Articles | Volume 15, issue 9
https://doi.org/10.5194/essd-15-3931-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-3931-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
05 Sep 2023
Data description paper |
| 05 Sep 2023
| 05 Sep 2023
An atlas of seabed biodiversity for Aotearoa New Zealand
Fabrice Stephenson
CORRESPONDING AUTHOR
School of Science, University of Waikato, Hamilton, New Zealand
Tom Brough
National Institute of Water and Atmospheric Research (NIWA), Dunedin, New
Zealand
Drew Lohrer
National Institute of Water and Atmospheric Research (NIWA), Hamilton, New
Zealand
Daniel Leduc
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
Shane Geange
New Zealand Department of Conservation, Wellington, New Zealand
Owen Anderson
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
David Bowden
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
Malcolm R. Clark
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
Niki Davey
National Institute of Water and Atmospheric Research (NIWA), Nelson, New
Zealand
Enrique Pardo
New Zealand Department of Conservation, Wellington, New Zealand
Dennis P. Gordon
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
Brittany Finucci
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
Michelle Kelly
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
Diana Macpherson
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
Lisa McCartain
National Institute of Water and Atmospheric Research (NIWA), Hamilton, New
Zealand
Sadie Mills
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
Kate Neill
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
Wendy Nelson
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
Rachael Peart
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
Matthew H. Pinkerton
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
Geoffrey B. Read
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
Jodie Robertson
New Zealand Department of Conservation, Wellington, New Zealand
Ashley Rowden
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand
Kareen Schnabel
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
Andrew Stewart
Museum of New Zealand Te Papa Tongarewa, Wellington, New Zealand
Carl Struthers
Museum of New Zealand Te Papa Tongarewa, Wellington, New Zealand
Leigh Tait
National Institute of Water and Atmospheric Research (NIWA), Christchurch,
New Zealand
School of Biological Sciences, University of Canterbury, Christchurch, New Zealand
Di Tracey
National Institute of Water and Atmospheric Research (NIWA), Wellington,
New Zealand
School of Biological Sciences, Victoria University of Wellington, Wellington, New Zealand
Shaun Weston
New Zealand Department of Conservation, Wellington, New Zealand
Carolyn Lundquist
National Institute of Water and Atmospheric Research (NIWA), Hamilton, New
Zealand
School of Environment, University of Auckland, Auckland, New Zealand
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Katharine T. Bigham, Ashley A. Rowden, Daniel Leduc, and David A. Bowden
Biogeosciences, 18, 1893–1908, https://doi.org/10.5194/bg-18-1893-2021, https://doi.org/10.5194/bg-18-1893-2021, 2021
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Turbidity flows – underwater avalanches – are large-scale physical disturbances believed to have profound impacts on productivity and diversity of benthic communities in the deep sea. We reviewed published studies and found that current evidence for changes in productivity is ambiguous at best, but the influence on regional and local diversity is clearer. We suggest study design criteria that may lead to a better understanding of large-scale disturbance effects on deep-sea benthos.
Irawan Asaad, Carolyn J. Lundquist, Mark V. Erdmann, and Mark J. Costello
Earth Syst. Sci. Data, 11, 163–174, https://doi.org/10.5194/essd-11-163-2019, https://doi.org/10.5194/essd-11-163-2019, 2019
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This atlas is a compendium of geospatial online and open-access data describing biodiversity conservation in the Coral Triangle of the Indo-Pacific biogeographic realm. It consists of three sets of interlinked digital maps: (1) biodiversity features; (2) areas of importance for biodiversity conservation; and (3) recommended priorities for Marine Protected Area (MPA) Network Expansion. These maps provide the most comprehensive biodiversity datasets available to date for the region.
