Global ETD Search

51	Determining Drivers for Wildebeest (Connochaetes taurinus) Distribution in the Masai Mara National Reserve and Surrounding Group Ranches Sheehan, Meghan Marie 12 January 2016 (has links) No description available. Geography Geographic Information Science Biographies Animal Sciences Ecology Statistics GIS Species distribution modeling MaxEnt Bioclim Biogeography wildebeest migration Masai Mara National Reserve wildlife conservation ArcGIS East Africa animal distribution SDM
52	Spatial characterization of Western Interior Seaway paleoceanography using foraminifera, fuzzy sets and Dempster-Shafer theory Lockshin, Sam 15 July 2016 (has links) No description available. Geographic Information Science Earth Geography Geology Marine Geology Oceanography Paleoecology Paleontology Statistics paleontology GIS foraminifera species distribution modeling fuzzy sets Dempster-Shafer theory paleoceanography Western Interior Seaway Cenomanian Turonian spatial modeling Bayesian statistics Oceanic Anoxic Event uncertainty modeling ArcGIS
53	A Bayesian approach to habitat suitability prediction Lockett, Daniel Edwin IV 27 March 2012 (has links) For the west coast of North America, from northern California to southern Washington, a habitat suitability prediction framework was developed to support wave energy device siting. Concern that wave energy devices may impact the seafloor and benthos has renewed research interest in the distribution of marine benthic invertebrates and factors influencing their distribution. A Bayesian belief network approach was employed for learning species-habitat associations for Rhabdus rectius, a tusk-shaped marine infaunal Mollusk. Environmental variables describing surficial geology and water depth were found to be most influential to the distribution of R. rectius. Water property variables, such as temperature and salinity, were less influential as distribution predictors. Species-habitat associations were used to predict habitat suitability probabilities for R. rectius, which were then mapped over an area of interest along the south-central Oregon coast. Habitat suitability prediction models tested well against data withheld for crossvalidation supporting our conclusion that Bayesian learning extracts useful information available in very small, incomplete data sets and identifies which variables drive habitat suitability for R. rectius. Additionally, Bayesian belief networks are easily updated with new information, quantitative or qualitative, which provides a flexible mechanism for multiple scenario analyses. The prediction framework presented here is a practical tool informing marine spatial planning assessment through visualization of habitat suitability. / Graduation date: 2012 Habitat suitability Bayesian Species Distribution Modeling GIS Marine spatial planning wave energy renewable energy Belief network benthic invertebrates machine learning predictive modeling ecological modeling probabilistic modeling Sea floor mapping Habitat classification Maximum likelihood
54	Influence multi-échelle des facteurs environnementaux dans la répartition du Desman des Pyrénées (Galemys pyrenaicus) en France / Multi-scale influence of environmental factors in the distribution of the Pyrenean desman (Galemys pyrenaicus) in France Charbonnel, Anaïs 04 June 2015 (has links) L’écologie du Desman des Pyrénées (Galemys pyrenaicus), mammifère semi-aquatique endémique de la péninsule ibérique et des Pyrénées, demeure encore très peu connue. Les objectifs de cette thèse, dans le cadre d’un Plan National d’Actions, ont été d’identifier les variables environnementales agissant sur la répartition de l’espèce à différentes échelles spatiales, en considérant sa détectabilité imparfaite (i.e. fausses absences et fausses présences). Une probabilité de détection élevée, mais spatialement hétérogène à l’échelle des Pyrénées françaises, a été mise en évidence. La distribution du Desman des Pyrénées s’est également révélée spatialement structurée et majoritairement influencée par des facteurs propres aux milieux aquatiques, mais en forte régression depuis les années 80. Ces résultats ont permis de proposer des mesures de conservation pour cette espèce menacée. / The ecology of the Pyrenean desman (Galemys pyrenaicus), a small semi-aquatic mammal endemic to the Iberian Peninsula and the Pyrenees, remains still largely unknown. The aim of this PhD thesis conducted within the framework of a National Action Plan was to identify the environmental variables influencing the Desman distribution at various spatial scales, by accounting for its imperfect detection (i.e. false absences and false presences). A high, but spatially heterogeneous at the French Pyrenees extent, probability of detection was highlighted. The distribution of the Pyrenean Desman was also emphasized to be spatially structured and mainly influenced by aquatic factors, but severely contracting for the last 25 years. These results enabled to suggest conservation measures for this endangered species. Biologie de la conservation Galemys pyrenaicus Pyrénées françaises Suivi Modèles de distribution d’espèces Modèles d’occupation de sites Détection Réplicas spatiaux Echelle spatiale Hydrologie Favorabilité d’habitat Changements globaux Conservation biology Galemys pyrenaicus French Pyrenees Monitoring Species distribution modeling Site occupancy modeling Detection Spatial replicates Spatial scale Hydrology Habitat suitability Global change

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