ALBERT

Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Carroll, E. L., Ott, P. H., McMillan, L. F., Galletti Vernazzani, B., Neveceralova, P., Vermeulen, E., Gaggiotti, O. E., Andriolo, A., Baker, C. S., Bamford, C., Best, P., Cabrera, E., Calderan, S., Chirife, A., Fewster, R. M., Flores, P. A. C., Frasier, T., Freitas, T. R. O., Groch, K., Hulva, P., Kennedy, A., Leaper, R., Leslie, M. S., Moore, M., Oliveira, L., Seger, J., Stepien, E. N., Valenzuela, L. O., Zerbini, A., & Jackson, J. A. Genetic diversity and connectivity of southern right whales (Eubalaena australis) found in the Brazil and Chile-Peru wintering grounds and the South Georgia (Islas Georgias del Sur) feeding ground. Journal of Heredity, 111(3), (2020): 263-276, doi:10.1093/jhered/esaa010.

Description: As species recover from exploitation, continued assessments of connectivity and population structure are warranted to provide information for conservation and management. This is particularly true in species with high dispersal capacity, such as migratory whales, where patterns of connectivity could change rapidly. Here we build on a previous long-term, large-scale collaboration on southern right whales (Eubalaena australis) to combine new (nnew) and published (npub) mitochondrial (mtDNA) and microsatellite genetic data from all major wintering grounds and, uniquely, the South Georgia (Islas Georgias del Sur: SG) feeding grounds. Specifically, we include data from Argentina (npub mtDNA/microsatellite = 208/46), Brazil (nnew mtDNA/microsatellite = 50/50), South Africa (nnew mtDNA/microsatellite = 66/77, npub mtDNA/microsatellite = 350/47), Chile–Peru (nnew mtDNA/microsatellite = 1/1), the Indo-Pacific (npub mtDNA/microsatellite = 769/126), and SG (npub mtDNA/microsatellite = 8/0, nnew mtDNA/microsatellite = 3/11) to investigate the position of previously unstudied habitats in the migratory network: Brazil, SG, and Chile–Peru. These new genetic data show connectivity between Brazil and Argentina, exemplified by weak genetic differentiation and the movement of 1 genetically identified individual between the South American grounds. The single sample from Chile–Peru had an mtDNA haplotype previously only observed in the Indo-Pacific and had a nuclear genotype that appeared admixed between the Indo-Pacific and South Atlantic, based on genetic clustering and assignment algorithms. The SG samples were clearly South Atlantic and were more similar to the South American than the South African wintering grounds. This study highlights how international collaborations are critical to provide context for emerging or recovering regions, like the SG feeding ground, as well as those that remain critically endangered, such as Chile–Peru.

Description: This work was supported by the EU BEST 2.0 medium grant 1594 and UK DARWIN PLUS grant 057 and additional funding from the World Wildlife Fund GB107301. The collection of the Chile–Peru sample was supported by the Global Greengrants Fund and the Pacific Whale Foundation. The collection of the Brazilian samples was supported through grants by the Brazilian National Research Council to Paulo H. Ott (CNPq proc. n° 144064/98-7) and Paulo A.C. Flores (CNPq proc. n° 146609/1999-9) and with support from the World Wildlife Fund (WWF-Brazil). The collection of the South African samples was supported by the Global Greengrants Fund, the Pacific Whale Foundation and Charles University Grant Agency (1140217). E.L.C. was partially supported by a Rutherford Discovery Fellowship from the Royal Society of New Zealand. This study forms part of the Ecosystems component of the British Antarctic Survey Polar Sciences for Planet Earth Programme, funded by the Natural Environment Research Council.

Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Chapman, A. S. A., Beaulieu, S. E., Colaco, A., Gebruk, A. V., Hilario, A., Kihara, T. C., Ramirez-Llodra, E., Sarrazin, J., Tunnicliffe, V., Amon, D. J., Baker, M. C., Boschen-Rose, R. E., Chen, C., Cooper, I. J., Copley, J. T., Corbari, L., Cordes, E. E., Cuvelier, D., Duperron, S., Du Preez, C., Gollner, S., Horton, T., Hourdez, S., Krylova, E. M., Linse, K., LokaBharathi, P. A., Marsh, L., Matabos, M., Mills, S. W., Mullineaux, L. S., Rapp, H. T., Reid, W. D. K., Rybakova (Goroslavskaya), E., Thomas, T. R. A., Southgate, S. J., Stohr, S., Turner, P. J., Watanabe, H. K., Yasuhara, M., & Bates, A. E. sFDvent: a global trait database for deep-sea hydrothermal-vent fauna. Global Ecology and Biogeography, 28(11), (2019): 1538-1551, doi: 10.1111/geb.12975.

