Potential climatic influence on the maximum stand carrying capacity of 15 Mediterranean conifers and broadleaves

Abstract

Climate change projections for the Mediterranean basin predict a continuous increment in extreme drought and heat episodes, affecting forest dynamics, structure and composition. Understanding how climate influences the maximum size-density relationship (MSDR) is therefore critical to design adaptative silvicultural guidelines based on the potential stand carrying capacity of tree species. With this aim, data from the Third Spanish National Forest Inventory (3NFI) and WorldClim databases were used to analyze climate related variations of the maximum stand carrying capacity for 15 species from the Pinus, Fagus and Quercus genus. First, basic MSDR were fitted using linear quantile regression and observed size-density data from monospecific 3NFI plots. Reference values of maximum stocking, expressed as SDImax, were estimated by species. In a second step, climatedependent MSDR models including 35 different annual and seasonal climatic variables were fitted. The best climate-dependent MSDR model was selected by species according to the Akaike Information Criteria in order to analyze general and species-specific trends in the SDImax variation. Results showed a common trend across species in SDIgenus variation with smaller SDImax values linked to drier and warmer conditions, suggesting potential reductions of the maximum stocking for this species based on projected climatic scenarios. Opposed to this trend, results for Pinus nigra suggest that milder winters as effect of increments in minimum temperatures could beneficiate mountainous species. Humidity (expressed as the De Martonne Index) was found as key driver affecting SDImax of Fagus species, since changes in spring and summer temperatures explained SDImax variations of Quercus species. Pinus species were indistinctively affected by temperature and water stress. All the selected climate-dependent models improved the goodness of fit over the basic and the business-as-usual models including the De Martonne Index as independent climatic variable. Our findings highlight the importance of using specific climatic variables to better characterize climatic impacts on the MSDR. Models presented in this study will allow to obtain more precise estimations of the maximum stocking for different coniferous and broadleaved species, providing an advanced tool for managing Mediterranean pure and mixed forests under different scenarios of climate change.