrayer ce déclin et une évaluation de leur efficacité passe au préalable par une compréhension affinée des réponses écologiques des espèces dans l’écosystème considéré. Nous avons ainsi tenté de mieux comprendre la distribution et la sélection d’habitat des oiseaux prairiaux dans les plaines d’inondation du bassin de la Loire dans l’ouest de la France. Cette étude visait à construire et à tester à l’échelle de la zone d’étude des prédicteurs environnementaux pertinents d’humidité, de climat, de végétation et de paysage. Il a ainsi été possible d’établir la réponse des espèces à ces prédicteurs et de construire des modèles de distribution locaux. Cette étude a permis de confirmer le rôle structurant du gradient d’humidité pour les populations d’oiseaux prairiaux en plaine alluviale. Ce gradient conditionne la qualité de l’habitat pour ces espèces en contrôlant notamment la végétation présente. Il contrôle en outre la phénologie des fauches qui est le facteur-clé dont dépend le succès reproducteur. Enfin, il est largement déterminé par la susceptibilité à l’inondation, qui peut affecter la distribution lorsqu’elle intervient au printemps induisant ainsi un découplage spatial entre les MAE et la distribution des espèces prairiales en milieu alluvial. Nous avons également mis en évidence l’évitement par les oiseaux prairiaux du bocage qui concentre par ailleurs des enjeux importants de conservation de la biodiversité. Enfin, nous avons utilisé les prédicteurs environnementaux pour modéliser la distribution des oiseaux prairiaux lesquels mettent en évidence des différences d’utilisation de l’habitat prairial entre les espèces. Ces résultats mettent en avant la nécessité de redéfinir les priorités de conservation à l’échelle du paysage. Ils pourraient également être pris en considération pour améliorer l’efficacité des MAE. / The intensification of agricultural practices in the last decades profoundly changed agricultural ecosystems. Grassland birds are particularly affected by these changes and have been declining sharply. The implementation of Agro-Environmental Schemes (AES) failed to halt this decline. Assessing their effectiveness requires a better understanding of the ecological responses of species in the ecosystem. We attempted to quantify and analyze the distribution and habitat selection of grassland birds in the floodplains of the Loire basin in Western France. This study aimed at building and testing relevant environmental predictors of moisture, climate, vegetation and landscape. Then, we established species response to these predictors and built local distribution models. This study confirmed the prominent rôle of moisture gradient for grassland bird populations in floodplains. The location on the gradient determines habitat quality for these species especially by affecting vegetation composition. It also controls the phenology of mowing, a key factor for reproductive success. Finally, this gradient is largely determined by flooding susceptibility, which may affect bird distribution when flood occurs in spring. In such years, we observed a spatial mismatch between AES and grassland bird distributions in floodplain. We also highlighted the avoidance of hedgerows by grassland birds, which stresses the incompatibility at fine scale between two objects of biodiversity conservation. Finally, we used the environmental predictors to model the distributions the main grassland birds, which models highlighted differences in habitat use between grassland species. These results emphasize the need to redefine the priorities of conservation at the landscape scale. They could also be considered to improve the efficiency of AES

Invasive species are organisms whose introduction and spread in exotic ranges result in a multitude of ecological impacts. Understanding the factors that constrain the exotic distributions of invasive species is of considerable interest. Biotic associations formed with taxa in the invaded community may be particularly important in shaping invader distributions. These associations emerge from interactions between the traits of the invasive species and some subset of the traits present in the invaded community. Focusing on how organism traits influence the outcomes of biotic interactions may inform predictions of invader distributions. This kind of trait-based approach may be most easily applied to systems where invaders specialize on particular hosts because such associations imply a close correspondence between the traits of the invader and hosts. This dissertation focuses on the South American cactus moth (Cactoblastis cactorum, Lepidoptera: Pyralidae), an invasive consumer in North America whose larvae infest prickly-pear cacti (Opuntia spp.). Chapter One is a brief introduction providing background and context to the presented research. In Chapter Two, I quantify Opuntia morphological and tissue macronutrient traits hypothesized to correlate with patterns of C. cactorum host use. Tissue macronutrient traits appear important in predicting C. cactorum infestation whereas a model containing Opuntia morphological traits had poor predictive ability. Chapter Three describes a method that uses host Opuntia identity and availability to estimate habitat suitability in order to predict the North American distribution of C. cactorum. I then simulate C. cactorum dispersal relative to scenarios of habitat suitability and Opuntia availability. Chapter Four alters the model in Chapter Three so that habitat suitability for C. cactorum is determined by the availability of trait-based groupings of Opuntia hosts. I then simulate C. cactorum dispersal via a different method from that described in Chapter Three. In Chapters Three and Four, I evaluate the degree of similarity among model predictions and the relative contribution of modeling constraints in generating variation in this similarity. Chapters Three and Four predictions were most affected by estimates of abiotic suitability and dispersal constraints, respectively. Chapter Five is a short summary of my results and a discussion of their more general applicability.