P. Piazza, V. Cummings, D. Lohrer, S. Marini, P. Marriott, F. Menna, E. Nocerino, A. Peirano, and S. Schiaparelli
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 885–892, https://doi.org/10.5194/isprs-archives-XLII-2-885-2018, https://doi.org/10.5194/isprs-archives-XLII-2-885-2018, 2018
Related subject area
Domain: ESSD – Ocean | Subject: Biological oceanography
MAREL Carnot data and metadata from the Coriolis data center
Bio-optical properties of the cyanobacterium Nodularia spumigena
A synthetic optical database generated by radiative transfer simulations in support of studies in ocean optics and optical remote sensing of the global ocean
The Coastal Surveillance Through Observation of Ocean Color (COASTℓOOC) dataset
HIPPO environmental monitoring: impact of phytoplankton dynamics on water column chemistry and the sclerochronology of the king scallop (Pecten maximus) as a biogenic archive for past primary production reconstructions
AlgaeTraits: a trait database for (European) seaweeds
A new global oceanic multi-model net primary productivity data product
How to learn more about hydrological conditions and phytoplankton dynamics and diversity in the eastern English Channel and the Southern Bight of the North Sea: the Suivi Régional des Nutriments data set (1992–2021)
Deepwater red shrimp fishery in the eastern–central Mediterranean Sea: AIS-observed monthly fishing effort and frequency over 4 years
Global dataset on seagrass meadow structure, biomass and production
The Green Edge cruise: investigating the marginal ice zone processes during late spring and early summer to understand the fate of the Arctic phytoplankton bloom
A global marine particle size distribution dataset obtained with the Underwater Vision Profiler 5
The COSMUS expedition: seafloor images and acoustic bathymetric data from the PS124 expedition to the southern Weddell Sea, Antarctica
Raed Halawi Ghosn, Émilie Poisson-Caillault, Guillaume Charria, Armel Bonnat, Michel Repecaud, Jean-Valery Facq, Loïc Quéméner, Vincent Duquesne, Camille Blondel, and Alain Lefebvre
Earth Syst. Sci. Data, 15, 4205–4218, https://doi.org/10.5194/essd-15-4205-2023, https://doi.org/10.5194/essd-15-4205-2023, 2023
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This article describes a long-term (2004–2022) dataset from an in situ instrumented station located in the eastern English Channel and belonging to the COAST-HF network (ILICO). It provides high temporal resolution (sub-hourly) oceanographic and meteorological measurements. The MAREL Carnot dataset can be used to conduct research in marine ecology, oceanography, and data science. It was utilized to characterize recurrent, rare, and extreme events in the coastal area.
Shungudzemwoyo P. Garaba, Michelle Albinus, Guido Bonthond, Sabine Flöder, Mario L. M. Miranda, Sven Rohde, Joanne Y. L. Yong, and Jochen Wollschläger
Earth Syst. Sci. Data, 15, 4163–4179, https://doi.org/10.5194/essd-15-4163-2023, https://doi.org/10.5194/essd-15-4163-2023, 2023
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These high-quality data document a harmful algal bloom dominated by Nodularia spumigena, a cyanobacterium that has been recurring in waters around the world, using advanced water observation technologies. We also showcase the benefits of experiments of opportunity and the issues with obtaining synoptic spatio-temporal data for monitoring water quality. The dataset can be leveraged to gain more knowledge on related blooms, develop detection algorithms and optimize future monitoring efforts.
Hubert Loisel, Daniel Schaffer Ferreira Jorge, Rick A. Reynolds, and Dariusz Stramski
Earth Syst. Sci. Data, 15, 3711–3731, https://doi.org/10.5194/essd-15-3711-2023, https://doi.org/10.5194/essd-15-3711-2023, 2023
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Studies of light fields in aquatic environments require data from radiative transfer simulations that are free of measurement errors. In contrast to previously published synthetic optical databases, the present database was created by simulations covering a broad range of seawater optical properties that exhibit probability distributions consistent with a global ocean dominated by open-ocean pelagic environments. This database is intended to support ocean color science and applications.
Philippe Massicotte, Marcel Babin, Frank Fell, Vincent Fournier-Sicre, and David Doxaran
Earth Syst. Sci. Data, 15, 3529–3545, https://doi.org/10.5194/essd-15-3529-2023, https://doi.org/10.5194/essd-15-3529-2023, 2023
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The COASTlOOC oceanographic expeditions in 1997 and 1998 studied the relationship between seawater properties and biology and chemistry across the European coasts. The team collected data from 379 stations using ships and helicopters to support the development of ocean color remote-sensing algorithms. This unique and consistent dataset is still used today by researchers.
