Bias in the use of broadscale vegetation data in the analysis of habitat selection

Effective conservation efforts often depend on accurate identification of habitat requirements. Studies that identify habitat requirements for animals typically investigate use of structural habitat (vegetation) instead of functional habitat (conditions for biological fitness). The spatial scale of data could bias the match between functional and structural habitat because broadscale structural habitat maps exclude small habitat patches (inclusions) and broadscale location error can bias estimates of habitat use. To investigate how spatial scale affects the match between functional and structural habitat, we backtracked American marten (Martes americana) and fisher (Pekania [formerly Martes] pennanti) movement paths during winter and compared results from selection and tortuosity analyses conducted with broadscale (4 ha) and fine-scale (0.02 ha) structural habitat data. Functional habitat (rest sites and prey kill sites) occurred disproportionately in hemlock–cedar. Fine-scale structural habitat data detected greater selection and tortuosity within hemlock–cedar by traveling martens, but broadscale structural habitat data did not, which demonstrates that combining fine-scale location data with fine-scale structural habitat data improves the match between functional and structural habitat and understanding of habitat requirements. Selection and tortuosity indexes were poorly correlated, indicating that factors other than structural habitat influenced movement patterns. Within-stand structural habitat heterogeneity is important to martens and fishers, especially when heterogeneity includes mature conifer inclusions within primarily deciduous forests. Broadscale data may identify structural habitat associated with required types, rather than required habitat itself, when functional habitat corresponds with landscape features such as inclusions.