
Spatial distribution of Svalbard rock ptarmigan based on a predictive multi‐scale habitat model
Author(s) -
Pedersen Åshild Ø.,
Fuglei Eva,
HörnellWillebrand Maria,
Biuw Martin,
Jepsen Jane U.
Publication year - 2017
Publication title -
wildlife biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.566
H-Index - 52
eISSN - 1903-220X
pISSN - 0909-6396
DOI - 10.2981/wlb.00239
Subject(s) - habitat , snowmelt , vegetation (pathology) , physical geography , ecology , terrain , arctic , digital elevation model , geography , elevation (ballistics) , spatial ecology , snow , environmental science , cartography , biology , remote sensing , medicine , geometry , mathematics , pathology , meteorology
We re‐evaluated the relationship between territorial Svalbard rock ptarmigan male presence and ecological relevant variables related to vegetation, terrain and snowmelt, building on the lessons learned from a previous regional habitat multiscale model, to predict breeding habitat suitability of this high‐arctic, endemic ptarmigan on a large spatial scale. We used 11 years (2000–2010) of presence/absence data of territorial males, a multi‐scale generalized linear modelling framework (glms) and recent advances in digital satellite based vegetation mapping. The final habitat model contained four significant predictors related to vegetation, terrain (elevation and slope) and a heat load index, as a proxy for snowmelt. Increasing amount of one particular habitat type, ‘established dense Dryas heath’ influenced habitat suitability positively at a small scale, while gentle sloping landscapes of intermediate steepness (10–25°) and elevation in the upper southwest facing part of the mountain slopes characterized occurrence at the landscape scale. The best model attained a relatively high explanatory power with a good ability to discriminate correctly between used and available sites. We extrapolated the habitat model to all parts of Spitsbergen with a current growing season sufficiently long for ptarmigan to complete a breeding cycle. The model indicates that only a small proportion of the vegetation covered land area (∼3.9%) is highly suitable for ptarmigan. In Svalbard the ptarmigan is an attractive game species, appears in low densities with low annual survival, has restricted availability of breeding habitat and is likely vulnerable to climate change. In such contexts, we suggest to use our predictive habitat model in harvest management of the species so that hunting quotas and efforts may be adjusted to habitat suitability, indicating the reproductive potential, in the hunting areas.