Valentin Siebert, Brivaëla Moriceau, Lukas Fröhlich, Bernd R. Schöne, Erwan Amice, Beatriz Beker, Kevin Bihannic, Isabelle Bihannic, Gaspard Delebecq, Jérémy Devesa, Morgane Gallinari, Yoan Germain, Émilie Grossteffan, Klaus Peter Jochum, Thierry Le Bec, Manon Le Goff, Céline Liorzou, Aude Leynaert, Claudie Marec, Marc Picheral, Peggy Rimmelin-Maury, Marie-Laure Rouget, Matthieu Waeles, and Julien Thébault
Earth Syst. Sci. Data, 15, 3263–3281, https://doi.org/10.5194/essd-15-3263-2023, https://doi.org/10.5194/essd-15-3263-2023, 2023
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This article presents an overview of the results of biological, chemical and physical parameters measured at high temporal resolution (sampling once and twice per week) during environmental monitoring that took place in 2021 in the Bay of Brest. We strongly believe that this dataset could be very useful for other scientists performing sclerochronological investigations, studying biogeochemical cycles or conducting various ecological research projects.
Sofie Vranken, Marine Robuchon, Stefanie Dekeyzer, Ignacio Bárbara, Inka Bartsch, Aurélie Blanfuné, Charles-François Boudouresque, Wim Decock, Christophe Destombe, Bruno de Reviers, Pilar Díaz-Tapia, Anne Herbst, Romain Julliard, Rolf Karez, Priit Kersen, Stacy A. Krueger-Hadfield, Ralph Kuhlenkamp, Akira F. Peters, Viviana Peña, Cristina Piñeiro-Corbeira, Fabio Rindi, Florence Rousseau, Jan Rueness, Hendrik Schubert, Kjersti Sjøtun, Marta Sansón, Dan Smale, Thierry Thibaut, Myriam Valero, Leen Vandepitte, Bart Vanhoorne, Alba Vergés, Marc Verlaque, Christophe Vieira, Line Le Gall, Frederik Leliaert, and Olivier De Clerck
Earth Syst. Sci. Data, 15, 2711–2754, https://doi.org/10.5194/essd-15-2711-2023, https://doi.org/10.5194/essd-15-2711-2023, 2023
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We present AlgaeTraits, a high-quality seaweed trait database. The data are structured within the framework of WoRMS and are supported by an expert editor community. With 45 175 trait records for 21 prioritised biological and ecological traits, and a taxonomic coverage of 1 745 European species, AlgaeTraits significantly advances previous efforts to provide standardised seaweed trait data. AlgaeTraits will serve as a foundation for future research on diversity and evolution of seaweeds.
Thomas James Ryan-Keogh, Sandy Jane Thomalla, Nicolette Chang, and Tumelo Moalusi
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-244, https://doi.org/10.5194/essd-2023-244, 2023
Revised manuscript accepted for ESSD
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Oceanic productivity has been highlighted as an important environmental indicator of climate change in comparison to other existing metrics. However, the availability of this data to assess trends and trajectories is plagued with issues, such as application to only a single satellite reducing the time period for assessment. We have applied multiple algorithms to the longest ocean colour record to provide a record for assessing climate change driven trends.
Alain Lefebvre and David Devreker
Earth Syst. Sci. Data, 15, 1077–1092, https://doi.org/10.5194/essd-15-1077-2023, https://doi.org/10.5194/essd-15-1077-2023, 2023
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The Suivi Regional des Nutriments (SRN) data set includes long-term time series on marine phytoplankton and physicochemical measures in the eastern English Channel and the Southern Bight of the North Sea. These data sets should be useful for comparing contrasted coastal marine ecosystems to further knowledge about the direct and indirect effects of human pressures and environmental changes on ecosystem structure and function, including eutrophication and harmful algal bloom issues.
