Details

Autor(en) / Beteiligte

• Crates, Ross
• Rayner, Laura
• Stojanovic, Dejan
• Scheele, Ben C.
• Roff, Adam
• MacKenzie, Jason
• Heinsohn, Robert
• Boer, Matthias

Titel

Poor-quality monitoring data underestimate the impact of Australia's megafires on a critically endangered songbird

Ist Teil von

• Diversity & distributions, 2022-03, Vol.28 (3), p.506-514

Ort / Verlag

Oxford: Wiley

Erscheinungsjahr

2022

Quelle

Wiley Online Library Journals

Beschreibungen/Notizen

• Aim Catastrophic events such as south‐eastern Australia's 2019/20 megafires are predicted to increase in frequency and severity under climate change. Rapid, well‐informed conservation prioritization will become increasingly crucial for minimizing biodiversity losses resulting from megafires. However, such assessments are susceptible to bias, because the quality of monitoring data underpinning knowledge of species' distributions is highly variable and they fail to account for differences in life history traits such as aggregative breeding. We aimed to assess how impact estimates of the 2019/20 megafires on the critically endangered regent honeyeater Anthochaera phrygia varied according to the quality of available input data and assessment methodology. Innovation Using Google Earth Engine Burnt Area Mapping, we estimated the impact of the megafires on the regent honeyeater using six monitoring datasets that differ in quality and temporal span. These datasets are representative of the variable quality of monitoring data available for assessing fire impact on 326 other threatened species; most are poorly monitored, and few have standardized, species‐specific monitoring programmes. We found that assessments based on area of occupancy (AOO), extent of occurrence (EOO) and public sightings underestimated the fire impact relative to recent, targeted monitoring datasets: a MaxEnt model, sightings from a national monitoring programme and nest locations since 2015. Using an impact threshold of 30% of habitat burned, regent honeyeaters would not meet these criteria using estimates derived from EOO, AOO or public sightings, but would exceed the cut‐off based on estimates derived from the targeted monitoring data that account for population density. Main conclusions To ensure that conservation prioritization has the greatest capacity to minimize biodiversity losses, we highlight the need to improve targeted, threatened species monitoring. We demonstrate the importance of using recent, standardized monitoring data to estimate accurately the impact of major ecological disturbances, particularly for declining, nomadic species undergoing range contractions.