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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Date
15//2/26/1Item status
Restricted AccessAuthor
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.