A joint individual-based model coupling growth and mortality reveals that tree vigor is a key component of tropical forest dynamics

Authored by Melaine Aubry-Kientz, Vivien Rossi, Jean-Jacques Boreux, Bruno Herault

Date Published: 2015

DOI: 10.1002/ece3.1532

Sponsors: French National Research Agency (ANR)

Platforms: R

Model Documentation: ODD Mathematical description

Model Code URLs: http://onlinelibrary.wiley.com/store/10.1002/ece3.1532/asset/supinfo/ece31532-sup-0001-AppendixS1.pdf?v=1&s=2f3ab0cb6977c0f2a1ac270e484851f60d93a92e

Abstract

Tree vigor is often used as a covariate when tree mortality is predicted from tree growth in tropical forest dynamic models, but it is rarely explicitly accounted for in a coherent modeling framework. We quantify tree vigor at the individual tree level, based on the difference between expected and observed growth. The available methods to join nonlinear tree growth and mortality processes are not commonly used by forest ecologists so that we develop an inference methodology based on an MCMC approach, allowing us to sample the parameters of the growth and mortality model according to their posterior distribution using the joint model likelihood. We apply our framework to a set of data on the 20-year dynamics of a forest in Paracou, French Guiana, taking advantage of functional trait-based growth and mortality models already developed independently. Our results showed that growth and mortality are intimately linked and that the vigor estimator is an essential predictor of mortality, highlighting that trees growing more than expected have a far lower probability of dying. Our joint model methodology is sufficiently generic to be used to join two longitudinal and punctual linked processes and thus may be applied to a wide range of growth and mortality models. In the context of global changes, such joint models are urgently needed in tropical forests to analyze, and then predict, the effects of the ongoing changes on the tree dynamics in hyperdiverse tropical forests.
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Competition Uncertainty sensitivity Projections Size Survival Traits Wood density Lowland rain-forest Nothofagus