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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引用次数: 0
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.
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.