Jacopo Pulcinella, Enrico Nicola Armelloni, Carmen Ferrà, Giuseppe Scarcella, and Anna Nora Tassetti
Earth Syst. Sci. Data, 15, 809–820, https://doi.org/10.5194/essd-15-809-2023, https://doi.org/10.5194/essd-15-809-2023, 2023
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Deep-sea fishery in the Mediterranean Sea was historically driven by the commercial profitability of deepwater red shrimps. Understanding spatiotemporal dynamics of fishing is key to comprehensively evaluate the status of these resources and prevent stock collapse. The observed monthly fishing effort and frequency dataset released by the automatic identification system (AIS) may help researchers as well as those involved in fishery management and in the update of existing management plans.
Simone Strydom, Roisin McCallum, Anna Lafratta, Chanelle L. Webster, Caitlyn M. O'Dea, Nicole E. Said, Natasha Dunham, Karina Inostroza, Cristian Salinas, Samuel Billinghurst, Charlie M. Phelps, Connor Campbell, Connor Gorham, Rachele Bernasconi, Anna M. Frouws, Axel Werner, Federico Vitelli, Viena Puigcorbé, Alexandra D'Cruz, Kathryn M. McMahon, Jack Robinson, Megan J. Huggett, Sian McNamara, Glenn A. Hyndes, and Oscar Serrano
Earth Syst. Sci. Data, 15, 511–519, https://doi.org/10.5194/essd-15-511-2023, https://doi.org/10.5194/essd-15-511-2023, 2023
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Seagrasses are important underwater plants that provide valuable ecosystem services to humans, including mitigating climate change. Understanding the natural history of seagrass meadows across different types of environments is crucial to conserving seagrasses in the global ocean. This dataset contains data extracted from peer-reviewed publications and highlights which seagrasses have been studied and in which locations and is useful for pointing out which need further investigation.
Flavienne Bruyant, Rémi Amiraux, Marie-Pier Amyot, Philippe Archambault, Lise Artigue, Lucas Barbedo de Freitas, Guislain Bécu, Simon Bélanger, Pascaline Bourgain, Annick Bricaud, Etienne Brouard, Camille Brunet, Tonya Burgers, Danielle Caleb, Katrine Chalut, Hervé Claustre, Véronique Cornet-Barthaux, Pierre Coupel, Marine Cusa, Fanny Cusset, Laeticia Dadaglio, Marty Davelaar, Gabrièle Deslongchamps, Céline Dimier, Julie Dinasquet, Dany Dumont, Brent Else, Igor Eulaers, Joannie Ferland, Gabrielle Filteau, Marie-Hélène Forget, Jérome Fort, Louis Fortier, Martí Galí, Morgane Gallinari, Svend-Erik Garbus, Nicole Garcia, Catherine Gérikas Ribeiro, Colline Gombault, Priscilla Gourvil, Clémence Goyens, Cindy Grant, Pierre-Luc Grondin, Pascal Guillot, Sandrine Hillion, Rachel Hussherr, Fabien Joux, Hannah Joy-Warren, Gabriel Joyal, David Kieber, Augustin Lafond, José Lagunas, Patrick Lajeunesse, Catherine Lalande, Jade Larivière, Florence Le Gall, Karine Leblanc, Mathieu Leblanc, Justine Legras, Keith Lévesque, Kate-M. Lewis, Edouard Leymarie, Aude Leynaert, Thomas Linkowski, Martine Lizotte, Adriana Lopes dos Santos, Claudie Marec, Dominique Marie, Guillaume Massé, Philippe Massicotte, Atsushi Matsuoka, Lisa A. Miller, Sharif Mirshak, Nathalie Morata, Brivaela Moriceau, Philippe-Israël Morin, Simon Morisset, Anders Mosbech, Alfonso Mucci, Gabrielle Nadaï, Christian Nozais, Ingrid Obernosterer, Thimoté Paire, Christos Panagiotopoulos, Marie Parenteau, Noémie Pelletier, Marc Picheral, Bernard Quéguiner, Patrick Raimbault, Joséphine Ras, Eric Rehm, Llúcia Ribot Lacosta, Jean-François Rontani, Blanche Saint-Béat, Julie Sansoulet, Noé Sardet, Catherine Schmechtig, Antoine Sciandra, Richard Sempéré, Caroline Sévigny, Jordan Toullec, Margot Tragin, Jean-Éric Tremblay, Annie-Pier Trottier, Daniel Vaulot, Anda Vladoiu, Lei Xue, Gustavo Yunda-Guarin, and Marcel Babin
Earth Syst. Sci. Data, 14, 4607–4642, https://doi.org/10.5194/essd-14-4607-2022, https://doi.org/10.5194/essd-14-4607-2022, 2022
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This paper presents a dataset acquired during a research cruise held in Baffin Bay in 2016. We observed that the disappearance of sea ice in the Arctic Ocean increases both the length and spatial extent of the phytoplankton growth season. In the future, this will impact the food webs on which the local populations depend for their food supply and fisheries. This dataset will provide insight into quantifying these impacts and help the decision-making process for policymakers.
