Forest ownership fragmentation represents a major constraint to sustainable forest management in many European countries, particularly in Italy, where private forests are often divided into small and spatially dispersed holdings. This study evaluates the potential of cadastral data to support forest-owner aggregation through graph-based spatial network analysis implemented within the Forest Sharing^® platform. Its novelty lies in the operational integration of voluntary cadastral parcel data with a comparative network framework that quantifies how parcel representation and spatial thresholds alter the identification of candidate multi-owner management units. The analysis included 29,549 cadastral forest parcels voluntarily registered by 910 private forest owners across Italy. Parcels were treated as network nodes, and three spatial relationship models were compared: strict topological adjacency, minimum polygon-to-polygon distance, and distance between internal representative points. Distance-based networks were evaluated at 50-m increments from 50 to 1000 m, while cluster eligibility was defined by a minimum area of 30 ha and at least two owners. Strict adjacency identified six eligible clusters covering 465.7 ha. The minimum polygon-distance method identified 31 eligible clusters and 7297.2 ha at 100 m, increasing to 44 clusters and 14,204.8 ha at 1000 m. The point-on-surface method was substantially more conservative at short thresholds but progressively converged with the polygon method; edge recall increased from 0.479 at 100 m to 0.916 at 1000 m, while precision remained equal to 1.0. Median ownership complexity remained limited to two or three owners per eligible cluster, although the largest components included substantially more owners at high thresholds. The results demonstrate that parcel geometry and threshold selection materially influence estimated aggregation opportunities and support the use of polygon-based proximity combined with sensitivity analysis as a transparent screening framework for collective forest management.

Forest ownership fragmentation represents a major constraint to sustainable forest management in many European countries, particularly in Italy, where private forests are often divided into small and spatially dispersed holdings. This study evaluates the potential of cadastral data to support forest owner aggregation through a graph-based spatial network analysis implemented within the Forest Sharing® platform. The analysis was conducted on 29,549 cadastral forest parcels voluntarily registered by 910 private forest owners across Italy. Parcels were represented as nodes in a spatial network and connected using four aggregation-distance thresholds (100, 250, 500, and 1000 m). Connected components were interpreted as potential forest management clusters. Only clusters including at least 30 ha of forest area and a minimum of two owners were retained. The proposed methodology successfully identified aggregable forest management units under all scenarios. Increasing aggregation distances substantially increased both the number of eligible clusters and the total forest area available for collective management. The number of clusters increased from 5 at the 100 m threshold to 48 at 500 m, while the aggregable forest area increased from approximately 700 ha to more than 12,000 ha at the 1000 m threshold. Most clusters involve two and five owners, indicating that substantial aggregation opportunities can be achieved without excessive ownership complexity. The study highlights the potential of cadastral information and spatial network analysis to support forest owner associations, collective management initiatives, and forest policy measures aimed at overcoming ownership fragmentation.

Continuous cover forest management (CCFM) plays a key role in sustaining forest multifunctionality by reconciling timber production with long-term carbon sequestration, biodiversity conservation, and landscape continuity. It represents a cornerstone of the closer-to-nature approach promoted by the European Forest Strategy for 2030 and related EU Guidelines, providing science-based solutions to enhance forest resilience to climate change while supporting bioeconomy and rural development. As forests are increasingly expected to contribute to climate change mitigation, they simultaneously face growing pressures from climatic extremes and environmental stressors, making the evaluation of management practices under changing climate conditions a critical research priority.In this study, carried out in the context of the EU project SMURF, we analyze the long-term application of group selection cutting within irregular black pine (Pinus nigra J.F. Arnold) stands of the Sila Plateau (Calabria, Southern Italy), a traditional silvicultural system widely adopted by private forest owners. Using ecosystem service modelling approaches, we assess variations in gross primary productivity (GPP) and net primary productivity (NPP) in relation to gap size, regeneration patterns, and climate parameters, with the aim of evaluating the effectiveness of this CCFM practice in supporting climate change mitigation.Results highlight how gap size variability allows the pursuit of multiple management objectives, ranging from the conservation of pure black pine stands—of high value for historical landscapes and habitat preservation—to the promotion of broadleaved species recruitment, which may enhance ecosystem resilience and wildfire resistance under future climate scenarios. Regeneration dynamics within gaps are analyzed to define operational silvicultural parameters that support successful natural regeneration while maintaining stable carbon sequestration rates. Overall, the study demonstrates that group selection cutting can effectively balance climate mitigation potential with economic income, contributing to science-based forest management strategies, forest resilience and adaptive capacity in Mediterranean mountain environments.