<p>This dissertation focuses on solving some common problems associated with ecological field studies. In the core of the statistical methodology, lies spatial modeling that provides greater flexibility and improved predictive performance over existing algorithms. The applications involve prevalence datasets for hundreds of plants over a large area in the Cape Floristic Region (CFR) of South Africa.</p><p>In Chapter 2, we begin with modeling the categorical abundance data with a multi level spatial model using background information such as environmental and soil-type factors. The empirical pattern is formulated as a degraded version of the potential pattern, with the degradation effect accomplished in two stages. First, we adjust for land use transformation and then we adjust for measurement error, hence misclassification error, to yield the observed abundance classifications. With data on a regular grid over CFR, the analysis is done with a conditionally autoregressive prior on spatial random effects. With around ~ 37000 cells to work with, a novel paralleilization algorithm is developed for updating the spatial parameters to efficiently estimate potential and transformed abundance surfaces over the entire region.</p><p>In Chapter 3, we focus on a different but increasingly common type of prevalence data in the so called <italic>presence-only</italic> setting. We detail the limitations associated with a usual presence-absence analysis for this data and advocate modeling the data as a point pattern realization. The underlying intensity surface is modeled with a point-level spatial Gaussian process prior, after taking into account sampling bias and change in land-use pattern. The large size of the region enforces using an computational approximation with a bias-corrected predictive process. We compare our methodology against the the most commonly used maximum entropy method, to highlight the improvement in predictive performance.</p><p>In Chapter 4, we develop a novel hierarchical model for analyzing noisy point pattern datasets, that arise commonly in ecological surveys due to multiple sources of bias, as discussed in previous chapters. The effect of the noise leads to displacements of locations as well as potential loss of points inside a bounded domain. Depending on the assumption on existence of locations outside the boundary, a couple of different models -- <italic>island</italic> and <italic>subregion</italic>, are specified. The methodology assumes informative knowledge of the scale of measurement error, either pre-specified or learned from a training sample. Its performance is tested against different scales of measurement error related to the data collection techniques in CFR.</p><p>In Chapter 5, we suggest an alternative model for prevalence data, different from the one in Chapter 3, to avoid numerical approximation and subsequent computational complexities for a large region. A mixture model, similar to the one in Chapter 4 is used, with potential dependence among the weights and locations of components. The covariates as well as a spatial process are used to model the dependence. A novel birth-death algorithm for the number of components in the mixture is under construction.</p><p>Lastly, in Chapter 6, we proceed to joint modeling of multiple-species datasets. The challenge is to infer about inter-species competition with a large number of populations, possibly running into several hundreds. Our contribution involves applying hierarchical Dirichlet process to cluster the presence localities and subsequently developing measures of range overlap from posterior draws. This kind of simultaneous inference can potentially have implications for questions related to biodiversity and conservation studies. .</p> / Dissertation

Master of Science / Department of Diagnostic Medicine and Pathobiology / Ram K. Raghavan / Dermacentor variabilis (Say) (Acari: Ixodidae), commonly known as the American dog tick is a medically important tick species in N. America, which has been implicated as a competent vector for several diseases, including tularemia, bovine anaplasmosis and canine tick paralysis. This tick is also the primary suspect for the transmission of Rickettsia rickettsii, the causative agent of Rocky Mountain spotted fever (RMSF). The spatial distribution and geographic extent of D. variabilis territory in N. America is suspected to have changed in the recent times due to natural and anthropogenic, non-stationary forces. A clear understanding of the spatial distribution and environmental factors contributing to the distribution has public health significance, allowing us to make informed management decisions and for setting robust future research goals aimed at understanding vector-biology and disease management. Additionally, ongoing climate-change is expected to alter species spatial distribution and abundance within distribution range. In this research, I studied the current and likely future spatial distribution of D. variabilis ticks in N. America based on two representative concentration pathways, RCP 4.5 and RCP 8.5, representing lower and higher emission scenarios, respectively, under several global circulation models (GCM). The spatial distribution models were constructed using MaxEnt program and BioClim data was used as environmental data for modeling. Best models were selected based on Partial ROC curves, AIC, and omission rates. Median prediction of these models indicate a wider spread of D. variabilis from its currently known extent, and much further spread as a result of climate change. Different environmental variables that significantly influenced current and future D. variabilis distribution included annual mean temperature, mean diurnal range, maximum temperature of the warmest month, annual precipitation, precipitation seasonality, and precipitation of the wettest quarter.

