Room 6C/6E Landscape Genetics of Native Plant Species in Arches and Canyonlands National Parks

Friday, October 12, 2012: 8:00 PM
6C/6E (WSCC)
Meeyoon Choo, MS , Biology Department, University of Memphis, Memphis, TN
Takuya Nakazato, PhD , University of Memphis, Memphis
Troy Wood, PhD , US Geological Survey, Arizona, AZ
Changing climate conditions and human activities are the main effects of grassland degradation. Climate has increased in temperature significantly, altered precipitation regimes, and greater aridity in southwestern drylands. The ecosystem resilience to climate change is enhanced by greater diversity in terms of different responses to climate variables. This suggests that a key climate adaptation strategy for land management agencies such as National Park Service (NPS) is to maintain or restore diversity in the systems for which they have stewardship responsibilities. In addition to species and functional diversity, genetic diversity also is an important consideration for restoration- particularly in the context of changing climatic conditions. In this project, native plant species, Stipa hymenoides, is identified for use in the restoration of Colorado Plateau grasslands- by sampling individuals from populations distributed across a 760m (2500ft) elevation gradient spanning Arches National Park, Canyonlands National Park. AFLP genotyping was used to evaluate whether patterns in genetic variability are correlated with landscape features. Analyses of AFLP data revealed moderate population structure (Fst = 0.15), indicating there has moderate level of gene flow among populations. However, PCoA and Mantel test (IBD) showed a positive correlation in genetic structure corresponds with the spatial landscape, suggusting there has some geographic barriers or features influence the process of gene flow and dispersal. Therefore, ongoing analyses are exploring correlations between allele frequencies and elevation, a proxy for climate. This project can greatly assist restoration ecology through aiding identification of effective genotypes and prediction of ecosystem recovery and for conservation genetics.