Remotely Sensed Fire Heterogeneity and Biomass Recovery Predicts Empirical Biodiversity Responses

Authors:
Open Access
Publisher website
Google Scholar
Abstract
Aim: To compare field‐based evidence of plant and animal responses to fire with remotely sensed signals of fire heterogeneity and post‐fire biomass recovery. Location: South‐eastern Australia; New South Wales. Time Period: 2019–2022. Major Taxa Studied: A total of 982 species of plants and animals, in eight taxonomic groups: amphibians, birds, fish, insects, mammals, molluscs, plants and reptiles. Methods: We collated 545,223 plant and animal response records from 47 field surveys of 4613 sites that focussed on areas burnt in 2019–2020. For each site, we calculated remotely sensed signals of fire heterogeneity and post‐fire biomass recovery, including the delayed recovery index. Meta‐regression analyses were conducted separately for species that declined after fire (negative effect sizes) and species that increased after fire (positive effect sizes) for each buffer size (250 m, 500 m, 1 km, 1.5 km, 2 km and 2.5 km radius). Results: We found that species exposed to homogenous high‐severity fire (i.e., low fire heterogeneity) were more likely to exhibit decreased abundance/occurrence or inhibited recovery. Areas with delayed recovery of biomass also had significant negative on‐ground responses, with lower abundance or occurrence in areas where biomass recovery was slower. Main Conclusions: The fire heterogeneity index and the delayed recovery index are suitable for inclusion in monitoring and reporting systems for tracking relative measures over time, particularly when field survey data is not available at the landscape scales required to support reporting and management decisions. Locations with remotely sensed signals of delayed recovery should be prioritised for protection against further disturbances that may interfere with the recovery process. Research attention must next focus on how cumulative fire heterogeneity patterns of successive fires affect the post‐fire recovery dynamics to further inform the application of remote sensing indicators as management tools for biodiversity conservation.

This publication has 54 references indexed in Scilit: