There are presently four recognized species of clinid (kelpfish family: Clinidae) on the west coast of North America: Gibbonsia elegans, G. metzi, G. montereyensis, and Heterostichus rostratus. In addition, Clark L. Hubbs proposed an endemic subspecies in the genus Gibbonsia on Guadalupe Island. Later investigations using allozymes indicated low levels of genetic diversity between populations and treated subspecies names as synonyms, leading to the present-day status of three species in the genus. Here, we use high-throughput sequencing and a combination of nuclear and mitochondrial markers to revisit the systematics and population structure of the genus Gibbonsia. We find that Guadalupe Island specimens that are morphologically identified as G. elegans form a distinct genetic lineage for both nuclear and mitochondrial markers, supporting Hubbs's hypothesis of a Guadalupe Island endemic, Gibbonsia erroli. Further, we find that while dispersal potential is high for all species in the genus, genome-wide markers and outlier analyses show population structure at short geographic distances, suggesting fine scale environmental variation leading to local adaptation.

Pricklebacks (Family Stichaeidae) are generally cold-temperate fishes most commonly found in the north Pacific. As part of the California Conservation Genomics Project (CCGP), we sequenced the genome of the Monkeyface Prickleback, Cebidichthys violaceus, to establish a genomic model for understanding phylogeographic patterns of marine organisms in California. These patterns, in turn, may inform the design of marine protected areas using dispersal models based on forthcoming population genomic data. The genome of C. violaceus is typical of many marine fishes at less than 1 Gb (genome size = 575.6 Mb), and our assembly is near-chromosome level (contig N50 = 1 Mb, scaffold N50 = 16.4 Mb, BUSCO completeness = 93.2%). Within the context of the CCGP, the genome will be used as a reference for future whole genome resequencing projects, enhancing our knowledge of the population structure of the species and more generally, the efficacy of marine protected areas as a primary conservation tool across California's marine ecosystems.

Sculpins (Family Cottidae) are generally cold-temperate intertidal reef fishes most commonly found in the North Pacific. As part of the California Conservation Genomics Project (CCGP), we sequenced the genome of the Woolly Sculpin, Clinocottus analis, to establish a genomic model for understanding phylogeographic structure of inshore marine taxa along the California coast. These patterns, in turn, should further inform the design of marine protected areas using dispersal models based on genomic data. The small genome of C. analis is typical of marine fishes at less than 1 Gb (genome size = 538 Mb), and our assembly is near-chromosome level (contig N50 = 9.1 Mb, scaffold N50 = 21 Mb, BUSCO completeness = 97.9%). Within the context of the CCGP, the Woolly Sculpin genome will be used as a reference for future whole-genome resequencing projects aimed at enhancing our knowledge of the population structure of the species, and efficacy of marine protected areas across the state.

A common way of illustrating phylogeographic results is through the use of haplotype networks. While these networks help to visualize relationships between individuals, populations, and species, evolutionary studies often only quantitatively analyze genetic diversity among haplotypes and ignore other network properties. Here, we present a new metric, haplotype network branch diversity (HBd), as an easy way to quantifiably compare haplotype network complexity. Our metric builds off the logic of combining genetic and topological diversity to estimate complexity previously used by the published metric haplotype network diversity (HNd). However, unlike HNd which uses a combination of network features to produce complexity values that cannot be defined in probabilistic terms, thereby obscuring the values' implication for a sampled population, HBd uses frequencies of haplotype classes to incorporate topological information of networks, keeping the focus on the population and providing easy-to-interpret probabilistic values for randomly sampled individuals. The goal of this study is to introduce this more intuitive metric and provide an R script that allows researchers to calculate diversity and complexity indices from haplotype networks. A group of datasets, generated manually (model dataset) and based on published data (empirical dataset), were used to illustrate the behavior of HBd and both of its terms, haplotype diversity, and a new index called branch diversity. Results followed a predicted trend in both model and empirical datasets, from low metric values in simple networks to high values in complex networks. In short, the new combined metric joins genetic and topological diversity of haplotype networks, into a single complexity value. Based on our analysis, we recommend the use of HBd, as it makes direct comparisons of network complexity straightforward and provides probabilistic values that can readily discriminate situations that are difficult to resolve with available metrics.