Abstract
Background: Several studies have suggested the possibility of obtaining specific respiratory benefits by experiencing forests and other natural resources. Despite this, forests have never been considered according to such potential. This study aims to compare municipalities by considering the absence/presence of tree species generating ‘above threshold’ potential respiratory benefits. Methods: The autonomous Region of Friuli Venezia Giulia in Italy has been assumed as a research area. The natural resource based view (NRBV), postulating the strategic role played by natural resources in achieving both above-average (thus ‘valuable’) and ‘concentrated’ (thus ‘rare’ among competitors) performance, has been adopted. The literature reviews dealing with potential respiratory benefits of biogenic organic compounds (BVOCs) emitted by trees, published within the ‘forest therapy’ research field, have been adopted. Three analysis models rating tree species by their potential respiratory benefits in ‘holistic-general’ (P1), ‘particular’ (P2), and ‘dynamic” terms (P3) have been outlined. The resulting overall potentials of tree species have been assessed by adopting the well-rooted Hollerith distance (HD) model. Tree species have been rated “1” when they satisfy one or more of 58 potential respiratory benefits. Municipalities have been ranked by considering the surface area covered by forest types whose dominant tree species achieve above-average potential respiratory benefits. QGIS software has been adopted to geographically reference the results obtained. Results: (P1) Valuable municipalities include those covered by both coniferous and deciduous forests; (P2–3) Municipalities achieving the highest potential respiratory benefits, in both particular and dynamic terms, have been mapped. Discussion: Forest-based initiatives that are running in the preselected municipalities can be both further improved and diversified in a targeted way. Conclusions: Despite some limitations mostly embedded in the concept of ‘model’, this study allows scholars to reduce uncertainties when locating municipalities in which to conduct local-scale experiments.