Evidence for interannual variation in genetic structure of Dungeness crab (Cancer magister) along the California Current System

Abstract

Using a combination of population- and individual-based analytical approaches, we provide a comprehensive examination of genetic connectivity of Dungeness crab (Cancer magister) along ~1,200 km of the California Current System (CCS). We sampled individuals at 33 sites in 2012 to establish a baseline of genetic diversity and hierarchal population genetic structure and then assessed interannual variability in our estimates by sampling again in 2014. Genetic diversity showed little variation among sites or across years. In 2012, we observed weak genetic differentiation among sites (F range = -0.005-0.014) following a pattern of isolation by distance (IBD) and significantly high relatedness among individuals within nine sampling sites. In 2014, pairwise F estimates were lower (F range = -0.014-0.007), there was no spatial autocorrelation, and fewer sites had significant evidence of relatedness. Based on these findings, we propose that interannual variation in the physical oceanographic conditions of the CCS influences larval recruitment and thus gene flow, contributing to interannual variation in population genetic structure. Estimates of effective population size (N ) were large in both 2012 and 2014. Together, our results suggest that Dungeness crab in the CCS may constitute a single evolutionary population, although geographically limited dispersal results in an ephemeral signal of IBD. Furthermore, our findings demonstrate that populations of marine organisms may be susceptible to temporal changes in population genetic structure over short time periods; thus, interannual variability in population genetic measures should be considered.

Uncovering mechanisms of global ocean change effects on the Dungeness crab (Cancer magister) through metabolomics analysis

“…While we attempted to control for variation between individuals by collecting animals from the same location within a 2-month period, we were unable to control for prior environmental exposure or genetic background of the wild-caught animals we used. Where prior studies have found high genetic variation among individuals within one sampling site 47,48 , we suspect that both genetics and prior environmental exposure likely contributed to the high variation in metabolite abundances among individuals within treatment groups, which may have obscured the different treatment effects. Within-sample variation could be reduced by sampling from a specific tissue rather than using whole animals, however this may be challenging in early stage juvenile Dungeness crabs given their small size.…”

Dimensions of genotypic and phenotypic divergence in marine metapopulations: space, time, and ontogeny

“…Spatially, subpopulations that are geographically proximate may exhibit greater genotypic differentiation than more distant subpopulations (Watts et al 1990;Iacchei et al 2013;Thomas et al 2015;Norderhaug et al 2016;DiBattista et al 2017). Temporally, patterns of genotypic differentiation fluctuate through time because of turnover in genotypic variation (Johnson and Black 1982;Hogan et al 2010Hogan et al , 2012Jackson et al 2017). Consequently, genotypic differentiation within a focal site over time can be at comparable, or greater, magnitudes to that seen among subpopulations across space (Gould and Dunlap 2017;Villacorta-Rath et al 2017).…”

“…However, my observations do not show strong support for true panmixia, and instead, show greater alignment with expectations of chaotic genetic patchiness (Table 3.1). Spatial genotypic structure was temporally variable and unrelated to the distance between sites (Figure 3.2), a typical feature of chaotic genetic patchiness (Johnson and Black 1982;DiBattista et al 2017;Jackson et al 2017).…”

“…Even in species that are capable of high dispersal, not all habitat patches may be well connected, resulting in spatial variability in the extent to which a system exists as a more-structured versus well-connected metapopulation (Harrison and Hastings 1996). The spatial distribution of habitat, or factors that limit dispersal, might also be temporally variable, which affects connectivity across metapopulations through time (Hanski 1999;Gómez Fernández et al 2016;Jackson et al 2017).…”

“…Typically, in demersal marine species, dispersal is restricted to early life stages and propagules (gametes, eggs, or larvae) pelagically disperse via ocean currents (see for example: Schmidt and Rand 1999;Christie et al 2010;Moody et al 2015;Thia et al 2018). This potentially affords huge dispersal potential in such systems, and many marine species exhibit chaotic genetic patchiness, a pattern of weak but significant genotypic structure that is uncorrelated with space and variable through time (Johnson and Black 1982;Hogan et al 2010;Toonen and Grosberg 2011;Selwyn et al 2016;Jackson et al 2017).…”