Aim: Fires can severely impact aquatic fauna, especially when attributes of soil, topography, fire severity and post-fire rainfall interact to cause substantial sedimentation. Such events can cause immediate mortality and longer-term changes in food resources and habitat structure. Approaches for estimating fire impacts on terrestrial species (e.g. intersecting fire extent with species distributions) are inappropriate for aquatic species as sedimentation can carry well downstream of the fire extent, and occur long after fire. Here, we develop an approach for estimating the spatial extent of fire impacts for aquatic systems, across multiple catchments.
Location: Southern Australian bioregions affected by the fires in 2019–2020 that burned >10 million ha of temperate and subtropical forests.
Methods: We integrated an existing soil erosion model with fire severity mapping and rainfall data to estimate the spatial extent of post-fire sedimentation threat in waterways and in basins and the potential exposure of aquatic species to this threat. We validated the model against field observations of sedimentation events after the 2019–20 fires.
Results: While fires overlapped with ~27,643 km of waterways, post-fire sedimentation events potentially occurred across ~40,449 km. In total, 55% (n = 85) of 154 basins in the study region may have experienced substantial post-fire sedimentation. Ten species—including six Critically Endangered—were threatened by post-fire sedimentation events across 100% of their range. The model increased the estimates for potential impact, compared to considering fire extent alone, for >80% of aquatic species. Some species had distributions that did not overlap with the fire extent, but that were entirely exposed to post-fire sedimentation threat.
Conclusions: Compared with estimating the overlap of fire extent with species' ranges, our model improves estimates of fire-related threats to aquatic fauna by capturing the complexities of fire impacts on hydrological systems. The model provides a method for quickly estimating post-fire sedimentation threat after future fires in any fire-prone region, thus potentially improving conservation assessments and informing emergency management interventions.