This paper presents a spatial-based decision support system (DSS) to assist public and private forest managers in the analysis of potential feasibility in payments for forest ecosystem services (PES) for the prevention of soil erosion. The model quantifies the maximum willingness to pay (WTP) of managers of a reservoir to prevent soil loss. The minimum willingness to accept (WTA) of forest owners for the activation of a private market is also computed. The comparison of WTP and WTA identifies the forest area where PES are ideally feasible with additional potential for compensation to enable the schemes. The DSS highlights forest idiosyncrasies as well as local socio-economic and geomorphological characteristics influencing PES suitability at a geographic level. The potential applications and future improvements of the model are also discussed.

Prevention of erosion in mountain basins: A spatial-based tool to support payments for forest ecosystem services / Sacchelli S.; Borghi C.; Grilli G.. - In: JOURNAL OF FOREST SCIENCE. - ISSN 1212-4834. - ELETTRONICO. - 67:(2021), pp. 258-271. [10.17221/5/2021-JFS]

Prevention of erosion in mountain basins: A spatial-based tool to support payments for forest ecosystem services

Sacchelli S.
;
Borghi C.;Grilli G.
2021

Abstract

This paper presents a spatial-based decision support system (DSS) to assist public and private forest managers in the analysis of potential feasibility in payments for forest ecosystem services (PES) for the prevention of soil erosion. The model quantifies the maximum willingness to pay (WTP) of managers of a reservoir to prevent soil loss. The minimum willingness to accept (WTA) of forest owners for the activation of a private market is also computed. The comparison of WTP and WTA identifies the forest area where PES are ideally feasible with additional potential for compensation to enable the schemes. The DSS highlights forest idiosyncrasies as well as local socio-economic and geomorphological characteristics influencing PES suitability at a geographic level. The potential applications and future improvements of the model are also discussed.
2021
67
258
271
Sacchelli S.; Borghi C.; Grilli G.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1239342
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