Projecting environmental niche models through time is a common goal when studying species response to climatic change. Species distribution models (SDMs) are commonly used to estimate a species' niche from observed patterns of occurrence and environmental predictors. However, a species niche is also shaped by non-environmental factors--including biotic interactions and dispersal barrier—truncating SDM estimates. Though truncated SDMs may accurately predict present-day species niche, projections through time are often biased by environmental condition change. Modeling niche in a phylogenetic framework leverages a clade's shared evolutionary history to pull species estimates closer towards phylogenetic conserved values and farther away from species specific biases. We propose a new Bayesian model of phylogenetic niche implemented in R. Under our model, species SDM parameters are transformed into biologically interpretable continuous parameters of environmental niche optimum, breadth, and tolerance evolving under multivariate Brownian motion random walk. Through simulation analyses, we demonstrated model accuracy and precision that improved as phylogeny size increased. We also demonstrated our model on a clade of eastern United States Plethodontid salamanders by accurately estimating species niche, even when no occurrence data is present. Our model demonstrates a novel framework where niche changes can be studied forwards and backwards through time to understand ancestral ranges, patterns of environmental specialization, and niche in data deficient species. / Master of Science / As many species face increasing pressure in a changing climate, it is crucial to understand the set of environmental conditions that shape species' ranges--known as the environmental niche--to guide conservation and land management practices. Species distribution models (SDMs) are common tools that are used to model species' environmental niche. These models treat a species' probability of occurrence as a function of environmental conditions. SDM niche estimates can predict a species' range given climate data, paleoclimate, or projections of future climate change to estimate species range shifts from the past to the future. However, SDM estimates are often biased by non-environmental factors shaping a species' range including competitive divergence or dispersal barriers. Biased SDM estimates can result in range predictions that get worse as we extrapolate beyond the observed climatic conditions. One way to overcome these biases is by leveraging the shared evolutionary history amongst related species to "fill in the gaps". Species that are more closely phylogenetically related often have more similar or "conserved" environmental niches. By estimating environmental niche over all species in a clade jointly, we can leverage niche conservatism to produce more biologically realistic estimates of niche. However, currently a methodological gap exists between SDMs estimates and macroevolutionary models, prohibiting them from being estimated jointly. We propose a novel model of evolutionary niche called PhyNE (Phylogenetic Niche Evolution), where biologically realistic environmental niches are fit across a set of species with occurrence data, while simultaneously fitting and leveraging a model of evolution across a portion of the tree of life. We evaluated model accuracy, bias, and precision through simulation analyses. Accuracy and precision increased with larger phylogeny size and effectively estimated model parameters. We then applied PhyNE to Plethodontid salamanders from Eastern North America. This ecologically-important and diverse group of lungless salamanders require cold and wet conditions and have distributions that are strongly affected by climatic conditions. Species within the family vary greatly in distribution, with some species being wide ranging generalists, while others are hyper-endemics that inhabit specific mountains in the Southern Appalachians with restricted thermal and hydric conditions. We fit PhyNE to occurrence data for these species and their associated average annual precipitation and temperature data. We identified no correlations between species environmental preference and specialization. Pattern of preference and specialization varied among Plethodontid species groups, with more aquatic species possessing a broader environmental niche, likely due to the aquatic microclimate facilitating occurrence in a wider range of conditions. We demonstrated the effectiveness of PhyNE's evolutionarily-informed estimates of environmental niche, even when species' occurrence data is limited or even absent. PhyNE establishes a proof-of-concept framework for a new class of approaches for studying niche evolution, including improved methods for estimating niche for data-deficient species, historical reconstructions, future predictions under climate change, and evaluation of niche evolutionary processes across the tree of life. Our approach establishes a framework for leveraging the rapidly growing availability of biodiversity data and molecular phylogenies to make robust eco-evolutionary predictions and assessments of species' niche and distributions in a rapidly changing world.

