An empirical ecological-type model for predicting stone pine ( Pinus pinea L.) cone production in the Northern Plateau (Spain)

Abstract

Data from a 10 year series of cone production taken from 755 trees were used to model individual cone production in stone pine ( Pinus pinea L.) stands in the Northern Inland Plateau of Spain following three different approaches. The first step was the construction of a silvicultural model, including typical forest growth covariates as tree size, stand density, site index and distance independent competition indices. Remaining between-plot variability was related with ecological attributes, as winter rainfall and altitude, resulting in a hybrid model. The third approach attempted to develop an ecological-type based model by considering a previous stratification of stone pine forests based on altitude, soil, geology and climate characteristics. The best model in terms of likelihood, bias and accuracy on predictions was the ecological-type one, producing unbiased marginal estimates for the main part of the territory with an efficiency reaching up to 39%. Due to the hierarchical structure of data set, proposed model was formulated as a multilevel mixed model. Stochastic formulation allows simulating cone production under different changing scenarios and describing real distribution of cone production within a given stand. Developed model constitutes the cone yield module for PINEA2, an integrated single tree model for the management of stone pine stands within the northern Plateau of Spain.