Autecology and growth of Aleppo pine ( Pinus halepensis Mill.) | Autecology and growth of Aleppo pine ( Pinus halepensis Mill.): A comprehensive study in France

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SEDYVIN [ADD1_IRSTEA]Dynamique et fonctionnement des écosystèmes

إنجليزي. Aleppo pine (Pinus halepensis Mill.) is one of the dominant conifer species in the Mediterranean area. Many studies have investigated the role of climate variables (precipitations, temperature) in its occurrence and growth, but few have taken the effect of local site conditions into account, nor their interaction with climate.This study aimed at thoroughly assessing forest sites potential for Aleppo pine in France, and designing a practical tool to help forest managers implementing these results. The study is based on a network of 512 plots laid out in the French Mediterranean area, where 2158 trees were measured. A site index was computed using a height growth model calibrated on these plots. Using neural networks and partial least square regression models (PIS), we disentangled the effects of climatic factors and local site conditions in Aleppo pine presence and growth.Local water balance (assessed through topography, soil, geology and legacies of past human activities) was the main factor driving Aleppo pine productivity in the study area. Climate played a significant role as a whole but more important at the species distribution margins, frost and snow limiting Aleppo pine range northwards and in elevation. Based on these results, a practical tool was designed for two different types of mother rocks to help assessing forest site potential for Aleppo pine.As the span of climate conditions in south-eastern France includes most of those found in Aleppo pine distribution area, except the driest and hottest ones found in its southernmost locations, this study could easily be used or adapted in most other concerned countries. Because of the ongoing climate change and increasing drought in the Mediterranean area, the balance between local and climate factors may change in time and space. Our results show that without an accurate knowledge of local conditions, the impact of climate change cannot be predicted.