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.

A spatially explicit approach for stand-scale economic valuation of current and future potential of cork forests with respect to ecosystem production is developed and presented. The approach, which relies in large part on the mensura-tion of stand top height and number of trees as main drivers, has been tested on the pure cork forests of Sardinia (Italy). The test was conducted to assess the effects of alternative silvicultural options on cork and fodder production, carbon sequestration, and water yield. Under current conditions, the surveyed pure cork oak forest stands in Sardinia are characterized, on average, by an annual economic production of 93 euro ha^-1 yr^-1 as concerns cork, 37 euro ha^-1 yr^-1 as concerns carbon sequestration and 261 euro ha^-1 yr^-1 as concerns water yield. The value of cork production on an 11-year cycle equals 1023 euro ha^-1 on average. The total economic production values among the tested silvicultural alternatives have proven to be characterized by relatively small differences, due to the trade-offs among the considered goods and services. Therefore, at least under conditions similar to those surveyed, managers may safely rely on different stand density options, without any relevant detrimental effect on total economic production. The tested spatial visualization of the economic values of goods and services production can be useful in supporting forest management planning, e.g., to identify priority areas in order to maximize ecosystem production for local communities. The approach proposed here and tested to this end proves to be readily applicable to other cork contexts with similar characteristics under Mediterranean conditions. © SISEF.