This research seeks to advance our understanding of how to make better informed species conservation decisions on a global scale and advance our understanding of how species' spatial distributions (their geographic ranges) may be respond to climate change, so we can know which areas should be set aside to ensure their present and future conservation. To understand how species' geographic ranges may change, it's important to first assess how geographic ranges are defined and measured. The quantifiable measurement of a species' geographic range, (its geographic range size), is a key criterion the International Union for the Conservation of Nature uses to determine the conservation status and prioritization of species worldwide. Thus, part one of this thesis evaluates different measures for how geographic range size is commonly quantified in the conservation community, to determine whether some range size measures are more reliable than others.Further, to evaluate how species' geographic ranges may respond to climate change, I examine the climatic factors influencing observable longitudinal range size gradients in the North American tree species range maps from E.L. Little's Atlas of North American Trees.

<p>Antillean manatees (Trichechus manatus manatus) were heavily hunted in the past throughout the Wider Caribbean Region (WCR), and are currently listed as endangered on the IUCN Red List of Threatened Species. In most WCR countries, including Haiti and the Dominican Republic, remaining manatee populations are believed to be small and declining, but current information is needed on their status, distribution, and local threats to the species.</p><p>To assess the past and current distribution and conservation status of the Antillean manatee in Hispaniola, I conducted a systematic review of documentary archives dating from the pre-Columbian era to 2013. I then surveyed more than 670 artisanal fishers from Haiti and the Dominican Republic in 2013-2014 using a standardized questionnaire. Finally, to identify important areas for manatees in the Dominican Republic, I developed a country-wide ensemble model of manatee distribution, and compared modeled hotspots with those identified by fishers.</p><p>Manatees were historically abundant in Hispaniola, but were hunted for their meat and became relatively rare by the end of the 19th century. The use of manatee body parts diversified with time to include their oil, skin, and bones. Traditional uses for folk medicine and handcrafts persist today in coastal communities in the Dominican Republic. Most threats to Antillean manatees in Hispaniola are anthropogenic in nature, and most mortality is caused by fisheries. I estimated a minimum island-wide annual mortality of approximately 20 animals. To understand the impact of this level of mortality, and to provide a baseline for measuring the success of future conservation actions, the Dominican Republic and Haiti should work together to obtain a reliable estimate of the current population size of manatees in Hispaniola.</p><p> </p><p>In Haiti, the survey of fishers showed a wider distribution range of the species than suggested by the documentary archive review: fishers reported recent manatee sightings in seven of nine coastal departments, and three manatee hotspot areas were identified in the north, central, and south coasts. Thus, the contracted manatee distribution range suggested by the documentary archive review likely reflects a lack of research in Haiti. Both the review and the interviews agreed that manatees no longer occupy freshwater habitats in the country. In general, more dedicated manatee studies are needed in Haiti, employing aerial, land, or boat surveys. </p><p>In the Dominican Republic, the documentary archive review and the survey of fishers showed that manatees still occur throughout the country, and occasionally occupy freshwater habitats. Monte Cristi province in the north coast, and Barahona province in the south coast, were identified as focal areas. Sighting reports of manatees decreased from Monte Cristi eastwards to the adjacent province in the Dominican Republic, and westwards into Haiti. Along the north coast of Haiti, the number of manatee sighting and capture reports decreased with increasing distance to Monte Cristi province. There was good agreement among the modeled manatee hotspots, hotspots identified by fishers, and hotspots identified during previous dedicated manatee studies. The concordance of these results suggests that the distribution and patterns of habitat use of manatees in the Dominican Republic have not changed dramatically in over 30 years, and that the remaining manatees exhibit some degree of site fidelity. The ensemble modeling approach used in the present study produced accurate and detailed maps of manatee distribution with minimum data requirements. This modeling strategy is replicable and readily transferable to other countries in the Caribbean or elsewhere with limited data on a species of interest.