A trait‐based rapid assessment framework to estimate fire impacts on data‐poor Australian invertebrate taxa

Following large-scale threatening events, a key challenge is to rapidly establish which species have been most affected and are in need of urgent conservation. For data-poor taxa, such assessments are challenging. In Australia, invertebrates represent over 90% of faunal diversity and are critical for ecosystem function, yet most are undescribed, and, of the described, most are poorly known. Thus, it is important to have a way to estimate susceptibility to major disturbance of data-deficient taxa. We developed a novel trait-based method for assessing the impact of a major wildfire on invertebrates. We applied it to 1220 species that showed high distributional overlap with the 2019-2020 Australian megafires. We estimated susceptibility based on the microhabitat species occupy, their life-history and ecological traits, and mechanisms that account for key data uncertainties (number of usable occurrence records, availability of traits data, and recency of taxonomic work). We found 748 species likely to be of potential conservation concern following the megafires; 169, 579, and 454 were highly, moderately, and mildly threatened by a major fire, respectively. Most species (867) were associated with poor or very poor data quality. Of the 867 poorly known species, 97 were most at risk from a major fire. Our approach is generalizable to other data-deficient taxa and to major disturbance events globally and can be used to improve representation of poorly known species in conservation assessments and threat mitigation decisions. If the uncertainties and knowledge gaps we identified are addressed, it is likely risk prediction could be improved.

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Publication Details

Journal
Conservation Biology
Published
2026-02-06
DOI
https://doi.org/10.1111/cobi.70223
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
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article

A trait‐based rapid assessment framework to estimate fire impacts on data‐poor Australian invertebrate taxa

Payal Bal, Jessica Marsh, Libby Rumpff, John C. Z. Woinarski
Conservation Biology
Species Distribution and Climate Change
article

A trait‐based rapid assessment framework to estimate fire impacts on data‐poor Australian invertebrate taxa

Payal Bal, Jessica Marsh, Libby Rumpff, John C. Z. Woinarski
article en

Abstract

Following large-scale threatening events, a key challenge is to rapidly establish which species have been most affected and are in need of urgent conservation. For data-poor taxa, such assessments are challenging. In Australia, invertebrates represent over 90% of faunal diversity and are critical for ecosystem function, yet most are undescribed, and, of the described, most are poorly known. Thus, it is important to have a way to estimate susceptibility to major disturbance of data-deficient taxa. We developed a novel trait-based method for assessing the impact of a major wildfire on invertebrates. We applied it to 1220 species that showed high distributional overlap with the 2019-2020 Australian megafires. We estimated susceptibility based on the microhabitat species occupy, their life-history and ecological traits, and mechanisms that account for key data uncertainties (number of usable occurrence records, availability of traits data, and recency of taxonomic work). We found 748 species likely to be of potential conservation concern following the megafires; 169, 579, and 454 were highly, moderately, and mildly threatened by a major fire, respectively. Most species (867) were associated with poor or very poor data quality. Of the 867 poorly known species, 97 were most at risk from a major fire. Our approach is generalizable to other data-deficient taxa and to major disturbance events globally and can be used to improve representation of poorly known species in conservation assessments and threat mitigation decisions. If the uncertainties and knowledge gaps we identified are addressed, it is likely risk prediction could be improved.

Conservation Biology
The University of Melbourne (AU), Charles Darwin University (AU), Ecosystem Sciences (AU), The University of Adelaide (AU)
Life in Land
Openalex Percentile: Top 64%
Species Distribution and Climate Change
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