| Summary: | Context. Methods for estimating density of meso-carnivores in northern ecosystems are labour intensive and expensive to implement if mark–recapture and radio collaring are used. One alternative is to count tracks in the snow along transects as an index of density, but this method has been criticised as imprecise and lacking validation. Aims. We aimed to examine the utility of track counts along snowmobile trails in the snow for measuring changes in populations of Canada lynx and coyotes in the boreal forest of north-western Canada. Methods. We compared winter track counts of Canada lynx at three study sites and of coyotes at one site with concurrent estimates of density based on locations of radio-collared animals and estimates of numbers of uncollared animals from three 7–9-year studies in the Yukon and Northwest Territories, during a period of cyclical population fluctuations. Key results. Snow track counts were positively correlated (r2 = 0.83) with density of Canada lynx, estimated by live trapping and radio collaring in the three survey areas. Coyotes also showed a clear relationship (r2 = 0.80) between known density and snow track counts, but track counts were strongly affected by season, with much higher counts in the early winter when snow was shallower. This indicates the need to control for season or snow depth when using track counts as indices of coyote abundance. We recommend sample sizes of at least 10 track counts per winter along a 25-km transect to maximise precision. Conclusions. Snow track counts are a relatively simple, inexpensive method of concurrently tracking abundance of multiple species of meso-carnivores. These data indicate that track counts may be reliably used to monitor trends in numbers, but we suggest site-specific validation of the regressions reported here between tracks and animal abundance are required to translate these indices into estimates of density. Implications. Track counts have the potential to be an affordable alternative to more intensive methods of monitoring ...
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