Open AccessDensity estimates for Canada lynx vary among estimation methods
Author(s) -
DoranMyers D.,
Kenney A. J.,
Krebs C. J.,
Lamb C. T.,
Menzies A. K.,
Murray D.,
Studd E. K.,
Whittington J.,
Boutin S.
Publication year - 2021
Publication title -
ecosphere
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.255
H-Index - 57
ISSN - 2150-8925
DOI - 10.1002/ecs2.3774
Subject(s) - distance sampling , sampling (signal processing) , mark and recapture , transect , statistics , wildlife , estimation , geography , population density , abundance estimation , global positioning system , population , environmental science , ecology , physical geography , computer science , mathematics , abundance (ecology) , biology , demography , management , filter (signal processing) , sociology , economics , telecommunications , computer vision
Unbiased population density estimates are critical for ecological research and wildlife management but are often difficult to obtain. Researchers use a variety of sampling and statistical methods to generate estimates of density, but few studies have compared estimates across methods. During 2016–2017, we surveyed Canada lynx ( Lynx canadensis ) in southwestern Yukon Territory, Canada, using track transect counts, hair snares, camera traps, live traps, and Global Positioning System (GPS) collars. From these data, we estimated lynx density with two linearly scaled count methods, one spatial mark–recapture method, three spatial mark–resight methods, and one cumulative‐time method. We found up to fivefold variation in point density estimates despite adhering to method requirements and assumptions in a manner consistent with other studies. Our results highlight the dependency of density estimates on sampling process and model assumptions and demonstrate the value of careful and unbiased sampling design. Further research is needed to fully assess the accuracy and limitations of the many wildlife density estimation methods that are currently in use so that techniques can be appropriately applied to typical study systems and species.