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

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. (C) 2007 Elsevier B.V. All rights reserved.