A stage-structured hierarchical Bayes model for the babassu palm tree population dynamics – Estimated from anthropogenic open area data sets

Abstract

The babassu palm tree (Attalea speciosa Mart. ex Spreng.) is an endemic species of Amazon forests, and has social and economical impact/utility. Deforestation highlights this palm tree in anthropogenic open areas (pastures and cultivated fields). Simultaneously, knowledge concerning the sustainable functioning of the species within these manmade environments is sorely lacking: its life cycle is not well known, and its population dynamics remains unstudied. In this study, our objective was to generate a model of the population dynamics of the babassu palm tree, validated by in situ analysis, to understand how babassu, a forest species, adapts to pastureland and, under certain conditions, becomes invasive. We propose a random matrix model with aggregated variables based on the biological stages of the species as the input. The probabilities of the between-stage transition matrix were modelled using a Dirichlet-multinomial model with a hierarchy taking geographical organization, i.e. transect level, into account. The integration of prior information was formulated through a Bayesian approach. This Bayesian hierarchical matrix model enabled us to demonstrate a bottleneck in the population dynamics and a high year-dependent mortality rate at an early stage.