A tree- and climate-dependent growth model to predict mature annual cork thickness under different climate change scenarios

Climatic factors drive the annual growth of cork and the subsequent increase in its thickness, which, in addition to porosity, determines the price of cork. Therefore, the simulation of cork thickness is a crucial module of forest growth simulators for cork oak stands. As the existing cork growth models are independent of climatic factors, cork thickness under different climate change scenarios could not be simulated using these models. The primary objective of this study was to develop a climate-dependent tree model to predict annual cork growth. We also verified the hypothesis that the effects of climate change on cork annual growth are nonlinear, and vary with the cork age and thickness. Due to the limited amount of work developed around this topic, we evaluated three candidate models and selected the one that presented best prediction performance as the base model. A set of climate variables that characterized annual climatic conditions were tested in the base model parameters. The resulting climate-dependent model was referred to as the fixed-effects model, and used to initialize a mixed-effect model which accounted for the nested structure of the data. We considered two random effects-the plot and the trees inside the plot. Annual precipitation and the Lang index (ratio between annual precipitation and mean annual temperature) were the variables that showed best results when included in the model parameters. Using a ratio of the variable to cork thickness recorded during the previous year, in both cases, suggested a decline of the positive effect of annual precipitation and the Lang index for increasing cork thickness. The models developed in this study predicted the cork thickness of individual trees based on the cork age and under different climate change scenarios. Therefore, they can be used in forest growth simulators for forest management and research purposes.

Automated summary

This study developed a climate-dependent tree model to predict the annual growth of cork and verified the non-linear effects of climate change on cork growth, which varies with cork age and thickness. By evaluating three candidate models and selecting the one with the best prediction performance as the base model, a climate-dependent fixed-effects model was developed and a mixed-effects model was used to account for the nested structure of the data. The models developed in this study can predict the cork thickness of individual trees based on cork age and under different climate change scenarios.