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Novel quantitative indicators to characterize the protective effect of mountain forests against rockfall
Affiliation:1. Université Grenoble Alpes, Irstea, UR EMGR, 2 rue de la Papeterie-BP 76, F-38402 St-Martin-d’Hères, France;2. Université Grenoble Alpes, F-38402 Grenoble, France;3. Irstea, UR EMAX, F-13185 Aix en Provence, France;1. School of Industrial Engineering and Management, KTH Royal Institute of Technology, Brinellvägen 83, SE-10044 Stockholm, Sweden;2. Swedish Forestry Research Institute, Skogforsk, Uppsala Science Park, S-751 83 Uppsala, Sweden;1. Natural Resources Institute Finland, Green Technology, Silmäjärventie 2, FI69100, Kannus, Finland;2. Swedish University of Agricultural Sciences, Department of Forest Biomaterials and Technology, Skogsmarksgränd, SE-901 83 Umeå, Sweden;1. Faculty of Applied Ecology and Agricultural Sciences, Hedmark University College, Campus Evenstad, NO-2480 Koppang, Norway;2. Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, Pb. 5003, NO-1432 Ås, Norway;3. CNR IVALSA, Via Madonna del Piano 10, I-50019 Sesto Fiorentino, Italy;1. Consiglio per La Ricerca in Agricoltura e L''analisi Dell''economia Agraria (CREA) - Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via Della Pascolare 16, 00015, Monterotondo (Rome), Italy;2. Department of AGRARIA, Mediterranean University of Reggio Calabria, Feo di Vito, 89122 Reggio Calabria, Italy;3. Effetreseizero Srl, Spinoff CREA, Via Dei Solteri 37/1, 38121 Trento, Italy
Abstract:Natural hazards are frequent in mountain areas where they regularly cause casualties and damages to human infrastructures. Mountain forests contribute in mitigating these hazards, in particular rockfalls. Assessing the protective effect of a forest against rockfall is a difficult task for both forest managers and rockfall experts. Accurate and simple tools are therefore required to efficiently evaluate the level of protection that results from the presence of forest.This study defines three novel indicators to quantify the protective effect of forests against rockfalls, regarding (1) the reduction of the frequency of rockfalls, (2) the reduction of their maximum intensity, and (3) the combination of the reduction of the frequency and the energy of the rocks. The first two indicators are relevant for rockfall experts whereas the third is mostly interesting for foresters as it summarizes the protective effect of forest. The Rockyfor3D model was adapted and used to simulate rockfalls propagation on 3886 different forest stands located in all the French Alps. The results of the simulations were used to calculate the three indicators for each forest stand. Finally, the relations between the forest structures and compositions and the indicators values were investigated.Our principal result shows that only three forest characteristics are required to accurately predict the indicators and evaluate the protective level of a forest against rockfall. The two first variables correspond to the basal area and the mean diameter at breast height (DBH) of the forest stand which are two parameters commonly used by forest managers. The third characteristic is the length of forest in the maximum slope direction which can be computed with a geographic information system (GIS). The method proposed in this study is easily reproducible and is suitable to evaluate the protective effect of European mountain forests at different scales. At local scale, the proposed indicators can enrich rockfall studies in which forests are usually set aside to simplify the evaluation. Moreover, the indicators may find direct applications with foresters by allowing them to identify the protective level of their forest and consequently to adapt their management. Finally, the indicators are convenient to perform spatial analysis and produce maps of the protective effect of mountain forests that could find many applications in land settlement or evaluation of ecosystem services.
Keywords:Indicators  Protection forest  Rockfall  Ecosystem services  3D simulation model  Mountain forest
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