Predicting defaunation: accurately mapping bushmeat hunting pressure over large areas.

Abstract

Unsustainable hunting is emptying forests of large animals around the world, but current understanding of how human foraging spreads across landscapes has been stymied by data deficiencies and cryptic hunter behaviour. Unlike other global threats to biodiversity like deforestation, climate change and overfishing, maps of wild meat hunters' movements-often based on forest accessibility-typically cover small scales and are rarely validated with real-world observations. Using camera trapping data from rainforests across Malaysian Borneo, we show that while hunter movements are strongly correlated with the accessibility of different parts of the landscape, accessibility measures are most informative when they integrate fine-scale habitat features like topography and land cover. Measures of accessibility naive to fine-scale habitat complexity, like distance to the nearest road or settlement, generate poor approximations of hunters' movements. In comparison, accessibility as measured by high-resolution movement models based on circuit theory provides vastly better reflections of real-world foraging movements. Our results highlight that simple models incorporating fine-scale landscape heterogeneity can be powerful tools for understanding and predicting widespread threats to biodiversity.