Wildfire risk in Southern Europe is intensifying due to the combined effect of climatic, ecological, and socio-economic pressures, requiring improved decision-support tools for preventive landscape management. This study develops a scalable and transferable spatial multi-criteria decision analysis (MCDA) framework to support the prioritization of wildfire prevention areas by integrating harmonized pan-European geospatial datasets with expert-informed decision modelling. The methodology is applied to the Iberian Peninsula as a case study and combines a participatory Analytic Hierarchy Process (AHP) to derive weights for a structured set of criteria related to fuels, fire behavior, and values at risk, together with Multi-Attribute Utility Theory (MAUT) to model utility functions for each sub-criterion. To operationalize the workflow, we developed an open-source QGIS plugin (“Pan Europeo”) and a complementary Web-GIS platform, providing end-users with access, visualization, and analysis of harmonized datasets. The tools enable users to conduct a MCDA at a 100 × 100 m spatial resolution, producing continuous prioritization maps that identify areas of strategic importance for fuel management. The results of the participatory exercise conducted show that 20,804 hectares across the Iberian Peninsula have priority values above 0.8 (on a 0–1 scale, where 1 indicates maximum priority). Beyond the case study, the proposed workflow is fully transferable to other regions, enabling consistent application across scales. Our findings demonstrate how harmonized geospatial infrastructure and open-source decision-support tools can bridge science and decision-making, supporting more informed wildfire prevention and landscape resilience planning across Europe.
Large tree-cavities (LTC) are conspicuous structures with specific ecological functions in large trees. We summarize the distribution, dynamics, ecological roles and conservation issues of LTC based on nearly 370 sources where these could be distinguished (based on entrances ca. 9 cm wide or larger). Large live broadleaved trees provide most LTC; live conifers and snags have importance in certain ecosystems. The resulting landscape distributions differ from those of smaller cavities by (i) an order of magnitude lower densities in forests (> 10 LTC ha–1 qualifies as a conservation hotspot) and higher sensitivity to management; (ii) relatively frequent occurrence in semi-open natural, rural or urban landscapes, if certain trees are retained until senescence. The slow wood decay processes, crucial for LTC development, introduce mechanical challenges that are best met when tree remains alive. Fast-growing broadleaved trees can form LTC at an earlier age, but slower-growing species produce persistent cavities. Relatively few vertebrate species are obligate LTC users, but they are more often threatened and often have symbolic meaning for people. Especially, those species less capable of defending cavities against predators tend to use (and compete for) only a subset of available cavities. For invertebrates, LTC form micro-ecosystems that host specific assemblages. Maintaining LTC as functional parts of human-dominated ecosystems requires unprecedented planning horizons and distinct approaches to tree retention and recruitment depending on the landscape type and species. In terms of landscape planning, both ecological and socio-economic pre-conditions of LTC development and their ecosystem functioning beyond habitat provision are insufficiently studied.
Establishing initial geometric correspondences between terrestrial laser scanning (TLS) and unmanned aerial vehicle laser scanning (ULS) forest point clouds is difficult under cross-platform observations. Fine registration is vulnerable to local non-rigid canopy deformation caused by canopy disturbance and platform-dependent observation differences. This study proposes a coarse-to-fine automatic registration framework that integrates hybrid semantic triangle matching and vertical structure weighting. Tree-top points and canopy-gap centroids are first extracted from the canopy height model (CHM). They are used to construct hybrid semantic triangle descriptors. The initial transformation is then estimated using random sample consensus (RANSAC) and singular value decomposition (SVD) for coarse registration. For fine registration, a normalized-height-based vertical structure weighting model increases the constraints from stable structures, including stems and the ground. It reduces the effects of canopy disturbance and cross-platform observational differences on iterative closest point optimization. Experiments were conducted in six Shangri-La plots with different slopes and canopy closures. The mean point-to-plane RMSE after coarse registration was 0.272 m, 27.8
While the therapeutic potential of nature exposure is well-documented, the role of forest landscape types in mediating human well-being remains underexplored. This study investigated the physio-psychological restorative effects on university students among videos of three types of forests (coniferous forest, broad-leaved forest, mixed forest), urban environment and blank control. The 177 participants underwent stress induction, then watched a 6-min video or sat still. The physiological state was assessed by heart rate (HR) and electrodermal activity (EDA), while the mental state was reflected by State-Trait Anxiety Inventory (STAI-S) and Positive Affect and Negative Affect Schedule (PANAS). The results showed that watching forest and urban video significantly reduced HR, EDA, STAI-S and negative affect (NA), while boosted the positive affect (PA). The blank control improved psychological measurements reflected in the reduction of STAI-S as well as NA and the increase of PA, but no significant effects in physiological measurements. Videos of three types of forests had better restorative effects than urban environment and blank control group both in physiological and psychological aspects, with the coniferous forest video being most effective. The study confirmed the restorative benefits of forest videos, with coniferous forest showing the strongest effects, and suggested their potential for nature-averse or time-limited individuals.
Understanding the eco-evolutionary drivers of leaf nutrient concentrations helps explain the distribution patterns of woody plants along elevation gradients in subtropical mountain forests. We measured climatic and soil properties, as well as leaf concentrations of six essential nutrients (C, N, P, K, Ca, and Mg) in woody species representing distinct plant functional groups defined by their geographic origin and leaf habit, along a subtropical mountain elevational gradient. Leaf nutrient concentrations were differentiated among plant functional groups and were phylogenetically conserved. However, evolutionary model comparisons suggest that leaf nutrient evolution along elevations was best explained by stabilizing selection towards multiple optima corresponding to different plant functional groups. Mean annual temperature (MAT) emerged as the primary environmental filter, with leaf C, N, and P concentrations showing consistent relationships with MAT across all groups, challenging a core prediction of the leaf economic spectrum theory by demonstrating convergent responses to temperature among divergent groups. In contrast, tropical-affiliated groups, particularly evergreens, displayed heightened sensitivity of leaf K, Ca, and Mg concentrations to precipitation and soil nutrient availability. Our findings thus support a novel theoretical contribution by demonstrating that leaf nutrient-based phylogenetic constraint, plant functional group differentiation, and environmental filtering operate as interdependent rather than alternative mechanisms shaping woody plant distribution along elevational gradients. We recommend that future forest management in subtropical mountain ecosystems should integrate plant functional group-specific leaf nutrient profiles into restoration and monitoring frameworks to preserve functional diversity and enhance forest resilience in the face of ongoing environmental change.
