Fine-scale seascape genomics of an exploited marine species, the common cockle Cerastoderma edule, using a multi-modelling approach

Abstract

5 6 Running title: Seascape genomics of the common cockle 7 8ABSTRACT 26 Population dynamics of marine species that are sessile as adults are driven by oceanographic 27 dispersal of larvae from spawning to nursery grounds. This is mediated by life-history traits 28 such as the timing and frequency of spawning, larval behaviour and duration, and settlement 29 success. Here, we use 1725 single nucleotide polymorphisms (SNPs) to study the fine scale 30 spatial genetic structure in the commercially important cockle species Cerastoderma edule 31 and compare it to environmental variables and current-mediated larval dispersal within a 32 modelling framework. Hydrodynamic modelling employing the NEMO Atlantic Margin 33 Model (AMM15) was used to simulate larval transport and estimate connectivity between 34 populations during spawning months (April -September), factoring in larval duration and 35 seasonal variability of ocean currents. Results at neutral loci reveal the existence of three 36 separate genetic clusters (mean FST=0.021) within a relatively fine spatial scale in the 37 northwest Atlantic. Environmental association (EA) analysis indicates that oceanographic 38 currents and geographical distance between the populations explain over 20% of the variance 39 observed at neutral loci, while genetic variance (71%) at outlier loci was explained by sea 40 surface temperatures extremes. These results fill an important knowledge gap in the 41

Using biophysical modelling and population genetics for conservation and management of an exploited species, Pecten maximus L.

“…As well as being impractical to simulate 3D ocean circulation over decadal scales with a spatially high‐resolution (0.87–1.38 km) model, extreme cold and warm years are expected to represent a maximal range of residual flows and hence dispersal. This was confirmed by Coscia et al (2020), who conducted similar particle tracking simulations over several years (practical in this case since the domain was smaller—Irish Sea only), showing variability in dispersal between years that was similar to that simulated in this study. During the simulated cold year (1986), stratification caused by solar heating during the summer was relatively weak, hence, the associated density‐driven currents that are key to larval transport were also weak.…”

“…Such biophysical models have been used in conjunction with genetic studies of meta‐populations (e.g. Coscia et al, 2012, 2020; Gormley et al, 2015). Biophysical models will predict a range of plausible connectivities, for a specific period and given sufficient information on larval behaviour; although validation is challenging since larvae are too small to track.…”

Multi-model seascape genomics identifies distinct environmental drivers of selection among sympatric marine species

“…3). Previous seascape genomic studies in temperate regions have frequently identified some measure of SST as the best predictor of genomic variation of marine invertebrates [9,11,12,25,28,67], which is most likely due to SST affecting both cellular processes, and life-history events such as spawning and larval development [63]. However, for P. angulosus, Trange and SSTmean best explained genomic variation, whereas SSSmean best explained the structure of C. punctatus.…”

Multi-model seascape genomics identifies distinct environmental drivers of selection among sympatric marine species

“…3). Previous seascape genomic studies in temperate regions have frequently identified some measure of SST as the best predictor of genomic variation of marine invertebrates [9,11,12,25,28,51], which is most likely due to SST affecting both cellular processes, and life-history events such as spawning and larval development [52]. However, for P. angulosus, Trange and SSTmean best explained genomic variation, whereas SSSmean best explained the structure of C. punctatus.…”