Density estimation for small mammals from livetrapping grids: rodents in northern Canada

Management agencies and quantitative ecologists need robust estimates of population density. The best way of converting population estimates of livetrapped small mammals to population density is not clear. We estimated population density on livetrapping grids with 4 estimators applied to 3 species of boreal forest and 3 species of tundra rodents to test for relative differences in density estimators. We used 2 spatial estimators proposed by Efford (2009) and 2 traditional boundary-strip estimators designed for grid livetrapping. We analyzed mark– recapture data from 104 trapping sessions from the boreal forest at Kluane, Yukon (n 5 4,818 individuals), and 56 trapping sessions from tundra areas of Herschel Island and Komakuk Beach in northern Yukon (n 5 1,327 individuals). For boreal forest rodents on average both boundary-strip methods produced density estimates larger than Efford’s maximum-likelihood (ML) estimator by as much as 50% at all population densities up to 25 animals/ha. For tundra rodents both boundary-strip methods produced density estimates smaller than Efford’s ML at low density (,1.5/ha) and larger than Efford’s ML density by 36–63% at high density (25/ha). Efford’s inverse prediction estimator produced larger density estimates than the ML estimator by 4% for the boreal forest and 32% for the tundra rodents. Relationships were high between all the estimators, such that trends in density could be inferred from all methods. Determining the bias in population density estimators in small mammals will require data from populations spatially closed and completely enumerated. For our small mammals Efford’s ML estimator typically provided density estimates smaller than those produced by conventional boundary-strip estimators.