Identifying vulnerable hotspots of land cover or climate dependant bird species in Africa, using species distribution modelling
dc.contributor.advisor
Buchanan, Graeme
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dc.contributor.advisor
Woodhouse, Iain
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dc.contributor.author
Stolyarov, Serjay
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dc.date.accessioned
2015-11-20T11:43:52Z
dc.date.available
2015-11-20T11:43:52Z
dc.date.issued
2015-11-20
dc.description.abstract
Birds 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.
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dc.identifier.uri
http://hdl.handle.net/1842/11807
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en
dc.publisher
The University of Edinburgh
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dc.subject
MSc Geographical Information Science
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dc.subject
GIS
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Species distribution modelling
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dc.subject
SDM
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Mahalanobis Distance
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NDVI
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dc.subject
land cover
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dc.subject
climate
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dc.subject
birds
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Africa
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hotspots
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dc.title
Identifying vulnerable hotspots of land cover or climate dependant bird species in Africa, using species distribution modelling
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dc.type
Thesis or Dissertation
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dc.type.qualificationlevel
Masters
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dc.type.qualificationname
MSc Master of Science
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dcterms.accessRights
RESTRICTED ACCESS
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