Abstract
Forests are submitted to many hazards, with wind storms inducing the highest yield loss in European forests. Moreover, these wind losses are forecast to be multiplied by a factor 2 to 4 through the combination of forest aging and climatic changes. Additionally global changes have renewed and complicate the social expectations towards the forests and the estimation of their values. Forests are globally expected to i) produce more energy and materials, ii) stock more carbon,, iii) preserve the biodiversity and iv) become attractive recreational areas. The predictive management of a forest by its owner means programming actions over space and time for a typical duration of 15 to 20 years (harvest, renewal, conversion). It is thus crucial to assess how management actions may affect the risk of wind hazards while achieving the goals of the forest owner. The aim of the FOR-WIND project is to develop a Decision Support System (DSS) based on the computer simulation of virtual forest growth and wind hazards at the decade time scale and for whole forest management units. A sample representing the major French forest systems will be considered, ranging from pine plantation to deciduous forest mixing beech and oaks. The FOR-WIND DSS toolbox will allow to assess the effects of both technical and economic innovations on the expected values of a forest, combining yield and probabilities of wind losses. The technical decisions modelled will involve the choice of species, shorter rotations or changes in the spatial setting of the forests. Economic decisions will focus on the choice between a technical investment for a less risky forest and insurance against wind hazards. The For-Wind DSS Tools will be based on the novel knowledge in environmental mechanics, mechanobiology, statistics and risk economy. Six major items will be addressed: i) The effects of landscape patchiness, soils and tree species and size on the risk of wind hazards. Indeed clear cuts and forest edges modify the leeward wind aerodynamics and thus the spatial distribution of the exposure to wind risks. The soil characteristics (depth, texture and humidity) influence the anchorage strength. Finally tree size and species also play a major role, but little formalized knowledge is available, especially for broadleaved species. ii) The degree of wind acclimation and hardening of trees, through their capacity of sensing chronic winds and modifying their growth allometries accordingly. It is well known that recent forest edges are transiently unfit, but hardens as the trees on the edges grow under their new wind- exposure conditions. This acclimation effect, already poorly formalized at the stand and FMU levels, could give arguments for the use of irregular forests for mitigation purposes. iii) The integration of the previous effects into growth models based on sounded phenomenological laws, and fitted on datasets from long term silvicultural experiments used by research + development institutes to study silviculture. iv) The development of computer models of forest management simulating the simultaneous growth of many stands organized into a structured landscape, including stochastic effects related to climatic hazards and forest vulnerability. v) The issue of the possibility and advantages of insuring forest against wind risks taking their vulnerability and value into account. This value is linked to wood raw production, but also to other external non-market values. vi) The relative benefits on the long run of hard adaptation through silviculture versus soft adaptation through insurances, as well as the impact of public policies (fiscal advantages, subsidising changes in forest management). For-Wind DSS Toolbox will be used to assess management scenarios build with professional experts . and to conduct a debate on the comparative values of management practises. This toolbox will also improve the initial training of students.
France