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Modelling habitat suitability for capercaillie (Tetrao urogallus) in Scotland under future climate and forest scenarios: using Maxent to model the combined influence of biotic and abiotic factors affecting capercaillie distribution

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Ratcliffe2015 2.pdf (3.153Mb)
Date
15//2/26/1
Item status
Restricted Access
Author
Christine, Ratcliffe
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Abstract
Capercaillie (Tetrao urogallus), a large charismatic woodland grouse native to Scotland, are at risk of extinction. Their population has rapidly declined since the 1970s and the reasons for this are not clearly understood. Loss of habitat and climate change are two of the main theories explored in this paper. This study uses a software called Maxent which takes a probabilistic modelling approach and employs machine learning techniques to create a Habitat Suitability Map (HSM). The results identify which climatic and physical environmental characteristics most influence the current distribution of capercaillie. This is used to evaluate how much of the current landscape meets the needs of capercaillie based on their habitat preferences. The HSM for capercaillie is then ‘projected’ onto future climate in order to assess how robust capercaillie are to climate change. Two future climate scenarios are considered for climate in 2070 to investigate the effect of high and low emissions of greenhouse gases, as defined by the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways. The influence of future forest scenarios are considered jointly with climate change. Often bioclimatic variables are solely used to assess habitat suitability as there is good evidence that vegetation cover is strongly determined by climate. The results here show that explicitly including vegetation cover, especially for a species such as capercaillie that are heavily depended on a single species of tree (Scots Pine, Pinus sylvestris), significantly improves present day HSMs and drastically alters the predicted effects of climate change.
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http://hdl.handle.net/1842/10572
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  • GeoSciences MSc thesis collection

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