Forest structural complexity strongly influences habitat suitability for forest-dwelling species. Airborne laser scanning (ALS) provides efficient nationwide quantification of three-dimensional forest structure, but its applications in animal ecology remain limited, particularly for understudied mustelids. Here, we combined nationwide ALS data from 173 flight campaigns with species presence-absence observations, an unprecedented scale for mustelid studies, to assess how ALS-derived forest structural metrics predict the occurrence of pine marten, stoat, and least weasel in Finland. We modeled occurrences using spatial hierarchical generalized linear mixed-effects models. ALS metrics capturing vertical complexity and canopy cover, alongside landscape and climate variables, explained broad-scale habitat associations for pine marten and stoat. Least weasel occurrence was less predictable, likely reflecting its microhabitat preferences and dependence on voles. Key predictors of mustelid occurrence included canopy height variability, mid- and upper-canopy density, and canopy cover of tree layer. Our findings show that nationwide ALS combined with species occurrence data can reveal habitat preferences of small and medium-sized mustelids, supporting conservation, monitoring and management planning. • First nationwide occurrence analysis of three mustelids in Finland. • Combined ALS data from 173 flight campaigns with species observations. • National ALS data enabled extraction of detailed forest-structure metrics. • ALS canopy-structure metrics captured habitat features for pine marten and stoat. • ALS-derived forest metrics weakly reflected habitat traits of the least weasel.
Lämsä et al. (Tue,) studied this question.
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