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Theoretically, species' characteristics should allow estimation of dispersal potential and, in turn, explain levels of population genetic differentiation. However, a mismatch between traits and genetic patterns is often reported for marine species, and interpreted as evidence that life-history traits do not influence dispersal. Here, we couple ecological and genomic methods to test the hypothesis that species with attributes favouring greater dispersal potential—e.g., longer pelagic duration, higher fecundity and larger population size—have greater realized dispersal overall. We used a natural experiment created by a large-scale and multispecies mortality event which created a “clean slate” on which to study recruitment dynamics, thus simplifying a usually complex problem. We surveyed four species of differing dispersal potential to quantify the abundance and distribution of recruits and to genetically assign these recruits to probable parental sources. Species with higher dispersal potential recolonized a broader extent of the impacted range, did so more quickly and recovered more genetic diversity than species with lower dispersal potential. Moreover, populations of taxa with higher dispersal potential exhibited more immigration (71%–92% of recruits) than taxa with lower dispersal potential (17%–44% of recruits). By linking ecological with genomic perspectives, we demonstrate that a suite of interacting life-history and demographic attributes do influence species' realized dispersal and genetic neighbourhoods. To better understand species' resilience and recovery in this time of global change, integrative eco-evolutionary approaches are needed to more rigorously evaluate the effect of dispersal-linked attributes on realized dispersal and population genetic differentiation. 

The extent of parallel genomic responses to similar selective pressures depends on a complex array of environmental, demographic, and evolutionary forces. Laboratory experiments with replicated selective pressures yield mixed outcomes under controlled conditions and our understanding of genomic parallelism in the wild is limited to a few well-established systems. Here, we examine genomic signals of selection in the eelgrass Zostera marina across temperature gradients in adjacent embayments. Although we find many genomic regions with signals of selection within each bay, there is little overlap at the SNP level across bays. We do find overlap at the gene level, potentially suggesting multiple mutational pathways to the same phenotype. Using polygenic models we find that some sets of candidate SNPs are able to predict temperature across both bays, suggesting that small but parallel shifts in allele frequencies may be missed by independent genome scans. Together, these results highlight the continuous rather than binary nature of parallel evolution in polygenic traits and the complexity of evolutionary predictability. 

Abstract The extent of parallel genomic responses to similar selective pressures depends on a complex array of environmental, demographic, and evolutionary forces. Laboratory experiments with replicated selective pressures yield mixed outcomes under controlled conditions and our understanding of genomic parallelism in the wild is limited to a few well‐established systems. Here, we examine genomic signals of selection in the eelgrassZostera marinaacross temperature gradients in adjacent embayments. Although we find many genomic regions with signals of selection within each bay there is very little overlap in signals of selection at the SNP level, despite most polymorphisms being shared across bays. We do find overlap at the gene level, potentially suggesting multiple mutational pathways to the same phenotype. Using polygenic models we find that some sets of candidate SNPs are able to predict temperature across both bays, suggesting that small but parallel shifts in allele frequencies may be missed by independent genome scans. Together, these results highlight the continuous rather than binary nature of parallel evolution in polygenic traits and the complexity of evolutionary predictability. 

Abstract Susan Lynn Williams (1951–2018) was an exceptional marine ecologist whose research focused broadly on the ecology of benthic nearshore environments dominated by seagrasses, seaweeds, and coral reefs. She took an empirical approach founded in techniques of physiological ecology. Susan was committed to applying her research results to ocean management through outreach to decision-makers and resource managers. Susan’s career included research throughout the USA in tropical, temperate, and polar regions, but she specialized in tropical marine ecology. Susan’s scholarship, leadership, and friendship touched many people, leading to this multi-authored paper. Susan’s scholarship was multi-faceted, and she excelled in scientific discovery, integration of scientific results, application of science for conservation, and teaching, especially as a mentor to undergraduate and graduate students and postdoctoral scholars. Susan served in a variety of leadership positions throughout her career. She embodied all facets of leadership; leading by example, listening to others, committing to the “long haul,” maintaining trust, and creating a platform for all to shine. Susan was an important role model for women in science. Susan was also a loyal friend, maintaining friendships for many decades. Susan loved cooking and entertaining with friends. This paper provides an overview of the accomplishments of Susan in the broad categories of scholarship, leadership, and friendship.