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# Long-term changes in taxonomic and functional composition of European marine fish communities The GitHub linked repository is here: [European_demersal_fish_assemblages (](https://github.com/auroreRECE/European_demersal_fish_assemblages)DOI [10.5281/zenodo.11190119](https://zenodo.org/doi/10.5281/zenodo.11190119)) ## Overview This project is dedicated to studying the influence of environmental conditions and fishing on the functional and taxonomic structure of a demersal fish community in Europe. This GitHub repository provides the code of the Receveur et al. (2024) publication in Ecography. ## Data files description ### df\_MFA.csv This file contains the coordinates resulting from the Multiple Factor Analysis (MFA): * X : the row numbers ; * ID_unique : a unique ID number corresponding to the trawls ; * Dim.1 : the coordinate of each trawl on the first MFA dimension ; * Dim.2 : the coordinate of each trawl on the second MFA dimension ; * Dim.3 : the coordinate of each trawl on the third MFA dimension ; ### df\_PCA.csv This file contains the coordinates * X : the row numbers ; * ID_unique : a unique ID number corresponding to the trawls ; * Dim.1 : the coordinate of each trawl on the first PCA dimension ; * Dim.2 : the coordinate of each trawl on the second PCA dimension ; * Dim.3 : the coordinate of each trawl on the third PCA dimension ; ### df\_env.csv This file contains the following environmental parameters: * X : the row numbers ; * ID_unique : a unique ID number corresponding to the trawls ; * Year : the Year of each trawl ; * Quarter : the Quarter of each trawl ; * Ecoregion : the Ecoregion where each trawl has been done; * Survey : the name of the Survey ; * x_my_spatial_id : the longitude of the ICES rectangle where the trawl has been done ; * y_my_spatial_id : the latitude of the ICES rectangle where the trawl has been done ; * my_spatial_id : an ID for the ICES rectangle where the trawl has been done ; * depth : the bottom depth (meters) ; * depth_span : the bottom depth variability (maximum depth of the ICES cell - minimum depth) (meters) ; * chloro_mea: the mean chlorophyll-a concentration (mg/m³) ; * mlotst_mea : the mean mixed layer depth (meters) ; * oxy_bottom_mea : the mean bottom dissolved oxygen (umol/l) ; * oxy_surf_mea : the mean surface dissolved oxygen (umol/l) ; * temp_bottom_mea : the mean bottom temperature (°C) ; * temp_surf_mea : the mean surface temperature (°C) ; * curr_surf_mea : the mean surface current strength (m/s) ; * curr_bottom_mea : the mean bottom current strength (m/s) ; * sal_surf_mea : the mean surface salinity (PSU) ; * chloro_std : the standard deviation of chlorophyll-a concentration (mg/m³) ; * mlotst_std : the standard deviation of mixed layer depth (meters) ; * oxy_bottom_std : the standard deviation of bottom dissolved oxygen (umol/l) ; * oxy_surf_std : the standard deviation of surface dissolved oxygen (umol/l) ; * temp_bottom_std : the standard deviation of bottom temperature (°C) ; * temp_surf_std : the standard deviation of surface temperature (°C) ; * curr_surf_std : the standard deviation of surface current strength (m/s) ; * curr_bottom_std : the standard deviation of bottom current strength (m/s) ; * sal_surf_std : the standard deviation of surface salinity (PSU). ## Raw Data sources ### Biological data Trawls content is publicly available for the North East Atlantic (DATRAS database). Mediterranean data (MEDITS database) are available upon request to Maritime Affairs and Fisheries (MARE DATACOLLECTIONFRAMEWORK). The project uses the following surveys: | Survey Code | Survey name | Area | Period | References | | :---------- | :----------------------------------------------------- | :------------------------------------- | :-------: | :--------: | | BITS | Baltic International Trawl Survey | Baltic Sea | 1994-2019 | 4 | | BTS | Beam Trawl Survey | Celtic Sea; English Channel; North Sea | 1997-2019 | 7 | | BTS-VIII | Beam Trawl Survey – Bay of Biscay | Bay of Biscay | 2011-2019 | 7 | | DWS | Deepwater Survey | Irish Sea | 2006-2007 | 8 | | DYFS | Inshore Beam Trawl Survey | Southern North Sea | 2002-2019 | 7 | | EVHOE | French Southern Atlantic Bottom trawl Survey | Bay of Biscay and Celtic Sea | 2003-2019 | 1 | | FR-CGFS | French Channel ground Survey | English Channel | 1997-2019 | 2 | | IE-IAMS | Irish Anglerfish and megrim Survey | Scottish rockall and Irish Sea | 2016-2019 | 2 | | IE-IGFS | Irish Groundfish | Ireland Shelf Sea | 2003-2019 | 2 | | MEDITS | International bottom trawl survey in the Mediterranean | Mediterranean Sea | 1994-2018 | 9 | | NIGFS | Northern Ireland Groundfish Survey | Irish Sea | 2009-2019 | 2 | | NS-IBTS | North Sea International Bottom Trawl Survey | North Sea | 1997-2019 | 2 | | PT-IBTS | Portuguese International Bottom Trawl Survey | Portugal Shelf Sea | 2003-2017 | 2 | | ROCKALL | Scottish Rockall Survey (until 2010) | Rockall plateau | 2003-2009 | 2 | | SCOROC | Scottish Rockall Survey (from 2011) | Scottish plateau | 2011-2019 | 2 | | SCOWCGFS | Scottish West Coast Groundfish Survey | Scottish west coast | 2011-2019 | 2 | | SNS | Sole Net Survey | Southern North Sea | 2002-2019 | 7 | | SP-ARSA | Spanish Gulf of Cadiz Bottom Trawl Survey | Spain | 2003-2019 | 6 | | SP-NORTH | Spanish North Bottom Trawl Survey | North of Spain | 2003-2019 | 2 | | SP-PORC | Spanish Porcupine Bottom Trawl Survey | Irish Sea | 2003-2019 | 5 | | SWC-IBTS | Scottish West Coast International Bottom Trawl Survey | Scotland Shelf Sea | 1999-2010 | 2 | ### Trait data The complete traits data table is available upon request. It is a combination of the publicly available PANGAEA database, Fishbase information, and inference based on the FISHLIFE project. ### Environmental variables The data used are all publicly available on the Copernicus website. ### Fishing data The data used are all publicly available on the Global Fishing Watch website. ## Recommended Citation Please use the following citation: Receveur, A., Leprieur F., Ellingsen K., Keith D., Kleisner K., McLean M., Mérigot B., Mills K., Mouillot D., Rufino M., Trindade-Santos I., Van Hoey G., Albouy C., Auber A. Data for “Long-term changes in taxonomic and functional composition of European marine fish communities.” Dryad Digital Repository. (2024). doi.org/10.5061/dryad.x69p8czsj ## Acknowledgments This research is a product of the MAESTRO group funded by the synthesis center CESAB of the French Foundation for Research on Biodiversity (FRB). We thank France Filière Pêche (FFP) who founded the MAESTRO project. We also warmly thank all those who have contributed in any way to the scientific surveys and data collection/provision (European Institutions and scientists implicated in DATRAS-BTS, MEDITS, and DCF). ## References 1. ICES. The EVHOE survey (France). ICES Documents. (1997). Available at: https://archimer.ifremer.fr/doc/00036/14707/12013.pdf 2. ICES. Manual of the IBTS North Eastern Atlantic Surveys. Series of ICES Survey Protocols SISP 15 (2017). doi:10.17895/ices.pub.3519 3. ICES. Manual for the International Bottom Trawl Surveys Revision VIII. Series of ICES Survey Protocols SISP 10 - IBTS IX. (2015). 4. https://ices-library.figshare.com/articles/report/SISP_7_-*Manual_for_the_Baltic_International_Trawl_Surveys_BITS*/19050986 5. https://gis.ices.dk/geonetwork/srv/api/records/ce94a257-c8b3-44f7-9fd0-6bd7449ce073 6. http://ices.dk/sites/pub/CM%20Doccuments/2002/D/D0302A.pdf 7. https://ices-library.figshare.com/articles/report/SISP_14_-*Manual_for_the_Offshore_Beam_Trawl_Surveys_WGBEAM*/19051328 8. https://gis.ices.dk/geonetwork/srv/api/records/936b4fb7-9baa-4dbc-abd0-b1b7bda16406 9. https://archimer.ifremer.fr/doc/00117/22783/20585.pdf Evidence of large-scale biodiversity degradation in marine ecosystems has been reported worldwide, yet most research has focused on few species of interest or on limited spatiotemporal scales. Here we assessed the spatial and temporal changes in the taxonomic and functional composition of fish communities in European seas over the last 25 years (1994-2019). We then explored how these community changes were linked to environmental gradients and fishing pressure. We show that the spatial variation in fish species composition is more than two times higher than the temporal variation, with a marked spatial continuum in taxonomic composition and a more homogenous pattern in functional composition. The regions warming the fastest are experiencing an increasing dominance and total abundance of r-strategy fish species (lower age of maturity). Conversely, regions warming more slowly show an increasing dominance and total abundance of K-strategy species (high trophic level and late reproduction). Among the considered environmental variables, sea surface temperature, surface salinity, and chlorophyll-a most consistently influenced communities’ spatial patterns, while bottom temperature and oxygen had the most consistent influence on temporal patterns. Changes in communities’ functional composition were more closely related to environmental conditions than taxonomic changes. Our study demonstrates the importance of integrating community-level species traits across multi-decadal scales and across a large region to better capture and understand ecosystem-wide responses and provides a different lens on community dynamics that could be used to support sustainable fisheries management.

Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022). This version includes an update of heat storage of global ocean heat content, where one additional product (Li et al., 2022) had been included to the initial estimate. The Earth heat inventory had been updated accordingly, considering also the update for continental heat content (Cuesta-Valero et al., 2023).

This repository contains the data associated with the paper Tedersoo et al. (2022) Global patterns in endemicity and vulnerability of soil fungi // Global Change Biology. DOI:10.1111/gcb.16398 Fungi are highly diverse organisms and provide a wealth of ecosystem functions. However, distribution patterns and conservation needs of fungi have been very little explored compared to charismatic animals and plants. Here we assess endemicity patterns, global change vulnerability and conservation priority areas for functional groups of soil fungi based on six global surveys using a high-resolution, long-read metabarcoding approach. Endemicity of all fungi and most functional groups peaks in tropical habitats, including Amazonia, Yucatan, West-Central Africa, Sri Lanka and New Caledonia, with a negligible island effect compared with plants and animals. We also found that fungi are vulnerable mostly to drought, heat and land cover change, particularly in dry tropical regions with high human population density. Fungal conservation areas of highest priority include herbaceous wetlands, tropical forests and woodlands. We suggest that there should be more attention focused on the conservation of fungi, especially tropical root symbiotic arbuscular mycorrhizal and ectomycorrhizal fungi, unicellular early-diverging groups and macrofungi in general. Given the low overlap between endemicity of fungi and macroorganisms, but high matching in conservation needs, detailed analyses on distribution and conservation requirements are warranted for other microorganisms and soil organisms in general. This repository contains the following data associated with the publication: Supplementary tables S1 - S6 (`Tables_S1-S6.xlsx`): - Table S1. Definition of ecoregions and assignment of samples to ecoregions - Table S2. GSMc dataset used for endemicity analyses - Table S3. Dataset used for modeling endemicity values - Table S4. Dataset used for calculating and mapping vulnerability scores - Table S5. Dataset used for calculating and mapping conservation value - Table S6. Additional funding sources by authors OTU distribution by samples and ecoregions (`Data_taxon_assignment_to ecoregions.xlsx`) Gridded maps: Conservation priorities for all fungi and fungal groups - ConservationPriority_AllFungi.tif - ConservationPriority_AM.tif - ConservationPriority_EcM.tif - ConservationPriority_Moulds.tif - ConservationPriority_NonEcMAgaricomycetes.tif - ConservationPriority_OHPs.tif - ConservationPriority_Pathogens.tif - ConservationPriority_Unicellular.tif - ConservationPriority_Yeasts.tif The average vulnerability of all fungi and fungal groups and the model uncertainty estimates - AverageVulnerability_AllFungi.tif - AverageVulnerability_AM.tif - AverageVulnerability_EcM.tif - AverageVulnerability_Moulds.tif - AverageVulnerability_NonEcMAgaricomycetes.tif - AverageVulnerability_OHPs.tif - AverageVulnerability_Pathogens.tif - AverageVulnerabilityUncertainty_AllFungi.tif - AverageVulnerabilityUncertainty_AM.tif - AverageVulnerabilityUncertainty_EcM.tif - AverageVulnerabilityUncertainty_Moulds.tif - AverageVulnerabilityUncertainty_NonEcMAgaricomycetes.tif - AverageVulnerabilityUncertainty_OHPs.tif - AverageVulnerabilityUncertainty_Pathogens.tif - AverageVulnerabilityUncertainty_Unicellular.tif - AverageVulnerabilityUncertainty_Yeasts.tif - AverageVulnerability_Unicellular.tif - AverageVulnerability_Yeasts.tif The relative importance of predicted vulnerability of all fungi - RelativeImportanceOfVulnerability_AllFungi.tif Vulnerability to drought, heat, and land cover change for all fungi - Vulnerability_AllFungi_Heat-Drought-LandCoverChange.tif - VulnerabilityUncertainty_AllFungi_Heat-Drought-LandCoverChange.tif Human footprint index based on the Land-Use Harmonisation (LUH2; Hurtt et al., 2020, doi:10.5194/gmd-13-5425-2020) - `LandCoverChange_1960-2015.tif` MD5 checksums for all files (`MD5.md5`) Fungal groups: - AM, arbuscular mycorrhizal fungi (including all Glomeromycota but excluding all Endogonomycetes) - EcM, ectomycorrhizal fungi (excluding dubious lineages) - NonEcMAgaricomycetes, non-EcM Agaricomycetes (mostly saprotrophic fungi with usually macroscopic fruiting bodies) - Moulds (including Mortierellales, Mucorales, Umbelopsidales and Aspergillaceae and Trichocomaceae of Eurotiales and Trichoderma of Hypocreales) - Putative pathogens (including plant, animal and fungal pathogens as primary or secondary lifestyles) - OHPs, opportunistic human parasites (excluding Mortierellales) - Yeasts (excluding dimorphic yeasts) - Unicellular, other unicellular (non-yeast) fungi (including chytrids, aphids, rozellids and other early-diverging fungal lineages) Detailed processing steps can be found here: https://github.com/Mycology-Microbiology-Center/Fungal_Endemicity_and_Vulnerability This repository contains the data associated with the paper Tedersoo et al. (2022) Global patterns in endemicity and vulnerability of soil fungi // Global Change Biology. DOI:10.1111/gcb.16398 Fungi are highly diverse organisms and provide a wealth of ecosystem functions. However, distribution patterns and conservation needs of fungi have been very little explored compared to charismatic animals and plants. Here we assess endemicity patterns, global change vulnerability and conservation priority areas for functional groups of soil fungi based on six global surveys using a high-resolution, long-read metabarcoding approach. Endemicity of all fungi and most functional groups peaks in tropical habitats, including Amazonia, Yucatan, West-Central Africa, Sri Lanka and New Caledonia, with a negligible island effect compared with plants and animals. We also found that fungi are vulnerable mostly to drought, heat and land cover change, particularly in dry tropical regions with high human population density. Fungal conservation areas of highest priority include herbaceous wetlands, tropical forests and woodlands. We suggest that there should be more attention focused on the conservation of fungi, especially tropical root symbiotic arbuscular mycorrhizal and ectomycorrhizal fungi, unicellular early-diverging groups and macrofungi in general. Given the low overlap between endemicity of fungi and macroorganisms, but high matching in conservation needs, detailed analyses on distribution and conservation requirements are warranted for other microorganisms and soil organisms in general.

The global importance of mesopelagic fish is increasingly recognised, but they remain relatively poorly studied. This is particularly true in the Southern Ocean, where mesopelagic fishes are both key predators and prey, but where the remote environment makes sampling challenging. Despite this, multiple national Antarctic research programs have undertaken regional sampling of mesopelagic fish over several decades. However, data are dispersed, and sampling methodologies often differ precluding comparisons and limiting synthetic analyses. We identified potential data holders by compiling a metadata catalogue of existing survey data for Southern Ocean mesopelagic fishes. Data holders contributed 17,491 occurrence and 11,190 abundance records from 4780 net hauls from 72 different research cruises. Data span across 37 years from 1991 to 2019 and include trait-based information (length, weight, maturity). The final dataset underwent quality control processes and detailed metadata was provided for each sampling event. This dataset can be accessed through the Antarctic Biodiversity Portal. Myctobase will enhance research capacity by providing the broadscale baseline data necessary for observing and modelling mesopelagic fishes. The paper which this dataset refers to is available at https://doi.org/10.1038/s41597-022-01496-y. The original dataset as submitted for the paper is also available on Zenodo at https://doi.org/10.5281/zenodo.6131579. This dataset is published by SCAR-AntOBIS under the license CC-BY 4.0. We would appreciate it if you could follow the guidelines from the SCAR and IPY Data Policies (https://www.scar.org/excom-meetings/xxxi-scar-delegates-2010-buenos-aires-argentina/4563-scar-xxxi-ip04b-scar-data-policy/file/) when using the data. If you have any questions regarding this dataset, please do not hesitate to contact us via the contact information provided in the metadata or via data-biodiversity-aq@naturalsciences.be. Issues with dataset can be reported at https://github.com/biodiversity-aq/data-publication/ This dataset is part of the Belgian contribution to the EU-Lifewatch project funded by the Belgian Science Policy Office (BELSPO, contract n°FR/36/AN1/AntaBIS) .

