You are here:
Connectivity in a Heterogeneous Landscape: The Genetics and Population Dynamics of the Olympic MarmotEPA Grant Number: U915967
Title: Connectivity in a Heterogeneous Landscape: The Genetics and Population Dynamics of the Olympic Marmot
Investigators: Cox Griffin, Suzanne A.
Institution: University of Montana
EPA Project Officer: Just, Theodore J.
Project Period: January 1, 2001 through January 1, 2004
Project Amount: $101,632
RFA: STAR Graduate Fellowships (2001) RFA Text | Recipients Lists
Research Category: Fellowship - Terrestrial Ecology and Ecosystems , Academic Fellowships , Ecological Indicators/Assessment/Restoration
As protected areas become increasingly isolated, understanding and maintaining connectivity among populations of key species both within and between remaining areas will become increasingly important. Dispersal is a fundamental determinant of population dynamics and persistence, but a long-standing ecological challenge has been determining the role that the intervening landscape plays in controlling dispersal among local populations. The objective of this research project is to combine demographic estimates of within- and among-population vital rates, genetic analyses, and modeling approaches to explore the influence of landscape composition and structure on movement.
This synthetic approach of combining demographic estimates of within- and among-population vital rates, genetic analyses, and modeling approaches to explore the influence of landscape composition and structure on movement will be used to understand and predict the dynamics of Olympic marmots (Marmota olympus), a naturally fragmented species of conservation concern, endemic to the Olympic Peninsula. To identify the landscape features that impede or enhance connectivity, populations will first be identified in surveys guided by a geographic information system model for suitable habitat. DNA will be collected noninvasively up to 100 local populations to provide pairwise estimates of gene flow among populations. Demographic rates will be estimated from a subset of these populations. Multiple hypotheses representing movement through the landscape will be modeled in a spatially explicit, individually based simulation model of marmot population dynamics. Outputs from different realizations of the simulation model, varying because of the underlying model for dispersal, will be evaluated against observed genetic patterns to identify the most parsimonious model for movement across the landscape. Marmot dynamics will be predicted under possible future climate scenarios, incorporating expected changes in landscape and demographic parameters. Finally, in collaboration with Olympic National Park personnel, a marmot monitoring and management program will be developed based on current and future distribution and demographics, habitat needs and landscape use, and population genetic structure.