Deadwood stocks in south-western European forests: Ecological patterns and large scale assessments

Abstract

Forest deadwood is a relevant factor in the provision of ecosystem services (forest biodiversity, carbon sequestration, recreational and aesthetic values), but it also influences the risk and impact of forest perturbations. Hence, reliable estimations are urgently need in the lack of detailed information in Mediterranean forests at large scales. In this study we provide, for the first time, national-level estimations for Spain based on the information from the Spanish National Forest Inventory (38,945 plots). In addition, we compare and validate two approaches for estimating deadwood stocks where data is lacking; the first of these being a modelling approach based on stand, climatic and physiographical variables, and the other considers the ratio between deadwood and living biomass. We also examine the different patterns stock across forest types in four biogeographical regions according to a broad-spectrum of species groups and forests with different degrees of anthropogenic influence. The degrees are based on levels of protection and naturalness categories. The modelling approach provides more robust deadwood estimates and better predictive capacity than the ratio approach. Alpine (6.09 Mg.ha^-1) and Atlantic (3.53 Mg.ha^-1) bioregion forests store significantly higher mean deadwood biomass stocks than Macaronesian and Mediterranean forests. However, the share of deadwood in relation to the total biomass stock is greater in Mediterranean biogeographical region. As regards species groups, the mean deadwood stock of mixed forests doubled the stocks found in conifer and broadleaved dominated forests. We also found significant differences in deadwood biomass stocks between forests with different levels of anthropogenic protection. However, forest types with intensive forest management had contrasting figures for deadwood stock. The mean values obtained at national level according to forest type, bioregion and degree of anthropogenic influence, provide baseline information for carbon accounting as well as for other forest policy planning and management strategies.

Keywords: Carbon accounting; Forest biodiversity indicator; Generalized additive model; National statistics; Sustainability.