Inferring forest fate from demographic data: from vital rates to population dynamic models

Authored by Jessica Needham, Cory Merow, Sean M McMahon, Chia-Hao Chang-Yang, Hal Caswell

Date Published: 2018

DOI: 10.1098/rspb.2017.2050

Sponsors: Biotechnology and Biological Sciences Research Council (BBSRC) United States National Science Foundation (NSF)

Platforms: R

Model Documentation: Other Narrative Mathematical description

Model Code URLs: https://dx.doi.org/10.6084/m9.figshare.c.4010356.

Abstract

As population-level patterns of interest in forests emerge from individual vital rates, modelling forest dynamics requires making the link between the scales at which data are collected (individual stems) and the scales at which questions are asked (e.g. populations and communities). Structured population models (e.g. integral projection models (IPMs)) are useful tools for linking vital rates to population dynamics. However, the application of such models to forest trees remains challenging owing to features of tree life cycles, such as slow growth, long lifespan and lack of data on crucial ontogenic stages. We developed a survival model that accounts for size-dependent mortality and a growth model that characterizes individual heterogeneity. We integrated vital rate models into two types of population model; an analytically tractable form of IPM and an individual-based model (IBM) that is applied with stochastic simulations. We calculated longevities, passage times to, and occupancy time in, different life cycle stages, important metrics for understanding how demographic rates translate into patterns of forest turnover and carbon residence times. Here, we illustrate the methods for three tropical forest species with varying life-forms. Population dynamics from IPMs and IBMs matched a 34 year time series of data (albeit a snapshot of the life cycle for canopy trees) and highlight differences in life-history strategies between species. Specifically, the greater variation in growth rates within the two canopy species suggests an ability to respond to available resources, which in turn manifests as faster passage times and greater occupancy times in larger size classes. The framework presented here offers a novel and accessible approach to modelling the population dynamics of forest trees.

Tags

individual-based models Forest ecology Diversity Demography Light growth Climate-change Rain-forest Density-dependence Life-history strategies Tropical forest Integral projection models Integral projection models Population projections Tree-size distributions Neotropical tree