Environmental Covariability, Demographic Connectivity, and the Dynamics of Pacific Salmon (Oncorhynchus Spp.) PopulationsEPA Grant Number: U915719
Title: Environmental Covariability, Demographic Connectivity, and the Dynamics of Pacific Salmon (Oncorhynchus Spp.) Populations
Investigators: Regetz, James
Institution: Princeton University
EPA Project Officer: Lee, Sonja
Project Period: August 1, 2000 through August 1, 2003
Project Amount: $102,000
RFA: STAR Graduate Fellowships (2000) RFA Text | Recipients Lists
Research Category: Academic Fellowships , Ecological Indicators/Assessment/Restoration , Fellowship - Ecology and Ecosystems
The objectives of this research are to: (1) develop empirical models and statistical approaches to quantify dispersal and shared environmental forcing among spawning populations of Pacific salmon (Oncorhynchus spp.); and (2) derive general rules for how the relative contribution of different sources of covariation will affect persistence of populations under alternative patterns of local management and restoration.
Because direct observation of salmon movement between spawning areas is impractical, indirect inference from genetic data is a preferable approach. A new likelihood framework based on coalescent theory will be used to estimate gene flow among spawner populations. A population simulation model is being developed to test and refine this likelihood method. The method then will be used to estimate straying in chinook (O. tshawytscha) and steelhead (O. mykiss) populations of the Grande Ronde River basin, OR, and of a coastal river system. These results will be used to parameterize straying propensity as a function of hydrographic variables, creating a simple model that can be extended to other basins. Environmental covariability then will be addressed by statistically assessing the relationships between subpopulation demographic data and relevant stream, watershed, and climate attributes. Guided by these analyses, probability densities will be generated for local vital rates, conditional on environmental variables. Finally, these empirical estimates of specific sources of covariation will be integrated into a spatially explicit population viability model to predict whether the spatial distribution of management efforts affects population persistence. For example, under what conditions will small but diffuse restoration projects be more effective than a single large project that targets a cluster of subpopulations? A corollary study will assess the ability of simple, analytic models to generate qualitatively similar predictions.
This research is expected to result in the development of a tool to predict how the effects of local management actions are likely to perpetuate through the aggregate population of Pacific salmon over time.