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Dokai, W.

Publications and source records attributed to Dokai, W..

2 recordsLinked to original sources

Leveraging eDNA metabarcoding to characterize nearshore fish communities in Southeast Alaska: Do habitat and tide matter?

Nearshore marine habitats are critical for a variety of commercially important fish species, but assessing fish communities in these habitats is costly and time-intensive. Here, we leverage eDNA metabarcoding to characterize nearshore fish communities near Juneau, Alaska, USA, a high-latitude environment with large tidal swings, strong currents, and significant freshwater input. We investigated whether species richness and community composition differed across three habitat types (sand beaches, eelgrass beds, and rocky shorelines) and between high and low tides. Additionally, we tested whether replication of field samples and PCR reactions influenced either species richness or composition. We amplified a 12S mitochondrial locus in our samples and identified 188 fish amplicon sequence variants (ASVs), corresponding to 21 unique taxa, with approximately half of these resolved to single species. Species richness and composition inferred from eDNA differed substantially among habitats, with rock habitats containing fewer taxa and fewer overall detections than sand and eelgrass habitats. The effect of tide was more subtle and suggested a habitat-tide interaction, with differences in taxa between tides largely isolated to sand habitats. Power analyses indicated that additional field sampling is useful to detect subtle changes in species richness such as those due to tide. PCR replicates typically identified a small number of additional taxa. The most notable result from our study was that shore morphology appeared to substantially influence community structure. Rocky shorelines sloped quickly into deep water, while sand and eelgrass habitats descended much more gradually. We hypothesize that differences in taxa observed among habitats were largely due to lack of mixing between bottom and surface water, providing further evidence that eDNA transport is minimal and that many marine eDNA detections are derived from highly localized sampling locations. We suggest that future studies could explore the extent to which habitat and nearshore physical processes influence eDNA detections.

genomics↗

Gene flow influences the genomic architecture of local adaptation in six riverine fish species

Understanding how gene flow influences adaptive divergence is important for predicting adaptive responses. Theoretical studies suggest that when gene flow is high, clustering of adaptive genes in fewer genomic regions would protect adaptive alleles from among-population recombination and thus be selected for, but few studies have tested this hypothesis with empirical data. Here, we used RADseq to generate genomic data for six fish species with contrasting life histories from six reaches of the Upper Mississippi River System, USA. We then conducted genome scans for genomic islands of divergence to examine the distribution of adaptive loci and investigated whether these loci were found in inversions. We found that gene flow varied among species, and adaptive loci were clustered more tightly in species with higher gene flow. For example, the two species with the highest overall FST (0.03 - 0.07) and therefore lowest gene flow showed little evidence of clusters of adaptive loci, with adaptive loci spread uniformly across the genome. In contrast, nearly all adaptive loci in the species with the lowest FST (0.0004) were found in a single large putative inversion. Two other species with intermediate gene flow (FST ~ 0.004) also showed clustered genomic architectures, with most islands of divergence clustered on a few chromosomes. These results provide important empirical evidence to support the hypothesis that increasingly clustered architectures of local adaptation are associated with high gene flow. Our study utilized a unique system with species spanning a large gradient of life histories to highlight the importance of gene flow in shaping adaptive divergence.

evolutionary biology↗