Print PageDemographic vital rates of forest tree species have proved essential data in understanding important patterns in forest systems. Constructing models of future species behaviours of observed forests (not simulated) has been more difficult, as the common tools of population demography (e.g., PVA analysis from matrix models) require data difficult to acquire, such as fecundity, or parameterize accurately. New applications of integral projection models (IPMs), however, can use commonly gathered information on the growth and survival of tree species to infer accurate near-term (decadal) predictions of tree species population dynamics with uncertainty. Here I present analyses applying IPMs to data collected from the Smithsonian Institution’s Global Earth Observatory site in the Ituri forest of central Africa to show how snapshots of forest size distributions can be used to infer long-term changes in forest composition.
Results/Conclusions
Results support an hypothesized long-term (millennial) shift in the composition of a high-diversity forest to a mono-dominant assemblage where one tree species, Gilbertiodendron xxxxx) accounts for the majority of biomass. This approach offers many potential applications for predicting the population trajectories of communities of long-lived organisms in dynamic environments using commonly collected data.
