Global Distribution of Forest Fires and Socioeconomic-Environmental Consequences: A Comprehensive Review with Emphasis on Climate-Human Feedbacks
Kavita Budania
*
Department of Geography, MGM PG College, Sambhal Affiliated to Mahatma Jyotiba Phule Rohilkhand University, Bareilly, Uttar Pradesh, 253006, India.
Yogendra Singh
Department of Geography, MGM PG College, Sambhal Affiliated to Mahatma Jyotiba Phule Rohilkhand University, Bareilly, Uttar Pradesh, 253006, India.
Manish Naja
Aryabhatta Research Institute of Observational Sciences, Manora peak, Beluwakhan, Uttarakhand 263002, India.
Sakshi Gangwar
Department of Geography, MGM PG College, Sambhal Affiliated to Mahatma Jyotiba Phule Rohilkhand University, Bareilly, Uttar Pradesh, 253006, India.
Anuj Nehra
Department of Physics, Vardhaman College, Bijnor affiliated to Mahatma Jyotiba Phule Rohilkhand University, Bareilly, Uttar Pradesh, 253006, India.
Sonali Priyadarshini
School of Health Sciences and Technology, UPES, Bidholi Campus, Dehradun, Uttarakhand, India.
*Author to whom correspondence should be addressed.
Abstract
In recent years, wildfires have shifted from a seasonal ecological disturbance to a persistent atmospheric crisis. Fire catalysts vary from agricultural encroachment in Brazil and Bolivia to stratospheric pyroconvection in Australia and conflict-induced ignitions in Ukraine, and from forest fragmentation in Amazon rainforests to Australia’s ‘Black Summer’ fires. Together, these events have a cumulative impact on the systemic destabilisation of the global carbon cycle. Future projections suggest a rapid shift of critical carbon sinks into net atmospheric sources. Projections for the late twenty-first century indicate that Forest Fire Danger Index (FFDI) and Fire Weather Index (FWI) values will continue to rise, extending burn windows into previously protected high-altitude refugia and carbon-dense peatlands. To mitigate this escalating threat, global management must move beyond reactive suppression towards an integrated framework that bridges the "science-management gap". This requires the implementation of high-resolution AI predictive models alongside proactive policies such as peatland re-wetting, adaptive silviculture and socioeconomic protection for vulnerable rural populations. Ultimately, ensuring resilience in an increasingly flammable world requires a transboundary approach that treats wildfire emissions as global, rather than only national, incidents. In this review, the authors discuss various risk factors associated with forest fires in different regions of the Earth, as well as their assessment and prediction using modern AI-ML technologies to reduce losses from such disasters.
Keywords: Forest fire, wildfire risk, climate change, climate-human feedbacks, burned area, fire weather indices, remote sensing, machine learning, aerosol emissions, socioeconomic impacts, adaptive management, ecosystem resilience