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

IF 6.7 2区 环境科学与生态学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Environmental Technology & Innovation Pub Date : 2023-08-14 DOI:10.1016/j.eti.2023.103331
Farzin Shabani , Mahyat Shafapourtehrany , Mohsen Ahmadi , Bahareh Kalantar , Haluk Özener , Kieran Clancy , Atefeh Esmaeili , Ricardo Siqueira da Silva , Linda J. Beaumont , John Llewelyn , Simon Jones , Alessandro Ossola
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Abstract

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.

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火焰中的栖息地:气候变化将如何影响考拉森林的火灾风险
目的:生成目前和2070年的火灾易感性地图,以确定野火现在和未来气候变化下对考拉构成的威胁。地点:澳大利亚。时间段:现在和2070年。研究的主要分类群:考拉浏览的60种主要树种。方法:应用决策树机器学习算法,使用条件因素数据集生成火灾易感性指数(衡量给定地区或地区发生野火的可能性),即:海拔、坡向、降雨量、与河流的距离、与道路的距离、森林类型、地质、考拉的存在和未来的饮食来源、土地利用土地覆盖(LULC),归一化差异植被指数(NDVI)、坡度、土壤、温度和风速。结果:我们发现,总体而言,澳大利亚植被对山火的易感性普遍增加。对当前条件的模拟表明,39.56%的考拉栖息地的火灾易感性等级为“非常高”或“高”,到2070年增加到44.61%。主要结论:未来野火将对考拉种群产生越来越大的影响。如果要保护这种标志性的、脆弱的有袋动物,就需要调整保护策略来应对这种威胁。至关重要的是,要在确保考拉栖息地和种群不会被大火完全摧毁的同时,通过定期焚烧实现森林复兴和再生。
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来源期刊
Environmental Technology & Innovation
Environmental Technology & Innovation Environmental Science-General Environmental Science
CiteScore
14.00
自引率
4.20%
发文量
435
审稿时长
74 days
期刊介绍: Environmental Technology & Innovation adopts a challenge-oriented approach to solutions by integrating natural sciences to promote a sustainable future. The journal aims to foster the creation and development of innovative products, technologies, and ideas that enhance the environment, with impacts across soil, air, water, and food in rural and urban areas. As a platform for disseminating scientific evidence for environmental protection and sustainable development, the journal emphasizes fundamental science, methodologies, tools, techniques, and policy considerations. It emphasizes the importance of science and technology in environmental benefits, including smarter, cleaner technologies for environmental protection, more efficient resource processing methods, and the evidence supporting their effectiveness.
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