Using Artificial Neural Networks to Model Initial Recruitment of Mediterranean Pine Forests

Artificial Neural Networks (NNs) have been recognized as a powerful tool for automatically learning complex relationships in data. In this paper, we propose to apply such a tool for modeling forest regeneration, a possibility not yet investigated in the literature. In order to evaluate the capability of NNs to simulate initial recruitment of pine species in Mediterranean forests, a feed-forward multi-layer neural network has been applied to seed germination and seedling survival of four pine species under three soil conditions, with or without seed protection, in Castilla La Mancha (Central-Eastern Spain). The experimental campaign has shown good performance in predicting the two pine initial recruitment stages. The proposed approach may help to predict the success of natural regeneration in Mediterranean pine forests under different basal areas and management strategies.