Abstract Detail

Ecological factors that drive patterns of population genetic structure in plants

Cruzan, Mitchell [1], Diaz, Nicolas [2], Hendrickson, Elizabeth [3], Persinger, Jessica [4], Thompson, Pamela [5].

New Approaches to Landscape Genetic Studies in Plants.

Dispersal is a critical ecological and evolutionary process for establishing new populations and maintaining genetic connectivity among populations. Realized dispersal (gene flow) occurs as individuals or spores successfully contribute to the genetic composition of recipient populations. Gene flow is important for maintaining genetic diversity within populations, and provides a mechanism for the spread of beneficial genetic variants. While patterns of gene flow have traditionally been viewed under a model of isolation by distance (IBD), more recent approaches evaluate the effects of landscape features on genetic connectivity among populations (isolation by resistance; IBR). Landscape genetic studies with plants present unique challenges and opportunities. Because of their sedentary nature, the effects of specific landscape features on patterns of realized dispersal among plant populations can be more accurately determined. On the other hand, landscape genetic studies with plants are intrinsically more complicated because both the habitat requirements of the plant and the behavior of its dispersal vectors need to be considered. We develop a novel approach to plant landscape genetics that separates the effects of habitat suitability from other landscape elements by conducting environmental niche modelling using Maxent with PRISM climatic data and GIS layers representing soil characteristics to generate a habitat raster. We combine the habitat quality layer with GIS layers representing features that might affect vector movement including canopy cover, waterways, topography, and human land use. Genetic distance measures were generated using both maternally-inherited chloroplast haplotype frequencies from whole-genome sequencing after targeted capture, and from nuclear genome-wide SNP surveys using genotyping by sequencing (GBS). Landscape resistance values were optimized using ResistanceGA, and independent effects of landscape features were estimated using multiple regression for distance matrices (MRDM) in the EcoDist R package. We have used this approach to analyze patterns of realized dispersal for several annual and perennial plant species that display a range of seed dispersal syndromes and occur in the highly fragmented upland prairie habitat in southern Oregon. The general patterns revealed by these studies include more frequent long-distance seed movement for wind-dispersed species. Surprisingly, a general trend emerging is that seed dispersal resistance is positively associated with habitat quality; genetic connectivity is lower across continuous stretches of high-quality habitat while dispersal rates are elevated among habitat fragments. Landscape genetic studies such as these contribute to our understanding of the potential for range shifts for plant species under pressure from climate change.

Related Links:
Cruzan Lab Web Site

1 - Portland State University, Department Of Biology, 1719 SW 10th Ave, SRTC Rm 246 - Biology, Portland, OR, 97201, United States
2 - Portland State University, Biology Department, 1719 SW 10th Avenue, SRTC Rm 246, Portland , OR, 97201, United States
3 - Portland State University, Biology, 1719 SW 10th Avenue, SRTC Rm 246, Portland, OR, 97201, United States
4 - Portland State University, Biology, 1719 SW 10th Ave., SRTC Room 246, Portland, OR, 97201, United States
5 - Portland State University, Biology, 1719 SW 10th Ave, SRTC Rm 246 - Biology, Portland, Oregon, 97201, United States

Keywords:
population differentiation
Landscape genetics
Seed dispersal
Population genetics/genomics
Habitat quality.

Presentation Type: Colloquium Presentations
Session: CO11, Ecological factors that drive patterns of population genetic structure in plants
Location: Tucson I/Starr Pass
Date: Wednesday, July 31st, 2019
Time: 10:30 AM
Number: CO11010
Abstract ID:112
Candidate for Awards:None