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Strong influence of local habitat structure on mammals reveals mismatch with edge effects models
- Villaseñor, Nélida R., Blanchard, Wade, Driscoll, Don A., Gibbons, Philip, Lindenmayer, David B.
- Landscape ecology 2015 v.30 no.2 pp. 229-245
- Antechinus, Vulpes vulpes, cats, dogs, edge effects, fauna, habitats, landscapes, models, possums, rats, understory, urban planning, Australia
- CONTEXT: What determines mammal occurrence across wildland-urban edges? A better understanding of the variables involved will help update edge effects theory and improve our ability to conserve biota in urbanizing landscapes. OBJECTIVES: For the first time, we tested whether the occurrence of mammals across urban-forest edges and forest interiors was best predicted by: (1) edge variables (i.e. edge type and distance to an urban boundary), (2) local habitat structure (e.g. proportion of understory cover), or (3) edge variables after accounting for local habitat structure. METHODS: Using 77 camera stations in South-Eastern Australia, we quantified the factors influencing the occurrence of five native mammals (brown antechinus, bush rat, common brushtail possum, black wallaby and long-nosed bandicoot) and three non-native mammals (red fox, cat, and dog). RESULTS: The occurrence of most native and non-native mammals was best predicted by local habitat structure rather than by edge variables. Although edge variables had effects on most species occurrences, local habitat structure outweighed the impacts of edge effects. CONCLUSIONS: Our findings are important for management and urban planning as they suggest that local-scale management of habitat and habitat retention at urban edges will mitigate urban impacts on fauna. Our work reveals a critical mismatch in the spatial scale of predictive variables commonly used in edge effects models (edge types and distance to a boundary) compared with the smaller scale of local habitat variables, which underlie most species occurrence. We emphasize the need to consider heterogeneity within patches in predictive frameworks of edge effects.