</p><p>The intrinsic value of manatees was stronger for artisanal fishers in the Dominican Republic than in Haiti, and most Dominican fishers showed a positive attitude towards manatee conservation. The Dominican Republic is an upper middle income country with a high Human Development Index. It possesses a legal framework that specifically protects manatees, and has a greater number of marine protected areas, more dedicated manatee studies, and more manatee education and awareness campaigns than Haiti. The constant presence of manatees in specific coastal segments of the Dominican Republic, the perceived decline in the number of manatee captures, and a more conservation-minded public, offer hope for manatee conservation, as non-consumptive uses of manatees become more popular. I recommend a series of conservation actions in the Dominican Republic, including: reducing risks to manatees from harmful fishing gear and watercraft at confirmed manatee hotspots; providing alternative economic alternatives for displaced fishers, and developing responsible ecotourism ventures for manatee watching; improving law enforcement to reduce fisheries-related manatee deaths, stop the illegal trade in manatee body parts, and better protect manatee habitat; and continuing education and awareness campaigns for coastal communities near manatee hotspots. </p><p>In contrast, most fishers in Haiti continue to value manatees as a source of food and income, and showed a generally negative attitude towards manatee conservation. Haiti is a low income country with a low Human Development Index. Only a single dedicated manatee study has been conducted in Haiti, and manatees are not officially protected. Positive initiatives for manatees in Haiti include: protected areas declared in 2013 and 2014 that enclose two of the manatee hotspots identified in the present study; and local organizations that are currently working on coastal and marine environmental issues, including research and education on marine mammals. Future conservation efforts for manatees in Haiti should focus on addressing poverty and providing viable economic alternatives for coastal communities. I recommend a community partnership approach for manatee conservation, paired with education and awareness campaigns to inform coastal communities about the conservation situation of manatees in Haiti, and to help change their perceived value. Haiti should also provide legal protection for manatees and their habitat.</p> / Dissertation

A área de pesquisa denominada Informática para Biodiversidade enfrenta o desafio de suprir a demanda por tecnologia de apoio à conservação da biodiversidade. Dentre as áreas da ecologia que se beneficiam de recursos tecnológicos, a modelagem de distribuição de espécies se destaca pelo número de ferramentas e de algoritmos desenvolvidos para os pesquisadores da área. No entanto, estudos demostram que a modelagem tem se tornado mais complexa, bem como, a necessidade por melhorias da aplicação de novas técnicas e soluções computacionais. A interoperabilidade computacional para os dados de biodiversidade, que incluem os modelos gerados pelas ferramentas de modelagem, é citada pelos autores e pesquisadores da área como uma preocupação que demanda estudos, definição de melhores práticas e soluções de computação. Cada tópico que envolve a modelagem como, algoritmos, parâmetros, dados de ocorrência, camadas ambientais, ferramentas e técnicas para a elaboração de modelos, além dos padrões de metadados e perfis de aplicação, são objetos de estudo para que seja possível a interoperabilidade nesse campo de pesquisa. Este trabalho apresenta, portanto, uma estratégia computacional para apoiar a interoperabilidade entre os modelos gerados pelas ferramentas de modelagem de distribuição de espécies, através do uso de padrões de metadados e pelo desenvolvimento de um perfil de aplicação que apoie essa interoperabilidade. São apresentados dois estudos de caso com o objetivo de validar essas estratégias e uma arquitetura computacional para apoiar comunidades de desenvolvimento de ferramentas de modelagem a buscarem essa interoperabilidade entre os dados fornecidos e processados por elas. As contribuições deste trabalho envolvem a disponibilização de um perfil de aplicação voltado para a área de modelagem de distribuição de espécies, um protótipo de software para processar os modelos gerados pelas ferramentas de modelagem, o incentivo e o uso do digital objetct identification para disponibilização dos dados, além do processo de pesquisa e da validação de metodologias que foram utilizadas para se alcançarem os resultados desta pesquisa. / The research area called Informatics for Biodiversity faces the challenge of meeting the demand for technology to support biodiversity conservation. Among the areas of ecology that benefit from technological resources, the modeling of species distribution is notable for the number of tools and algorithms developed to researchers in this area. However, studies have shown that modeling has become more complex, as well as the need for improvements in the application of new techniques and computational solutions. The computational interoperability for biodiversity data, which includes models generated by modeling tools, is cited by authors and researchers in the field as a concern that demands studies, definition of best practices and computing solutions. Each topic that involves modeling such as algorithms, parameters, occurrence data, environmental layers, tools, techniques for the elaboration of models, standards of metadata and application profiles are objects of study of this dissertation. This thesis presents a computational strategy to support the interoperability between the models generated by the modeling tools of species distribution, through the use of metadata standards and the development of an application profile that supports this interoperability. Two case studies are presented with the objective of validating these strategies and we also present a computational architecture to support communities to develop of modeling tools to seek this interoperability between the data supplied and processed by them. The contributions of this work involve the provision of an application profile for the area of species distribution modeling, a software prototype to process the models generated by the modeling tools, the incentive and use of the digital objetct identification to make data available, and in addition to the process of research and validation of methodologies that were used to summarize the results of this research.

