Wildfire Risk Assessment in Ambato, Ecuador: Drought Impacts, Fuel Dynamics, and Wildland–Urban Interface Vulnerability DOI Creative Commons

Andrés Hidalgo,

Luis Contreras,

Verónica Livier Díaz Nuñez

et al.

Fire, Journal Year: 2025, Volume and Issue: 8(4), P. 130 - 130

Published: March 27, 2025

Wildfires represent an increasing threat to ecosystems and communities, driven by climate change, fuel dynamics, human activities. In Ambato, Ecuador, a city in the Andean highlands, these risks are exacerbated prolonged droughts, vegetation dryness, urban expansion into fire-prone areas within Wildland–Urban Interface (WUI). This study integrates climatic, ecological, socio-economic data from 2017 2023 assess wildfire risks, employing advanced geospatial tools, thematic mapping, machine learning models, including Multinomial Logistic Regression (MLR), Random Forest, XGBoost. By segmenting area 1 km2 grid cells, microscale risk variations were captured, enabling classification five categories: ‘Very Low’, ‘Low’, ‘Moderate’, ‘High’, High’. Results indicate that temperature anomalies, reduced moisture, anthropogenic factors such as waste burning unregulated land-use changes significantly increase fire susceptibility. Predictive models achieved accuracies of 76.04% 77.6% (Random Forest), 76.5% (XGBoost), effectively identifying high-risk zones. The highest-risk found Izamba, Pasa, San Fernando, where over 884.9 ha burned between 2023. year 2020 recorded most severe season (1500 burned), coinciding with extended droughts COVID-19 lockdowns. Findings emphasize urgent need for enhanced regulations, improved firefighting infrastructure, community-driven prevention strategies. research provides replicable framework assessment, applicable other regions beyond. integrating data-driven methodologies policy recommendations, this contributes evidence-based mitigation resilience planning climate-sensitive environments.

Language: Английский

“No One Is Safe”: Agricultural Burnings, Wildfires and Risk Perception in Two Agropastoral Communities in the Puna of Cusco, Peru DOI Creative Commons
Rossi Taboada Hermoza, Alejandra G. Martínez

Fire, Journal Year: 2025, Volume and Issue: 8(2), P. 60 - 60

Published: Feb. 1, 2025

By developing a conceptual framework that integrates the use of fire in agricultural activities, occurrence wildfires, and perception wildfire risk, this article examines interplay among these three elements within both wet dry Puna grasslands. The analysis focuses on two peasant agropastoral communities, Vilcabamba Apachaco, located Cusco region—an area with highest incidence wildfires Peru. This study highlights sociocultural significance persistence burnings communities necessity considering changes activity, mutual aid systems, communal institutions—particularly regarding land ownership—to understand factors contributing to occurrence. Furthermore, it reveals widespread recognition risk community members, who are acutely aware likelihood potential severity events, while governmental policies aimed at addressing hazard predominantly focus raising awareness enforcing bans burning, limited consideration complex dynamics.

Language: Английский

Citations

0
Rethinking wildfire management policy: Suggestions from firefighters who experienced the 2017 extreme wildfires in Portugal DOI
Vittorio Leone, Mario Elia, Raffaella Lovreglio

et al.

Forest Policy and Economics, Journal Year: 2025, Volume and Issue: 173, P. 103453 - 103453

Published: March 3, 2025

Language: Английский

Citations

0
Wildfire Risk Assessment in Ambato, Ecuador: Drought Impacts, Fuel Dynamics, and Wildland–Urban Interface Vulnerability DOI Creative Commons

Andrés Hidalgo,

Luis Contreras,

Verónica Livier Díaz Nuñez

et al.

Fire, Journal Year: 2025, Volume and Issue: 8(4), P. 130 - 130

Published: March 27, 2025

Wildfires represent an increasing threat to ecosystems and communities, driven by climate change, fuel dynamics, human activities. In Ambato, Ecuador, a city in the Andean highlands, these risks are exacerbated prolonged droughts, vegetation dryness, urban expansion into fire-prone areas within Wildland–Urban Interface (WUI). This study integrates climatic, ecological, socio-economic data from 2017 2023 assess wildfire risks, employing advanced geospatial tools, thematic mapping, machine learning models, including Multinomial Logistic Regression (MLR), Random Forest, XGBoost. By segmenting area 1 km2 grid cells, microscale risk variations were captured, enabling classification five categories: ‘Very Low’, ‘Low’, ‘Moderate’, ‘High’, High’. Results indicate that temperature anomalies, reduced moisture, anthropogenic factors such as waste burning unregulated land-use changes significantly increase fire susceptibility. Predictive models achieved accuracies of 76.04% 77.6% (Random Forest), 76.5% (XGBoost), effectively identifying high-risk zones. The highest-risk found Izamba, Pasa, San Fernando, where over 884.9 ha burned between 2023. year 2020 recorded most severe season (1500 burned), coinciding with extended droughts COVID-19 lockdowns. Findings emphasize urgent need for enhanced regulations, improved firefighting infrastructure, community-driven prevention strategies. research provides replicable framework assessment, applicable other regions beyond. integrating data-driven methodologies policy recommendations, this contributes evidence-based mitigation resilience planning climate-sensitive environments.

Language: Английский

Citations

0