Table of Contents

• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Data Files
• Parameters
• Instruments
• Deployments
• Project Information
• Funding

A re-sampling of historical population genetic surveys of Zostera marina from Bodega (BB), Tomales (TB), and San Francisco Bays (SFB) USA. Plant (Zostera marina) samples were collected from Bodega Bay, Tomales Bay, and San Francisco Bay in 2013. DNA was extracted and amplified in the Stachowicz and Grosberg labs at UCDavis, and fragments were analyzed at the UCDavis core facility during 2014-2015. Data are presented as number of base pairs.

Both sampling and analyses are described in the manuscript in press in the journal Heredity, titled "Temporal stability in patterns of genetic diversity and structure of a marine foundation species (Zostera marina)".

Briefly, we re-sampled Z. marina populations previously described genetically in the literature. Because the goal of sampling these populations was to compare changes over time within each region, we designed the re-sampling to match the previously published studies as closely as possible. Consequently, sampling schemes (haphazard collection (SFB) vs. quadrat sampling (TB and BB)) differed between regions. DNA from all samples was analyzed at 12 microsatellite loci.

We amplified 12 previously characterized microsatellite loci (CT12, CT19 (Reusch 2000), CT3, GA2, GA3 (Reusch et al. 1999), CL32 Contig 2, ZMC 12075, ZMC 13053, ZMC 19017, (Oetjen & Reusch 2007), CL 559 Contig 1, CL172 Contig 1, ZMC 19062 (Oetjen et al. 2010)). We analyzed fragments on an ABI 3010XL at the UC Davis DNA sequencing facility, and visualized the fragments using STRand software (Toonen & Hughes 2001). 

BCO-DMO Processing:
- modified parameter names to conform with BCO-DMO naming conventions; appended "a1" (allele 1) or "a2" (allele 2).
- added columns containing the full name/meaning for region, meadow, and tidal height codes.

There is growing evidence that genetic variation within and among populations of key species plays an important role in marine ecosystem processes. Several experiments provide compelling evidence that the number of genotypes in an assemblage (genotypic richness) can influence critical ecosystem functions including productivity, resistance to disturbance and invasion or colonization success. However, these studies use only the number of genotypes as a measure of genetic diversity. Recent analyses of species diversity experiments show that phylogenetic diversity may be a more reliable predictor of ecosystem functioning than simply the number of species. However, such approaches have not yet been applied to understanding the effects of genetics on ecosystem functioning. While genetic relatedness within a species holds the potential to predict the outcome of intraspecific interactions, and the functioning of ecosystems that depend on those species, we currently have few data to assess the shape or strength of this relationship. The investigators will build on their own previous work, and that of others, in eelgrass (Zostera marina) ecosystems showing strong effects of genotypic richness on a spectrum of critical ecosystem processes. The investigators will ask whether genotypic richness, or - as in studies at the level of species diversity - genetic relatedness/distance better predicts ecosystem functioning? If genetic relatedness measures are better predictors, then what mechanisms underlie this relationship? Can genetic relatedness predict ecological relatedness?

Although the current focus is on eelgrass, the research should be applicable to many systems. The project will assess the relationship between genetic relatedness and phenotypic distinctiveness of a key marine foundation species and use manipulative experiments to test the relative importance of the number of genotypes in an assemblage vs. their genetic relatedness and trait diversity for ecosystem functioning. Specifically, experiments will:
(1) characterize the relationship between genetic relatedness and trait similarity among individual genotypes of eelgrass, including responses to experimental warming;
(2) compare the effects of genetic relatedness and trait similarity among genotypes on the outcome of intraspecific competitive interactions; and
(3) test the relative effect of genetic relatedness vs. number of genotypes of eelgrass on the growth of eelgrass, its associated ecosystem functions it (e.g., primary production, nutrient dynamics, trophic transfer, habitat provision, and detrital production and decomposition).

Seagrass ecosystems provide important services to coastal regions including primary production, nutrient cycling, habitat for fisheries species, and erosion control. Previous studies have shown these services can be compromised by reduction in the numbers of species of grazers or genotypes, but this study will allow a more predictive approach to diversity loss by integrating the effects of multiple components of diversity and clarifying the extent to which diversity effects can be predicted by the genetic or ecological uniqueness of component genotypes.