Tree-ring and remote sensing analyses uncover the role played by elevation on European beech sensitivity to late spring frost.

Extreme climate events such as late spring frosts (LSFs) negatively affect productivity and tree growth in temperate beech forests. However, detailed information on how these forests recover after such events are still missing. We investigated how LSFs affected forest cover and radial growth in European beech (Fagus sylvatica L.) populations located at different elevations at four sites in the Italian Apennines, where LSFs have been recorded. We combined tree-ring and remote-sensing data to analyse the sensitivity and recovery capacity of beech populations to LSFs. Using daily temperature records, we reconstructed LSF events and assessed legacy effects on growth. We also evaluated the role played by elevation and stand structure as modulators of LSFs impacts. Finally, using satellite images we computed Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and LAI (Leaf Area Index) to evaluate the post-LSF canopy recovery. The growth reduction in LSF-affected trees ranged from 36 % to 84 %. We detected a negative impact of LSF on growth only during the LSF year, with growth recovery occurring within 1-2 years after the event. LSF-affected stands featured low vegetation indices until late June, i.e. on average 75 days after the frost events. We did not find a clear relationship between beech forest elevation and occurrence of LSFs defoliations. Our results indicate a high recovery capacity of common beech and no legacy effects of LSFs.

Combining Participatory Mapping and Geospatial Analysis Techniques to Assess Wildfire Risk in Rural North Vietnam.

Participatory mapping (PM) is a valuable research tool for assessing fire risk, especially in regions where data are difficult to collect or inconsistent; in such areas, the integration between crowdsourced data and geospatial techniques plays a fundamental role in gathering more consistent and reliable information. This study combines a participatory (community-based) mapping approach with geospatial techniques to assess fire risk in Van Chan district, northern Vietnam, an area where the economy relies mainly on forestry activities. Local stakeholders designed a map of wildfires, which was modelled as a function of a set of physical and socio-economic variables. A fire-probability map of the district was obtained and compared with MODIS data (2000-2020). The results suggest that higher fire probability occurs in areas with lower human pressure, and they provide information on related socio-economic drivers that affect this phenomenon. This study highlights the importance of combining participatory approaches and geospatial techniques to assess fire dynamics and prevent wildfires in terms of understanding and predicting the risks. The involvement of local communities is fundamental to this innovative participatory approach with regard to better supporting decision-making and prevention actions and to developing fire control management guidelines.