| Summary: | Forest dieback because of drought is a global phenomenon threatening particular tree populations. Particularly vulnerable stands are usually located in climatically stressing locations such as xeric sites subjected to seasonal drought. These tree populations show a pronounced loss of vitality, growth decline, and high mortality in response to extreme climate events such as heat waves and droughts. However, dieback events do not uniformly affect stands, with some trees showing higher symptoms of drought vulnerability than other neighboring conspecifics. In this study, we investigated if trees showing different vulnerabilities to dieback showed lower growth rates (Grs) and higher sensitivities to the climate in the past using dendroecology and the Vaganov-Shashkin (VS) process-based growth model. We studied two Pinus pinaster stands with contrasting Grs showing recent dieback in the Iberian System, north-eastern Spain. We compared coexisting declining (D) and non-declining (ND) trees with crown defoliation values above and below the 50% threshold, respectively. The mean growth rate was lower in D than in ND trees in the two stands. The two vigor classes showed a growth divergence prior to the dieback onset and different responsiveness to climate. The ND trees were more responsive to changes in spring water balance and soil moisture than D trees, indicating a loss of growth responsiveness to the climate in stressed trees. Such an interaction between water availability and vigor was reflected by the VS-model simulations, which provided evidence for the observation that growth was mainly limited by low soil moisture in both sites. Such an interaction between water availability and vigor was reflected by the VS-model simulations, which provided evidence for the observation that growth was mainly limited by low soil moisture in both sites. The presented comparisons indicated different stand vulnerabilities to drought contingent on-site conditions. Further research should investigate the role played by environmental conditions and individual features such as access to soil water or hydraulic traits and implement them in process-based growth models to better forecast dieback.
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