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An evaluation of genetic survey methods for bobcats in western Maryland
Author(s) -
Lamp Kevin J.,
Holland Angela M.,
Waits Lisette P.,
Bowman Jacob L.
Publication year - 2025
Publication title -
wildlife society bulletin
Language(s) - English
Resource type - Journals
ISSN - 2328-5540
DOI - 10.1002/wsb.1592
Abstract Noninvasive genetic survey (NGS) methods are a common technique used for monitoring solitary species; however, researchers and managers may have trouble determining which survey method(s) are suitable for a specific study. Research evaluating various NGS methods provides valuable information beneficial to those making decisions about study design. For bobcats ( Lynx rufus ) in western Maryland, we compared 3 NGS methods (i.e., hair snaring, scat sampling, and snow tracking) by number of detections produced, detections per hour worked, and number of individually identified samples. During January through March of 2019, we visited 120 hair snares weekly to collect hair samples and maintain cameras positioned to view hair snares. Simultaneously, we surveyed transects consisting of hiking trails and closed roads to collect scat samples and locate bobcat track lines. We followed track lines to collect hair in tracks or on natural snags (e.g., thorns). Our hair snares produced 5 detections and one individual identified over 960 trap weeks and 1,688 hours of work (0.003 detections/hour worked). We surveyed 318 km of scat transect over 128 hours and produced 9 bobcat detections (0.07 detections/hour worked) with 5 samples identified to the individual level. We surveyed 626 km of transect for bobcat track lines over 240 hours and produced 8 bobcat detections (0.03 detections/hour worked) but identified none to the individual level. Our results suggest scat sampling was more effective at producing bobcat detections than hair snaring or snow tracking. In addition, scat sampling offered a greater proportion of samples identified to individuals, which may be important for managers attempting to estimate abundance.

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