Incorporating altered fire frequency scenarios in species distribution models improves climate change predictions for tropical savanna birds

Abstract

Biodiversity conservation in the face of changing climate requires reliable predictions of species distributions. Distribution models need to include variables that strongly influence species persistence. Species will be affected by climate change directly by altering the amount and location of suitable climatic space, and indirectly by climate driven modification of habitat. While climate is a good predictor of species distributions, biotic and abiotic landscape factors also influence distribution. Very few studies of climate change effects on biodiversity have included key landscape factors in distribution modelling, despite recognition that landscape alteration through processes such as fire and land clearing changes fauna patterning. For birds in Australian tropical savannas, change in fire regimes is a critical conservation issue, linked to species decline. While species may show gradual shifts in distribution due to changes in temperature and rainfall, species are likely to show a more immediate response to changes in fire as a result of climatic changes. This study examines species' responses to changes in fire by projecting species distribution modelling algorithms built using Maxent onto scenarios with increased fire frequency. We accounted for important static landscape elements by including remnant vegetation and soil spatial layers. This study identified that increased fire frequency alters the predictions for birds by changing the amount of suitable habitat. Climate change combined with increased fire frequency will reduce available habitat; more than simply using climate predictions alone. Our results demonstrate the importance of including landscape factors into distribution modelling when generating species predictions. Understanding the impacts of landscape factors on bird distributions, in particular fire, is a critical step in conservation planning and adaptation of land management for combating biodiversity loss due to climate change