Predictive habitat models derived from nest-box occupancy for the endangered Carolina northern flying squirrel in the southern Appalachians

Endangered Species Research

Jane L. Rodrigue¹  Corinne A. Diggins¹  Andrew M. Evans¹  Christine A. Kelly¹  Nicole Abaid¹  W. Mark Ford¹  Douglas Newcomb¹  Richard H. Odom¹ 

关键词: Carolina northern flying squirrel;    Topographic gradients;    Nest-box;    Occupancy;    Red spruce-Fraser fir;    Southern Appalachians;   

DOI  :  10.3354/esr00662

学科分类：动物科学

来源: Inter-Research

【 摘 要 】

ABSTRACT: In the southern Appalachians, artificial nest-boxes are used to survey for the endangered Carolina northern flying squirrel (CNFS; Glaucomys sabrinus coloratus), a disjunct subspecies associated with high elevation (>1385 m) forests. Using environmental parameters diagnostic of squirrel habitat, we created 35 a priori occupancy models in the program PRESENCE for boxes surveyed in western North Carolina, 1996-2011. Our best approximating model showed CNFS denning associated with sheltered landforms and montane conifers, primarily red spruce Picea rubens. As sheltering decreased, decreasing distance to conifers was important. Area with a high probability (>0.5) of occupancy was distributed over 18662 ha of habitat, mostly across 10 mountain ranges. Because nest-box surveys underrepresented areas >1750 m and CNFS forage in conifers, we combined areas of high occupancy with conifer GIS coverages to create an additional distribution model of likely habitat. Regionally, above 1385 m, we determined that 31795 ha could be occupied by CNFS. Known occupied patches ranged from <50 ha in the Long Hope Valley in North Carolina to approximately 20000 ha in the Great Smoky Mountains National Park along the North Carolina-Tennessee boundary. These findings should allow managers to better define, protect and enhance existing CNFS habitat and provide a basis for future surveys. Owing to model biases, we view this as only a first approximation. Further research combining den selection with foraging habitat use across the full range of elevations, landforms and forest types is needed to increase predictive accuracy of CNFS distribution and sub-population viability.

【 授权许可】

Unknown