Blue mussels of the genus Mytilus are important ecosystem engineers in intertidal and subtidal communities. The distribution of Mytilus mussels is influenced by a number of benthic and pelagic environmental variables (e.g., substratum type and availability, water movement, phytoplankton production, physical disturbance) as well as interactions between these variables. Because of its broad tolerance of environmental variation the Mediterranean species, Mytilus galloprovincialis, has the greatest ability of all blue mussels to colonise new geographic regions. Understanding how population genetic variation is related to, or caused by, environmental variation is important but has long been a challenge. The present study examined the genetic differentiation of native populations of M. galloprovincialis throughout its entire geographic range in the Mediterranean Sea, the Black Sea and the Sea of Azov using 53 single nucleotide polymorphisms (SNP loci). Mussels, in total 1004 individuals collected from 36 locations, were genotyped and combined with existing SNP data for mussels from 11 reference sites. Pairwise comparisons of F_ST values, correspondence analysis (CA) and STRUCTURE analysis all revealed four groups of populations: the Atlantic Ocean; the western Mediterranean; the Aegean Sea; and the Azov, Black and Marmara Seas. One population – from Algeria (Oran West) – was intermediate between the two main groups of the Mediterranean Sea and Atlantic Ocean. Seascape genetic analyses using GLM and DistLM analyses were employed to test site-specific genetic variation as a function of 13 environmental variables. The GLM identified five environmental variables that explained variation in site-specific F_ST values, whilst in the DistLM best-fit model only four were significant. These analyses suggest that a complex mix of environmental variables contribute to explaining genetic variation of M. galloprovincialis populations within the Mediterranean Sea, which most likely reflects the complex geological history of formation, isolation and reconnection among the regional sub-basins of the Sea.

The impacts and interactions between hatchery-bred fish and wild fish populations has been a topic of active investigation in recent decades. In some instances, the benefits of stocking can be overshadowed by negative effects such as genetic introgression with natural populations, loss of genetic diversity, and dilution of local adaptations. Methods that facilitate the identification of stocked fish enable us to estimate not only the effectiveness of stocking but also the level of natural reproduction and the degree of hybridization. The longest Baltic river, the Vistula, also has the second highest discharge. Historically, it hosted numerous populations of the anadromous form of brown trout (sea trout); however, dam construction has since interfered with and reduced spawning migration to a rate that is much lower than before. Reduced spawning has resulted in a population collapse and a negative flow-on effect on commercial catches. In response, Poland (along with many other Baltic countries) initiated an intensive stocking program which continues today and which sees the average annual release of 700,000 smolts. As a consequence, today’s main-river and inshore catches come from stock-enhanced populations. High-throughput single-nucleotide polymorphism (SNP) genotyping was performed on samples of sea trout from southern Baltic populations; results suggest that a significant portion of the sea trout catches in the Vistula mouth region have direct hatchery origin and indicate the presence of Pomeranian specimens. SNP loci identified as outliers indicate a potential selection pressure that may be related with effects of hatchery breeding and mixing with natural populations. The brown trout SNP array applied in this study showed high effectiveness not only for population differentiation, but more importantly, it emerged as a sensitive tool to provide evidence of detection selection.

Molecular methods such as DNA/eDNA metabarcoding have emerged as useful tools to document the biodiversity of complex communities over large spatio‐temporal scales. We established an international Marine Biodiversity Observation Network (ARMS‐MBON) combining standardised sampling using autonomous reef monitoring structures (ARMS) with metabarcoding for genetic monitoring of marine hard‐bottom benthic communities. Here, we present the data of our first sampling campaign comprising 56 ARMS units deployed in 2018–2019 and retrieved in 2018–2020 across 15 observatories along the coasts of Europe and adjacent regions. We describe the open‐access data set (image, genetic and metadata) and explore the genetic data to show its potential for marine biodiversity monitoring and ecological research. Our analysis shows that ARMS recovered more than 60 eukaryotic phyla capturing diversity of up to ~5500 amplicon sequence variants and ~1800 operational taxonomic units, and up to ~250 and ~50 species per observatory using the cytochrome c oxidase subunit I (COI) and 18S rRNA marker genes, respectively. Further, ARMS detected threatened, vulnerable and non‐indigenous species often targeted in biological monitoring. We show that while deployment duration does not drive diversity estimates, sampling effort and sequencing depth across observatories do. We recommend that ARMS should be deployed for at least 3–6 months during the main growth season to use resources as efficiently as possible and that post‐sequencing curation is applied to enable statistical comparison of spatio‐temporal entities. We suggest that ARMS should be used in biological monitoring programs and long‐term ecological research and encourage the adoption of our ARMS‐MBON protocols.

