Reptiles and frogs conform to multiple conceptual landscape models in an agricultural landscape

Aim: Effective management of biodiversity in human-modified landscapes demands an understanding of how biotas respond to landscape features and management actions. Yet, biotic responses are complex and varied, resulting in numerous conceptual models being developed to aid interpretation and generalization. We examined the relevance of a range of conceptual landscape models that describe how the distribution of habitat influences species richness, abundance, occurrence and spatial dynamics, using an empirical data set of reptile and frog responses to agricultural management.
Location: South-eastern New South Wales, Australia.
Methods: We tested predictions developed from five conceptual landscape models using data collected from five land cover types and two grazing regimes.
Results: At least one species responded in a manner consistent with each of the five conceptual models tested. Most species responded to gradients of environmental variables and species-specific responses were observed, in congruence with the Continuum model. No species were consistently congruent with predictions from concepts of Island Biogeography theory. One-third of responses were congruent with the Matrix Quality model. The main prediction tested from the Matrix Tolerance model was upheld by both reptile and frog species. The predictions of the Habitat Amount hypothesis were upheld by rare reptile abundance and richness, and one frog species.
Main conclusions: Our study suggests that most conceptual models have some relevance to real-world systems and can be useful for interpreting biotic responses to landscape change and management. Importantly, no one model fully captured the range of species responses to our agricultural landscape, but the Continuum model, Matrix Quality model, Matrix Tolerance model and Habitat Amount hypothesis had complementary predictions that together appeared to explain most of the assemblage's responses to the management and environmental conditions of the agricultural landscape.