DOI: 10.5061/dryad.c2fqz61ck
title: Biodiversity, biogeography, and connectivity of polychaetes in the world's largest marine minerals exploration frontier

description: The abyssal Clarion-Clipperton Zone (CCZ), Pacific Ocean, is an area of
 commercial importance owing to the growing interest in mining high-grade
 polymetallic nodules at the seafloor for battery metals. Research into the
 spatial patterns of faunal diversity, composition, and population
 connectivity is needed to better understand the ecological impacts of
 potential resource extraction. Here, a DNA taxonomy approach is used to
 investigate regional-scale patterns of taxonomic and phylogenetic alpha
 and beta diversity, and genetic connectivity, of the dominant macrofaunal
 group (annelids) across a 6 million km2 region of the abyssal seafloor. We
 used a combination of new and published barcode data to study 1866
 polychaete specimens using molecular species delimitation. Both
 phylogenetic and taxonomic alpha and beta diversity metrics were used to
 analyse spatial patterns of biodiversity. Connectivity analyses were based
 on haplotype distributions for a subset of the studied taxa. DNA taxonomy
 identified 291–314 polychaete species from the COI and 16S datasets
 respectively. Taxonomic and phylogenetic beta diversity between sites were
 relatively high and mostly explained by lineage turnover. Over half of
 pairwise comparisons were more phylogenetically distinct than expected
 based on their taxonomic diversity. Connectivity analyses in abundant,
 broadly distributed taxa suggest an absence of genetic structuring driven
 by geographical location. Species diversity in abyssal Pacific polychaetes
 is high relative to other deep-sea regions. Results suggest that
 environmental filtering, where the environment selects against certain
 species, may play a significant role in regulating spatial patterns of
 biodiversity in the CCZ. A core group of widespread species have diverse
 haplotypes but are well connected over broad distances. Our data suggest
 that the high environmental and faunal heterogeneity of the CCZ should be
 considered in policy decisions such as designating protected areas.
description: Complete description of the DNA taxonomy pipeline used in the
 collection of samples new to this study is provided in Glover et al.
 (2016). Abyssal benthic specimens were collected from UK-1, OMS, and
 APEI-6 using a variety of oceanographic sampling gear including box cores,
 epibenthic sledges (EBS), remotely operated vehicle (ROV), and
 multi-cores. Live-sorted specimens were stored in individual microtube
 vials containing an aqueous solution of 80% non-denatured ethanol,
 numbered, barcoded into a database, and kept chilled until return to the
 Natural History Museum, London, UK. Extraction of DNA
 was done with DNeasy Blood and Tissue Kit (Qiagen) using a Hamilton
 Microlab STAR Robotic Workstation. Approximately 450 bp of 16S, and 650 bp
 of cytochrome c oxidase subunit I (COI) were amplified using primers
 listed in Table S1. PCR mixtures contained 1 μl of each primer (10 μM), 2
 μl template DNA and 21 μl of Red Taq DNA Polymerase 1.1X MasterMix (VWR)
 in a mixture of a total of 25 μl. The PCR amplification profile consisted
 of initial denaturation at 95 °C for 5 min, 35 cycles of denaturation at
 94 °C for 45 s, annealing at 55 °C for 45 s, extension at 72 °C for 2 min,
 and a final extension at 72 °C for 10 min. PCR products were purified
 using Millipore Multiscreen 96-well PCR Purification System, and
 sequencing was performed on an ABI 3730XL DNA Analyser (Applied
 Biosystems) at The Natural History Museum Sequencing Facility, using the
 same primers as in the PCR reactions. Overlapping sequence fragments were
 merged into consensus sequences using Geneious (Kearse et al.,
 2012). Sequences of the mitochondrial 16S rRNA (16S)
 and cytochrome c oxidase subunit I (COI) genetic markers were supplemented
 with sequences from Wiklund et al. (2019), Drennan et al. (2021), Glover
 et al. (in press), Neal et al. (2022a), Neal et al. (2022b), Janssen et
 al. (2015), Janssen et al. (2019), Bonifácio et al. (2020), and Bonifácio
 et al. (2021a,b) available through NCBI GenBank (Altschul et al., 1990)
 (https://www.ncbi.nlm.nih.gov/genbank/) and BOLD
 (https://www.boldsystems.org). Full 16S and COI sequence alignments used
 in analyses can be found in Appendix S2 and S3. Genetic data from a total
 of 1866 specimens were included in diversity analyses, with 1177 specimens
 having COI sequences, and 1101 specimens having 16S sequences.
 All sequence identities, including published ones, were confirmed
 using NCBI BLASTn (Altschul et al., 1990) to check for contamination
 before any analyses. COI sequences were translated into amino acids and
 checked for stop codons to avoid pseudogenes utilising MEGA X (Stecher et
 al., 2020). 16S and COI genes were aligned separately using MAFFT v.7
 (Katoh & Standley, 2013) and MUSCLE (Edgar, 2004) respectively
 using default settings. Alignments were further manually edited and
 clipped in MEGA X. Minimum length coverage was 508 base-pairs for COI and
 298 base-pairs for 16S. Best-fit partitions for each
 alignment and amino acid substitution models for COI were inferred using
 PartitionFinder 2.0 (Lanfear et al., 2017), utilising a greedy clustering
 algorithm (Lanfear et al., 2012), and PhyML v.3 (Guindon et al., 2010).
 The optimal evolutionary model for both 16S and all codon positions for
 COI was identified as the General Time Reversible model with corrections
 for invariant characters and gamma-distributed rate heterogeneity (GTR + I
 + G). Four outgroups were chosen based on those utilised in annelid
 phylogenies by (Rousset et al., 2007). BEAST v2.6.2
 (Bouckaert et al., 2019) was used to infer individual Bayesian ultrametric
 phylogenies for the 16S and COI datasets. Each Bayesian analysis was run
 for 100,000,000 generations, sampling every 100,000 generations using the
 optimal evolutionary model, Yule speciation model, and an uncorrelated
 relaxed clock. Trace plots of Markov Chain Monte Carlo (MCMC) runs were
 visually inspected in Tracer v.1.7.1 to assess stationarity and
 appropriate burn-in. After the likelihood of the trees of each chain
 converged, the first 50,000,000 states were discarded as
 burn-in.