Rainer Kiko, Marc Picheral, David Antoine, Marcel Babin, Léo Berline, Tristan Biard, Emmanuel Boss, Peter Brandt, Francois Carlotti, Svenja Christiansen, Laurent Coppola, Leandro de la Cruz, Emilie Diamond-Riquier, Xavier Durrieu de Madron, Amanda Elineau, Gabriel Gorsky, Lionel Guidi, Helena Hauss, Jean-Olivier Irisson, Lee Karp-Boss, Johannes Karstensen, Dong-gyun Kim, Rachel M. Lekanoff, Fabien Lombard, Rubens M. Lopes, Claudie Marec, Andrew M. P. McDonnell, Daniela Niemeyer, Margaux Noyon, Stephanie H. O'Daly, Mark D. Ohman, Jessica L. Pretty, Andreas Rogge, Sarah Searson, Masashi Shibata, Yuji Tanaka, Toste Tanhua, Jan Taucher, Emilia Trudnowska, Jessica S. Turner, Anya Waite, and Lars Stemmann
Earth Syst. Sci. Data, 14, 4315–4337, https://doi.org/10.5194/essd-14-4315-2022, https://doi.org/10.5194/essd-14-4315-2022, 2022
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The term
marine particlescomprises detrital aggregates; fecal pellets; bacterioplankton, phytoplankton and zooplankton; and even fish. Here, we present a global dataset that contains 8805 vertical particle size distribution profiles obtained with Underwater Vision Profiler 5 (UVP5) camera systems. These data are valuable to the scientific community, as they can be used to constrain important biogeochemical processes in the ocean, such as the flux of carbon to the deep sea.
Autun Purser, Laura Hehemann, Lilian Boehringer, Ellen Werner, Santiago E. A. Pineda-Metz, Lucie Vignes, Axel Nordhausen, Moritz Holtappels, and Frank Wenzhoefer
Earth Syst. Sci. Data, 14, 3635–3648, https://doi.org/10.5194/essd-14-3635-2022, https://doi.org/10.5194/essd-14-3635-2022, 2022
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Within this paper we present the seafloor images, maps and acoustic camera data collected by a towed underwater research platform deployed in 20 locations across the eastern Weddell Sea, Antarctica, during the PS124 COSMUS expedition with the research icebreaker RV Polarstern in 2021. The 20 deployments highlight the great variability in seafloor structure and faunal communities present. Of key interest was the discovery of the largest fish nesting colony discovered globally to date.
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Short summary
Understanding the distribution of species that live at the seafloor is critical to the management of the marine environment but is lacking in many areas. Here, we showcase an atlas of seafloor biodiversity that describes the distribution of approximately 600 organisms throughout New Zealand’s vast marine realm. Each layer in the open-access atlas has been evaluated by leading experts and provides a key resource for the sustainable use of New Zealand's marine environment.
Understanding the distribution of species that live at the seafloor is critical to the...
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