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Analysis of historic Carolina northern flying squirrel monitoring data and assessment of acoustical monitoring techniques

Red spruce (Picea rubens)-northern hardwood habitat for the northern flying squirrel (Glaucomys sabrinus) in the southern Appalachians


September 2011 - September 2013


The endangered Carolina northern flying squirrel (CNFS: Glaucomys sabrinus coloratus) occurs on a limited number of isolated/disjunct mountain peaks > 1400 m in North Carolina, Tennessee and Virginia in northern hardwood forests and mixed forests of northern hardwood-red spruce (Picea rubens), red-spruce-Fraser fir (Abies fraseri), and northern hardwood-eastern hemlock (Tsuga canadensis) (Ford et al. 2007). Naturally isolated since the end of the Pleistocene, CNFS habitat was further degraded by exploitative logging and wildfire at the turn of the 20th Century. Subsequent habitat recovery has been tempered by continued threats to these forest communities from exotic insect infection, (i.e., balsam woolly adelgid, Adelges piceae; hemlock woolly adelgid, A. tsugae), atmospheric acid deposition, recreational development, and climate change. On private land, further habitat loss occurs with second-home development. Den site and parasite-mediated competition with southern flying squirrels (G. volans) is an added stressor that probably limits CNFS at mid-elevations, particularly in the presence of significant hard mast species such as northern red oak (Quercus rubra) (Ford et al. 2007).

Survey protocols using nest box transects to determine presence/absence and persistence of the CNFS and the similarly endangered Virginia northern flying squirrel (G.s. fuscus) in West Virginia and northwestern Virginia have changed little since both subspecies were listed in 1986. As an inventory technique, it produces occupancy results slowly, though with reasonable detection probabilities (> 0.6) over multiple years (Ford et al. 2010). Nest box data also has provided some detail about northern flying squirrel demographics, i.e., timing of parturition and litter size (Reynolds et al. 1999) and has provided the basis for predictive habitat modeling at medium to large-landscape scales (Odom et al. 1999, Menzel et al. 2006). Despite annual or multiple intra-year surveys over successive years with some recapture of marked individuals, albeit small (Reynolds et al. 1999), no effort has been undertaken to examine the efficacy of nest-box data for use in calculating metrics on survival, relative population size, population rate of change, emigration, immigration or movement probabilities – critical data needs identified in the subspecies’ recovery plan (U.S. Fish and Wildlife Service 1990). Because nest-box monitoring is labor intensive and logistically challenging, the inability to generate these parameters might provide a rationale to discontinue nest-box monitoring in lieu of other survey techniques that either could generate these data or simply provide presence-absence data suitable for occupancy modeling with less intensive effort. However, if nest-box data can be used to generate meaningful population measures and characteristics, these could be linked with habitat and land cover delineations from remotely-sensed data and/or improved predictive land cover data comprehensive habitat and population management within whole geographic recovery units to address action items from the subspecies’ recovery plans.

Project objectives

1)Compile, review, analyze and characterize the North Carolina Wildlife Resource Commission’s Carolina northern flying squirrel nest box monitoring dataset;

2)provide a characterization of data variance and determine if nest box capture data can be used to assess mark-recapture based estimates of population size, population trends and survival rates using Program Mark or if nest box capture data can only provide robust occupancy estimates using Program Mark or Program Presence;

3)evaluate and provide recommendations for improving statistical power, precision and accuracy of data collected by nest box monitoring whether from mark-recapture or presence-absence such as incorporation of habitat quality rankings or spatial attributes of patch size and configuration in an AIC modeling approach; and

4)create database tools to facilitate analysis of extant and future Carolina northern flying squirrel data (e.g., recapture queries).


Current Staff

Federal Staff: 102

Masters Students: 243

Phd Students: 163

Post Docs: 57

University Staff: 254

5 Year Summary

Students graduated: 699

Scientific Publications: 1910

Presentations: 4358



Funding Agencies

  • North Carolina Field Office


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