Genetic‐environment associations are increasingly revealed through population genomic data and can occur through a number of processes, including secondary contact, divergent natural selection, or isolation by distance. Here, we investigate the influence of the environment, including seasonal temperature and salinity, on the population structure of the invasive European green crab (Carcinus maenas) in eastern North America. Green crab populations in eastern North America are associated with two independent invasions, previously shown to consist of distinct northern and southern ecotypes, with a contact zone in southern Nova Scotia, Canada. Using a RAD‐seq panel of 9,137 genomewide SNPs, we detected 41 SNPs (0.49%) whose allele frequencies were highly correlated with environmental data. A principal components analysis of 25 environmental variables differentiated populations into northern, southern, and admixed sites in concordance with the observed genomic spatial structure. Furthermore, a spatial principal components analysis conducted on genomic and geographic data revealed a high degree of global structure (p < .0001) partitioning a northern and southern ecotype. Redundancy and partial redundancy analyses revealed that among the environmental variables tested, winter sea surface temperature had the strongest association with spatial structuring, suggesting that it is an important factor defining range and expansion limits of each ecotype. Understanding environmental thresholds associated with intraspecific diversity will facilitate the ability to manage current and predict future distributions of this aquatic invasive species.

In the northwest Atlantic Ocean, sea scallop (Placopecten magellanicus) has been characterized by a latitudinal genetic cline with a breakpoint between northern and southern genetic clusters occurring at ~45°N along eastern Nova Scotia, Canada. Using 96 diagnostic single-nucleotide polymorphisms (SNPs) capable of discriminating between northern and southern clusters, we examined fine-scale genetic structure of scallops among 27 sample locations, spanning the largest geographic range evaluated in this species to date (~37-51°N). Here, we confirmed previous observations of northern and southern groups, but we show that the boundary between northern and southern clusters is not a discrete latitudinal break. Instead, at latitudes near the previously described boundary, we found unexpected patterns of fine-scale genetic structure occurring between inshore and offshore sites. Scallops from offshore sites, including St. Pierre Bank and the eastern Scotian Shelf, clustered with southern stocks, whereas inshore sites at similar latitudes clustered with northern stocks. Our analyses revealed significant genetic divergence across small spatial scales (i.e., 129-221 km distances), and that spatial structure over large and fine scales was strongly associated with temperature during seasonal periods of thermal minima. Clear temperature differences between inshore and offshore locations may explain the fine-scale structuring observed, such as why southern lineages of scallop occur at higher latitudes in deeper, warmer offshore waters. Our study supports growing evidence that fine-scale population structure in marine species is common, often environmentally associated, and that consideration of environmental and genomic data can significantly enhance the identification of marine diversity and management units.

To develop more reliable marine species distribution models (SDMs), we examine how genetic, climatic, and biotic interaction gradients give rise to prediction error in marine SDM. Genetic lineages with distinct ecological requirements spanning genetic gradients have yet to be treated separately in marine SDM, which are often constrained to modeling the potential distribution of one biological unit (e.g. lineage or species) at a time. By comparing SDM performance for the whole species or where observation and predictions were partitioned among geographically discontinuous genetic lineages, we first identified the appropriate biological unit for modeling sea scallop. Prediction errors, in particular contiguous omissions at the northern range margins were effectively halved in genetic lineage SDM (Total error=15%) verses whole species SDM. Remaining SDM prediction error was strongly associated with: i) Sharp climatic gradients (abrupt and persistent spatial shifts in limiting temperatures) found within continental shelf breaks and bottom channels. ii) A biotic gradient in the predation of sea scallop juveniles by the sand star within the Hudson Shelf USA. Our findings highlight how the accuracy of marine SDM is dependent on capturing the appropriate biological unit for modeling (e.g. lineages rather than species) and adequately resolving limiting abiotic and biotic interaction gradients.