Climate change and biodiversity loss are two of humanity’s greatest challenges. Blue carbon, i.e. the carbon captured and stored by marine living organisms and ecosystems, has the potential to help mitigate both challenges, because marine ecosystems that are important for sequestering carbon often also harbour rich biodiversity. Expanding and protecting Blue Carbon ecosystems has therefore been proposed as a Nature-based Solution to complement climate change mitigation efforts on land and to protect and restore marine biodiversity. In addition, securing and rebuilding Blue Carbon ecosystems can stabilise livelihoods, protect coasts, and support other societal needs such as food provision from the Ocean. However, the effectiveness of Blue Carbon ecosystems as a Nature-based Solution depends on the available space and ecosystem productivity, which can be impacted by climate change. Moreover, the overall carbon sequestration potential of Blue Carbon ecosystems is low and their contribution to climate stabilisation will only be significant once greenhouse gas emissions are strongly limited. Therefore, a drastic reduction of greenhouse gas emissions to keep global warming close to 1.5°C above pre-industrial levels is essential to maintain the health and long-term functionality of Blue Carbon ecosystems as a Nature-based Solution. This document describes examples and benefits of Blue Carbon ecosystems, and discusses uncertainties and challenges for the conservation and restoration of Blue Carbon ecosystems as a climate change solution. It also highlights the wider role of the Ocean in mitigating climate change through the carbon cycle, and closes with key research and management recommendations.

Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022).

Since the introduction of the sustainability challenge, scientists disagree over the interpretation of the term “sustainability.” Weak and strong sustainability are the two main interpretations of sustainability, which are opposing each other. Some researchers stated that the interpretation of the term depends on the context; others disagree pointing out that it always implies the meaning of continuation. The term “sustainability” can be used as attribute, which adds a certain characteristic to the noun. If something can be attributed as being sustainable, it can also be unsustainable. The sustainability challenge consists of shifting from the current unsustainable towards a sustainable system. This paper outlines that the weak sustainability term is illegitimate, as it leads to a contradiction with the acknowledged assumption that the current state is unsustainable. This contradiction is revealed through an analysis of the occurrence of decoupling in agriculture: Agricultural land use could be decoupled from agricultural production, but only with the trade-off of massive increases in fertilizer, pesticide, energy and water usage. This paper outlines an inherent inconsistency within the ongoing discussion about the interpretation of sustainability. Through identifying the invalidity of the weak sustainability interpretation the focus can be shifted form the discourse to the sustainability challenge itself.

"Be SURE - Be SUstainable REcommendations" The main goals and challenges for the Life Science (LS) communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large-scale data-driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable LS resources based on the collaborative, cross-disciplinary work done within the EOSC-Life (European Open Science Cloud for Life Sciences) consortium. Bringing together 13 European LS Research Infrastructures (RIs), it has laid the foundation for an open, digital space to support biological and medical research. Using lessons learned from 27 selected projects, we describe the organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the life sciences. We show how EOSC-Life provides a model for sustainable FAIR data management, including solutions for sensitive- and industry-related resources, by means of cross-disciplinary training and best practices sharing. Finally, we illustrate how data harmonisation and collaborative work facilitate interoperability of tools, data, solutions and lead to a better understanding of concepts, semantics and functionalities in the life sciences. IN PRESS EMBO Journal: https://www.embopress.org/journal/14602075 AVAILABLE SOON at : https://doi.org/10.15252/embj.2023115008  This research is mainly a product of the EOSC-Life European programme funding from the European Union's Horizon Europe research and innovation programme under grant agreement Nº824087. Complementary support was provided through EU funded project AgroServ (grant agreement Nº101058020), EU funded project BY-COVID (grant agreement Nº101046203), EU funded project DANUBIUS-IP (grant agreement Nº101079778), EU funded project EMPHASIS-GO (grant agreement Nº101079772), EU funded project FAIRplus (IMI grant agreement Nº802750), EU funded project FAIRsharing (Wellcome grant agreement Nº212930/Z/18/Z), EU funded project ISIDORe (grant agreement Nº101046133), EU funded project Precision Toxicology (grant agreement Nº965406), UKRI DASH (grant agreement NºMR/V038966/1). Special thanks to T. Biro and her radical collaboration team from Research Data Alliance who gave us great inspiration on how to lead this radical collaboration work.