A área de pesquisa denominada Informática para Biodiversidade enfrenta o desafio de suprir a demanda por tecnologia de apoio à conservação da biodiversidade. Dentre as áreas da ecologia que se beneficiam de recursos tecnológicos, a modelagem de distribuição de espécies se destaca pelo número de ferramentas e de algoritmos desenvolvidos para os pesquisadores da área. No entanto, estudos demostram que a modelagem tem se tornado mais complexa, bem como, a necessidade por melhorias da aplicação de novas técnicas e soluções computacionais. A interoperabilidade computacional para os dados de biodiversidade, que incluem os modelos gerados pelas ferramentas de modelagem, é citada pelos autores e pesquisadores da área como uma preocupação que demanda estudos, definição de melhores práticas e soluções de computação. Cada tópico que envolve a modelagem como, algoritmos, parâmetros, dados de ocorrência, camadas ambientais, ferramentas e técnicas para a elaboração de modelos, além dos padrões de metadados e perfis de aplicação, são objetos de estudo para que seja possível a interoperabilidade nesse campo de pesquisa. Este trabalho apresenta, portanto, uma estratégia computacional para apoiar a interoperabilidade entre os modelos gerados pelas ferramentas de modelagem de distribuição de espécies, através do uso de padrões de metadados e pelo desenvolvimento de um perfil de aplicação que apoie essa interoperabilidade. São apresentados dois estudos de caso com o objetivo de validar essas estratégias e uma arquitetura computacional para apoiar comunidades de desenvolvimento de ferramentas de modelagem a buscarem essa interoperabilidade entre os dados fornecidos e processados por elas. As contribuições deste trabalho envolvem a disponibilização de um perfil de aplicação voltado para a área de modelagem de distribuição de espécies, um protótipo de software para processar os modelos gerados pelas ferramentas de modelagem, o incentivo e o uso do digital objetct identification para disponibilização dos dados, além do processo de pesquisa e da validação de metodologias que foram utilizadas para se alcançarem os resultados desta pesquisa. / The research area called Informatics for Biodiversity faces the challenge of meeting the demand for technology to support biodiversity conservation. Among the areas of ecology that benefit from technological resources, the modeling of species distribution is notable for the number of tools and algorithms developed to researchers in this area. However, studies have shown that modeling has become more complex, as well as the need for improvements in the application of new techniques and computational solutions. The computational interoperability for biodiversity data, which includes models generated by modeling tools, is cited by authors and researchers in the field as a concern that demands studies, definition of best practices and computing solutions. Each topic that involves modeling such as algorithms, parameters, occurrence data, environmental layers, tools, techniques for the elaboration of models, standards of metadata and application profiles are objects of study of this dissertation. This thesis presents a computational strategy to support the interoperability between the models generated by the modeling tools of species distribution, through the use of metadata standards and the development of an application profile that supports this interoperability. Two case studies are presented with the objective of validating these strategies and we also present a computational architecture to support communities to develop of modeling tools to seek this interoperability between the data supplied and processed by them. The contributions of this work involve the provision of an application profile for the area of species distribution modeling, a software prototype to process the models generated by the modeling tools, the incentive and use of the digital objetct identification to make data available, and in addition to the process of research and validation of methodologies that were used to summarize the results of this research.

Conservation efforts that involve habitat protection, population augmentation, and species reintroductions require knowledge of the habitat requirements, distribution, and abundance of a species—information that can be challenging to acquire, especially for rare organisms with patchy distributions. In this thesis, I develop a protocol for the use of environmental DNA (eDNA) and create a Species Distribution Model for the endangered James spinymussel, Parvaspina collina (Unionidae). The results of this work show that eDNA is a robust tool for identifying species presence but not for estimating the relative abundance of populations. This study found that P. collina’s distribution is influenced by abiotic habitat characteristics related to sedimentation and runoff rather than by the distribution of its host fishes. The predicted habitat suitability was used to identify locations of priority conservation concern and these results can be used to direct future sampling efforts, identify potential dispersal routes, and inform conservation decisions.