Understanding the origins of invasive species is necessary to manage them and predict their potential for spreading. The mussel genus Mytilus forms an important component of coastal ecosystems in the northern and southern hemispheres. M. galloprovincialis is an important invasive species globally, first appearing on the South African coast in the 1970s. Studies using nuclear and mitochondrial DNA indicated that the invasion probably originated from the north-east Atlantic. We used fifty-five polymorphic SNPs to genotype mussels from sites across the coast of South Africa with reference samples from the Mediterranean, the Atlantic, and New Zealand to test for possible introgression of the northern and southern taxa. Low levels of genetic differentiation were confirmed, and all samples grouped with reference samples of the Atlantic form of M. galloprovincialis, supporting previous studies. The SNP genotyping, however, allowed the detection of some individuals with genotypes typical of the Mediterranean, indicating that introduced populations in South Africa do not have a uniform origin. The initial population introduced to South Africa may have been genetically heterogenous from the start, coming from a region influenced by both the Atlantic and Mediterranean. Alternatively, multiple introductions may have taken place, originating from different regions, specifically North Africa, southern Europe, and the Mediterranean, building up the final heterogeneity.

Molecular methods such as DNA/eDNA metabarcoding have emerged as useful tools to document biodiversity of complex communities over large spatio-temporal scales. We established an international Marine Biodiversity Observation Network (ARMS-MBON) combining standardised sampling using autonomous reef monitoring structures (ARMS) with metabarcoding for genetic monitoring of marine hard-bottom benthic communities. Here, we present the data of our first sampling campaign comprising 56 ARMS units deployed in 2018-2019 and retrieved in 2018-2020 across 15 observatories along the coasts of Europe and adjacent regions. We describe the open-access data set (image, genetic, and metadata) and explore the genetic data to show its potential for marine biodiversity monitoring and ecological research. Our analysis shows that ARMS recovered more than 60 eukaryotic phyla capturing diversity of up to ∼5,500 amplicon sequence variants and ∼1,800 operational taxonomic units, and up to ∼250 and ∼50 species per observatory using the cytochrome c oxidase subunit I (COI) and 18S rRNA marker genes, respectively. Further, ARMS detected threatened, vulnerable and non-indigenous species often targeted in biological monitoring. We show that while deployment duration does not drive diversity estimates, sampling effort and sequencing depth across observatories do. We recommend that ARMS should be deployed for at least three to six months during the main growth season to use resources as efficiently as possible and that post-sequencing curation is applied to enable statistical comparison of spatio-temporal entities. We suggest that ARMS should be used in biological monitoring programmes and long-term ecological research and encourage the adoption of our ARMS-MBON protocols.

Molecular methods such as DNA/eDNA metabarcoding have emerged as useful tools to document biodiversity of complex communities over large spatio-temporal scales. We established an international Marine Biodiversity Observation Network (ARMS-MBON) combining standardised sampling using autonomous reef monitoring structures (ARMS) with metabarcoding for genetic monitoring of marine hard-bottom benthic communities. Here, we present the data of our first sampling campaign comprising 56 ARMS units deployed in 2018-2019 and retrieved in 2018-2020 across 15 observatories along the coasts of Europe and adjacent regions. We describe the open-access data set (image, genetic, and metadata) and explore the genetic data to show its potential for marine biodiversity monitoring and ecological research. Our analysis shows that ARMS recovered more than 60 eukaryotic phyla capturing diversity of up to ∼5,500 amplicon sequence variants and ∼1,800 operational taxonomic units, and up to ∼250 and ∼50 species per observatory using the cytochrome c oxidase subunit I (COI) and 18S rRNA marker genes, respectively. Further, ARMS detected threatened, vulnerable and non-indigenous species often targeted in biological monitoring. We show that while deployment duration does not drive diversity estimates, sampling effort and sequencing depth across observatories do. We recommend that ARMS should be deployed for at least three to six months during the main growth season to use resources as efficiently as possible and that post-sequencing curation is applied to enable statistical comparison of spatio-temporal entities. We suggest that ARMS should be used in biological monitoring programmes and long-term ecological research and encourage the adoption of our ARMS-MBON protocols.