Habitat in flames: How climate change will affect fire risk across koala forests

被引:4
|
作者
Shabani, Farzin [1 ]
Shafapourtehrany, Mahyat [2 ]
Ahmadi, Mohsen [3 ]
Kalantar, Bahareh [4 ]
Ozener, Haluk [2 ]
Clancy, Kieran [5 ]
Esmaeili, Atefeh [6 ]
da Silva, Ricardo Siqueira [7 ]
Beaumont, Linda J. [8 ]
Llewelyn, John [9 ,10 ]
Jones, Simon [11 ]
Ossola, Alessandro [12 ,13 ]
机构
[1] Qatar Univ, Coll Arts & Sci, Dept Biol & Environm Sci, POB 2713, Doha, Qatar
[2] Bogazici Univ, Kandilli Observ & Earthquake Res Inst, Dept Geodesy, TR-34680 Istanbul, Turkiye
[3] Isfahan Univ Technol, Dept Nat Resources, Esfahan, Iran
[4] RIKEN Ctr Adv Intelligence Project, Disaster Resilience Sci Team, Goal Oriented Technol Res Grp, Tokyo 1030027, Japan
[5] Flinders Univ Tonsley, Coll Sci & Engn, GPO Box 2100, Adelaide, SA 5001, Australia
[6] Univ New England, Sch Environm & Rural Sci, Armidale, NSW 2351, Australia
[7] Fed Univ Vales Jequitinhonha & Mucuri, Dept Agron, BR-39100000 Diamantina, MG, Brazil
[8] Macquarie Univ, Sch Nat Sci, Sydney, NSW, Australia
[9] Flinders Univ S Australia, Coll Sci & Engn, Global Ecol Partuyarta Ngadluku Wardli Kuu, Adelaide, SA, Australia
[10] ARC Ctr Excellence Australian Biodivers & Heritage, Wollongong, Australia
[11] RMIT Univ, Sch Sci, Melbourne, Vic 3000, Australia
[12] Univ Calif Davis, Davis, CA USA
[13] Univ Melbourne, Fac Sci, Sch Agr Food & Ecosyst Sci SAFES, Melbourne, Vic, Australia
关键词
Climate change; 60 main tree species browsed by koalas; Decision Tree machine learning algorithm; Fire; NEW-SOUTH-WALES; LANDSLIDE SUSCEPTIBILITY; PHASCOLARCTOS-CINEREUS; CONDITIONING FACTORS; EXTINCTION RISK; MODELS; SHIFTS; TRENDS; IMPACT; CONSERVATION;
D O I
10.1016/j.eti.2023.103331
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Aim: Generate fire susceptibility maps for the present and 2070, to identify the threat wildfires pose to koalas now and under future climate change. Location: Australia. Time period: Present and 2070. Major taxa studied: 60 main tree species browsed by koalas. Method: The Decision Tree machine learning algorithm was applied to generate a fire susceptibility index (a measure of the potential for a given area or region to experience wildfires) using a dataset of conditioning factors, namely: altitude, aspect, rainfall, distance from rivers, distance from roads, forest type, geology, koala presence and future dietary sources, land use-land cover (LULC), normalized difference vegetation index (NDVI), slope, soil, temperature, and wind speed. Results: We found a general increase in susceptibility of Australian vegetation to bushfires overall. The simulation for current conditions indicated that 39.56% of total koala habitat has a fire susceptibility rating of "very high"or "high", increasing to 44.61% by 2070. Main conclusions: Wildfires will increasingly impact koala populations in the future. If this iconic and vulnerable marsupial is to be protected, conservation strategies need to be adapted to deal with this threat. It is crucial to strike a balance between ensuring that koala habitats and populations are not completely destroyed by fire while also allowing for forest rejuvenation and regeneration through periodic burns.& COPY; 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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页数:12
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