Remotely Sensed Fire Heterogeneity and Biomass Recovery Predicts Empirical Biodiversity Responses

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.

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Publication Details

Journal
Global Ecology and Biogeography
Published
2025-04-01
DOI
https://doi.org/10.1111/geb.70040
Citations
6
Primary Topic
Fire effects on ecosystems
Type
article
Field-Weighted Citation Impact
6.63
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article

Remotely Sensed Fire Heterogeneity and Biomass Recovery Predicts Empirical Biodiversity Responses

Tim S. Doherty, Vivianna Miritis, Owen Price, Bridget Roberts et al.
6 citations
Global Ecology and Biogeography
Fire effects on ecosystems
6.63
article

Remotely Sensed Fire Heterogeneity and Biomass Recovery Predicts Empirical Biodiversity Responses

Tim S. Doherty, Vivianna Miritis, Owen Price, Bridget Roberts, Ross Crates, Matthias M. Boer, Andrew Stauber, Elise Verhoeven, Matthew Beitzel, Chris J. Jolly, Mike Letnic, Alison Hewitt, Frank Köhler, Elise Pendall, Brian Hawkins, Rohan J. Bilney, Jonathan K. Webb, Ryan Shofner, Alex C. Maisey, George Madani, Chris McLean, Mark G. Tozer, Stephanie Pulsford, Chad T. Beranek, Jedda Lemmon, Grant J. Williamson, Grant D. Linley, Ryan R. Witt, Emma Cook, Thomas M. Newsome, Rachael H. Nolan, David Hancock, Chris A. M. Reid, John A. Gould, Fiona Grant, Euan G. Ritchie, Julia Rayment, Adam Roff, M. Lane, James M. Cook, Sarah Stock, Glenda M. Wardle, Karen J. Marsh, Berin D. E. Mackenzie, Kristina J. Macdonald, Dale G. Nimmo, Don A. Driscoll, Alfonsina Arriaga-Jiménez, Oliver Kelly, Rebecca K. Gibson, Bradley Law, Mark K. J. Ooi, David A. Keith, Craig Dunne, Alex Callen, Sally A. Power, Liz Tasker, Aaron C. Greenville, Chris R. Dickman, Amy‐Marie Gilpin, Zac C. Walker, Mikayla C. Green, Alexandria Thomsen, Shelby A. Ryan, Renée Brawata, A. O. Foster, Samantha Wallace, Brad R. Murray, Joshua S. Lee, Kaya Klop‐Toker, Andrew J. Denham, Tom D. Le Breton, Emma Spencer, Michael Mahony, V. G. Allen, Laura Schweickle, Michael Hewins
article en
6 citations

Abstract

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.

Global Ecology and BiogeographyVol. 34(4)
University of Technology Sydney (AU), Australian National University (AU), The University of Sydney (AU), University of Tasmania (AU), National Parks and Wildlife Service (AU), Australian Museum (AU), NSW Department of Planning and Environment (AU), Deakin University (AU), Charles Sturt University (AU), La Trobe University (AU), University of Wollongong (AU), Parks and Wildlife Service (AU), Australian Government (AU), Charles Darwin University (AU), UNSW Sydney (AU), NSW Forestry Corporation (AU), Central Coast Local Health District (AU), ACT Government (AU), NSW Department of Climate Change, Energy, the Environment and Water, Western Sydney University (AU), University of Newcastle Australia (AU), University of New England (AU), Macquarie University (AU)
Openalex Percentile: Top 3%
Fire effects on ecosystems
6.63
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