Annals of Forest Science, is a source of information about current developments and trends in forest research and forestry

A generalized height-diameter equation, along with a crown diameter prediction equation for cork oak forests in Spain were developed based on data from the Second Spanish Forest Inventory. Nine generalised height-diameter equations were selected as candidate functions to model the height-diameter under cork relationship, while for the crown diameter prediction model five linear and non-linear equations were tested. The equations were fitted using the mixedeffects model approach. The Stoffels & Van Soest power equation, constrained to pass through the point of dominant diameter and dominant height, was selected as the generalised height-diameter model. Regarding the crown diameter prediction model, the parable function without the intercept and with quadratic mean diameter incorporated as a fixed effect into the b parameter, proved to be the model with best prediction capabilities. The models were validated by characterising the model error using the PRESS (Prediction Sum of Squares) statistic. Both equations will be submodels of the ALCORNOQUE v1.0, a management oriented growth and yield model for cork oak forests in Spain.

Forest disturbances such as drought, fire, and logging affect the forest carbon dynamics and the terrestrial carbon sink. Forest mortality after disturbances creates uncertainties that need to be accounted for to understand forest dynamics and their associated C‐sink. We combined data from permanent resampling plots and biomass oriented dendroecological plots to estimate time series of annual woody biomass growth (ABI) in several forests. ABI time series were used to benchmark a vegetation model to analyze dynamics in forest productivity and carbon allocation forced by environmental variability. The model implements source and sink limitations explicitly by dynamically constraining carbon allocation of assimilated photosynthates as a function of temperature and moisture. Bias in tree‐ring reconstructed ABI increased back in time from data collection and with increasing disturbance intensity. ABI bias ranged from zero, in open stands without recorded mortality, to over 100% in stands with major disturbances such as thinning or snowstorms. Stand leaf area was still lower than in control plots decades after heavy thinning. Disturbances, species life‐history strategy and climatic variability affected carbon‐partitioning patterns in trees. Resprouting broadleaves reached maximum biomass growth at earlier ages than nonresprouting conifers. Environmental variability and leaf area explained much variability in woody biomass allocation. Effects of stand competition on C‐allocation were mediated by changes in stand leaf area except after major disturbances. Divergence between tree‐ring estimated and simulated ABI were caused by unaccounted changes in allocation or misrepresentation of some functional process independently of the model calibration approach. Higher disturbance intensity produced greater modifications of the C‐allocation pattern, increasing error in reconstructed biomass dynamics. Legacy effects from disturbances decreased model performance and reduce the potential use of ABI as a proxy to net primary productivity. Trait‐based dynamics of C‐allocation in response to environmental variability need to be refined in vegetation models.