Disturbances such as wildfires are an integral part of forest ecosystems, but climate change is increasing their extent, frequency, intensity and severity, compromising forest ecosystem services (ES) that are fundamental… Click to show full abstract
Disturbances such as wildfires are an integral part of forest ecosystems, but climate change is increasing their extent, frequency, intensity and severity, compromising forest ecosystem services (ES) that are fundamental to human well-being. Thus, evaluating the risk of losing ecosystem services due to wildfires is essential for anticipating and adapting to future conditions. Here, we analyze the spatial patterns of the risk of losing key forest ES and biodiversity (that is, carbon sink, bird richness, hydrological control and erosion control) due to wildfires in Catalonia (NE Spain), taking into account exposed values, hazard magnitude, susceptibility and lack of adaptive capacity. We also determine the effect of climate and different forest functional types on the risk of losing ES under average and extreme hazard conditions (defined as median and 90th percentile values of the Fire Weather Index, respectively), as well as on the increase in risk. Our results show that hazard magnitude is the most important component defining risk under average conditions. Under extreme conditions, exposed values (carbon sink capacity and erosion control) emerged as the most important components of risk. Climate was the main driver of ES at risk under average conditions, but the high vulnerability of non-Mediterranean conifer forests with a low adaptive capacity gained importance under extreme conditions. The increase in risk between average and extreme conditions was driven by precipitation, as the highest increases in risk were found in relatively wet forests with low average risk at present. These results have direct implications on the future risk of losing ES to wildfires in Mediterranean forests but also in other regions, and they could contribute to future policies by anticipating conditions associated with particularly high risk that can be used to guide efficient forest management.
               
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