Description: Motivation Traits are increasingly being used to quantify global biodiversity patterns, with trait databases growing in size and number, across diverse taxa. Despite growing interest in a trait‐based approach to the biodiversity of the deep sea, where the impacts of human activities (including seabed mining) accelerate, there is no single repository for species traits for deep‐sea chemosynthesis‐based ecosystems, including hydrothermal vents. Using an international, collaborative approach, we have compiled the first global‐scale trait database for deep‐sea hydrothermal‐vent fauna – sFDvent (sDiv‐funded trait database for the Functional Diversity of vents). We formed a funded working group to select traits appropriate to: (a) capture the performance of vent species and their influence on ecosystem processes, and (b) compare trait‐based diversity in different ecosystems. Forty contributors, representing expertise across most known hydrothermal‐vent systems and taxa, scored species traits using online collaborative tools and shared workspaces. Here, we characterise the sFDvent database, describe our approach, and evaluate its scope. Finally, we compare the sFDvent database to similar databases from shallow‐marine and terrestrial ecosystems to highlight how the sFDvent database can inform cross‐ecosystem comparisons. We also make the sFDvent database publicly available online by assigning a persistent, unique DOI. Main types of variable contained Six hundred and forty‐six vent species names, associated location information (33 regions), and scores for 13 traits (in categories: community structure, generalist/specialist, geographic distribution, habitat use, life history, mobility, species associations, symbiont, and trophic structure). Contributor IDs, certainty scores, and references are also provided. Spatial location and grain Global coverage (grain size: ocean basin), spanning eight ocean basins, including vents on 12 mid‐ocean ridges and 6 back‐arc spreading centres. Time period and grain sFDvent includes information on deep‐sea vent species, and associated taxonomic updates, since they were first discovered in 1977. Time is not recorded. The database will be updated every 5 years. Major taxa and level of measurement Deep‐sea hydrothermal‐vent fauna with species‐level identification present or in progress. Software format .csv and MS Excel (.xlsx).

Description: We would like to thank the following experts, who are not authors on this publication but made contributions to the sFDvent database: Anna Metaxas, Alexander Mironov, Jianwen Qiu (seep species contributions, to be added to a future version of the database) and Anders Warén. We would also like to thank Robert Cooke for his advice, time, and assistance in processing the raw data contributions to the sFDvent database using R. Thanks also to members of iDiv and its synthesis centre – sDiv – for much‐valued advice, support, and assistance during working‐group meetings: Doreen Brückner, Jes Hines, Borja Jiménez‐Alfaro, Ingolf Kühn and Marten Winter. We would also like to thank the following supporters of the database who contributed indirectly via early design meetings or members of their research groups: Malcolm Clark, Charles Fisher, Adrian Glover, Ashley Rowden and Cindy Lee Van Dover. Finally, thanks to the families of sFDvent working group members for their support while they were participating in meetings at iDiv in Germany. Financial support for sFDvent working group meetings was gratefully received from sDiv, the Synthesis Centre of iDiv (DFG FZT 118). ASAC was a PhD candidate funded by the SPITFIRE Doctoral Training Partnership (supported by the Natural Environmental Research Council, grant number: NE/L002531/1) and the University of Southampton at the time of submission. ASAC also thanks Dominic, Lesley, Lettice and Simon Chapman for their support throughout this project. AEB and VT are sponsored through the Canada Research Chair Programme. SEB received support from National Science Foundation Division of Environmental Biology Award #1558904 and The Joint Initiative Awards Fund from the Andrew W. Mellon Foundation. AC is supported by Program Investigador (IF/00029/2014/CP1230/CT0002) from Fundação para a Ciência e a Tecnologia (FCT). This study also had the support of Fundação para a Ciência e a Tecnologia, through the strategic project UID/MAR/04292/2013 granted to marine environmental sciences centre. Data compiled by AVG and EG were supported by Russian science foundation Grant 14‐50‐00095. AH was supported by the grant BPD/UI88/5805/2017 awarded by CESAM (UID/AMB/50017), which is financed by FCT/Ministério da Educação through national funds and co‐funded by fundo Europeu de desenvolvimento regional, within the PT2020 Partnership Agreement and Compete 2020. ERLL was partially supported by the MarMine project (247626/O30). JS was supported by Ifremer. Data on vent fauna from the East Scotia Ridge, Mid‐Cayman Spreading Centre, and Southwest Indian Ridge were obtained by UK natural environment research council Grants NE/D01249X/1, NE/F017774/1 and NE/H012087/1, respectively. REBR's contribution was supported by a Postdoctoral Fellowship at the University of Victoria, funded by the Canadian Healthy Oceans Network II Strategic Research Program (CHONe II). DC is supported by a post‐doctoral scholarship (SFRH/BPD/110278/2015) from FCT. HTR was supported by the Research Council of Norway through project number 70184227 and the KG Jebsen Centre for Deep Sea Research (University of Bergen). MY was partially supported by grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (project codes: HKU 17306014, HKU 17311316).