Response curves for key variables influencing wildfire occurrence in summer (top) and autumn (bottom).

<p>The graphs illustrate the probability of wildfire occurrence (y-axis) in relation to the values of significant variables (x-axis). The three most impactful variables identified are Human Modification of Terrestrial Systems (HMTS), Soil Organic Carbon (SOC), and Land Use/Land Cover (LULC) fo...

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Bibliographic Details
Main Author:	Peyman Karami (5909264) (author)
Other Authors:	Sajad Tavakoli (21001440) (author)
Published:	2025
Subjects:	Ecology Sociology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified vegetation types associated regions except deserts predict seasonal effects significant portion located experienced significant changes wind exposure index jackknife analysis indicated parametric spatiotemporal trends div >< p test identified areas successfully identified high hyrcanian mixed forests 2 </ sup predict fire risk iran </ p risk wildfire areas significant trends hyrcanian forests wildfire risk risk zones prediction analysis kappa index assess trends wildfire regimes wildfire occurrence wildfire activity vulnerable areas agricultural areas wei ). terrestrial systems study aims spatial variations spatial extent results showed recent years prone zones per km minimal overlap maxent model land uses land use land cover key component kernel function human modification human activities high across fire regimes fire density environmental variables driest month crucial indicators confidence level calculated using available fuel also classified 85 km 56 km
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Response curves for key variables influencing wildfire occurrence in summer (top) and autumn (bottom).

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