In macroecology, shifting from coarse- to local-scale explanatory factors is crucial for understanding how global change impacts functional diversity (FD). Plants possess diverse traits allowing them to differentially respond across a spectrum of environmental conditions. We aim to assess how macro- to microclimate, stand-scale measured soil properties, forest structure, and management type, influence forest understorey FD at the macroecological scale. Our study covers Italian forests, using thirteen predictors categorized into climate, soil, forest structure, and management. We analyzed five traits (i.e., specific leaf area, plant size, seed mass, belowground bud bank size, and clonal lateral spread) capturing independent functional dimensions to calculate the standardized effect size of functional diversity (SES-FD) for all traits (multi-trait) and for single traits. Multiple regression models were applied to assess the effect of predictors on SES-FD. We revealed that climate, soil, and forest structure significantly drive SES-FD of specific leaf area, plant size, seed mass, and bud bank. Forest management had a limited effect. However, differences emerged between herbaceous and woody growth forms of the understorey layer, with herbaceous species mainly responding to climate and soil features, while woody species were mainly affected by forest structure. Future warmer and more seasonal climate could reduce the diversity of resource economics, plant size, and persistence strategies of the forest understorey. Soil eutrophication and acidification may impact the diversity of regeneration strategies; canopy closure affects the diversity of above- and belowground traits, with a larger effect on woody species. Multifunctional approaches are vital to disentangle the effect of global changes on functional diversity since independent functional specialization axes are modulated by different drivers. © 2024 The Authors

Knowing the extent and frequency of forest cuttings over large areas is crucial for forest inventories and monitoring. Remote sensing has amply proved its ability to detect land cover changes, particularly in forested areas. Among various strategies, those focusing on mapping using classification approaches of remotely sensed time series are the most frequently used. The main limit of such approaches stems from the difficulty in perfectly and unambiguously classifying each pixel, especially over wide areas. The same procedure is of course simpler if performed over a single pixel. An automated method for identifying forest cuttings over a predefined network of sampling points (IUTI) using multitemporal Sentinel 2 imagery is described. The method employs normalized difference vegetation index (NDVI) growth trajectories to identify the presence of disturbances caused by forest cuttings using a large set of points (i.e., 1580 "forest" points). We applied the method using a total of 51 S2 images extracted from the Google Earth Engine over two years (2016 and 2017) in an area of about 70 km ² in Tuscany, central Italy. © 2019 by the authors.

Context: Pulsed food resources may strongly affect the population dynamics of several consumer species, with consequences on the ecosystem. One of the most common pulsed resources is forest mast seeding. Aims: We analysed mast seeding in deciduous forests in a mountainous area of northern Apennines and its effect on population dynamics of wild boar (Sus scrofa L.). Methods: We performed a quantitative, 20-year analysis on annual seed production in Turkey oak (Quercus cerris L.), beech (Fagus sylvatica L.) and chestnut (Castanea sativa Mill.) forest stands using litter traps. The wild boar population density was estimated by means of drive censuses and hunting bag records. The role of other biotic (density of predators) and abiotic (climate) factors potentially affecting wild boar mortality was also investigated. Results: Turkey oak and chestnut showed high levels of seed production, whereas lower levels were found in beech. The pulsed resources of chestnut and Turkey oak positively affected piglet density. Analyses also highlighted the influence of snow cover and wolves on wild boar population dynamics. Conclusion: Wild boar can be considered a pulse rate species, the management of which can be improved by annual monitoring of seed production. © 2013 INRA and Springer-Verlag France.