You are here:
Life History Strategies of Consistently Sparse Tropical Tree SpeciesEPA Grant Number: U915428
Title: Life History Strategies of Consistently Sparse Tropical Tree Species
Investigators: Potts, Matthew D.
Institution: Harvard University
EPA Project Officer: Broadway, Virginia
Project Period: September 16, 1998 through September 1, 2001
Project Amount: $74,792
RFA: STAR Graduate Fellowships (1998) RFA Text | Recipients Lists
Research Category: Academic Fellowships , Ecological Indicators/Assessment/Restoration , Fellowship - Ecology and Ecosystems
The objectives of this research project are to: (1) establish the existence of persistently rare tree species; (2) find the mechanisms that allow these species to persist; and (3) use this knowledge to better understand how different patterns and forms of habitat destruction affect community dynamics. Deforestation in the tropics is occurring at an alarming rate, rare species are becoming rarer, and even common species may become rare. Understanding the ecology of rare trees may reveal methods to better conserve both rare and common species.
To establish the existence of persistently rare species, I will identify species that are rare both temporally and spacially. Persistently rare species remain at low density over large geographic ranges. Data from long-term 50-ha plots in Malaysia and landscape-level surveys of tree abundance throughout Malaysia will identify tree species whose spatial distribution fits that of a persistently rare species. Coalescence theory, as well as matrix models based on stand structure and recruitment dynamics, will establish the population size of persistently rare species over evolutionary and ecological time scales. After identifying the persistently rare species, I will use hierarchical-clustering methods to find life history characteristics that are correlated with low density. Finally, spatial, individual-based models will be developed to investigate the implications for life history strategies of persistently sparse tree species on population and community dynamics. Models will take the form of differential equations and iterative spatial arrays. These models will allow for the generation of field-testable hypotheses that identify the importance of different life history strategies, and the impact of different patterns of habitat destruction on community dynamics.