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dc.contributor.advisorBuchanan, Graeme
dc.contributor.advisorWoodhouse, Iain
dc.contributor.authorStolyarov, Serjay
dc.date.accessioned2015-11-20T11:43:52Z
dc.date.available2015-11-20T11:43:52Z
dc.date.issued20/11/2015
dc.identifier.urihttp://hdl.handle.net/1842/11807
dc.description.abstractBirds are crucial parts of ecosystems and good indicators of the state of natural environments of the planet. As empirical evidence suggests, bird’s populations around the world are declining due to habitat loss from agricultural activities, deforestation and increasing effects from climate change, particularly in areas of Africa which are greatly abundant and rich in biodiversity. Africa is home for very large number of endemic birds, distributions and environments of which we still do not fully understand. Disentangling the relative influence of climate and land cover can improve conservation efforts to reduce loss of natural habitat or introduce adaptive management for climate change. This project uses Species Distribution Modelling (SDM) to analyse African bird species response to Normalised Difference Vegetation Index (NDVI) and climate variables for identification of hotspots of birds which are particularly influenced by land cover or by climate. The results have shown that out of 1503 modelled birds, 892 (59%) were particularly climate responsive, 400 (27%) are equally responsive and 211 (14%) are particularly NDVI responsive. Additionally, for 55% - 65% of species, combined modelling approach yielded higher model performance, while 25% - 30% of distributions were better explained by climate alone and 5% - 10% by NDVI alone. Both NDVI responsive and climate responsive are proportionally equally vulnerable under IUCN threatened list and climatic vulnerability traits. Vulnerability assessment of hotspots highlights dire need to improve Protected Area networks in order to preserve threatened species, many of which are endemic.en
dc.language.isoenen
dc.publisherThe University of Edinburghen
dc.subjectSpecies distribution modelling, SDM, Mahalanobis Distance, NDVI, land cover, climate, birds, Africa, hotspotsen
dc.subjectMSc Geographical Information Scienceen
dc.subjectGISen
dc.titleIdentifying vulnerable hotspots of land cover or climate dependant bird species in Africa, using species distribution modellingen
dc.typeThesis or Dissertationen
dc.type.qualificationlevelMastersen
dc.type.qualificationnameMSc Master of Scienceen
dcterms.accessRightsRestricted Accessen_US


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