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Research data keyboard_double_arrow_right Dataset 2020Publisher:Zenodo Funded by:EC | EdgeStressEC| EdgeStressThyrring, Jakob; Wegeberg, Susse; Blicher, Martin E.; Krause-Jensen, Dorte; Høgslund, Signe; Olesen, Birgit; Wiktor Jr, Jozef; Mouritsen, Kim N.; Peck, Lloyd S.; Sejr, Mikael K.;The data contains three supporting datasets: 1. Mid-intertidal data 2. Vertical transect data 3. GPS coordinates for all sites
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You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.3920534&type=result"></script>'); --> </script>
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.3920534&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Publisher:Zenodo Evans, Natalya; Tichota, Juliana; Ruef, Wendi; Moffett, James W.; Devol, Allan H.;Time series of data corresponding to Evans et al. (2022) "Natural variability and expansion of the nitrogen deficit within the Eastern Tropical North Pacific Oxygen Deficient Zone", containing secondary quality controlled data of 8 cruises in the ETNP ODZ, seven of which on the 110 W line, as well as supplemental sediment core data and CalCOFI oxygen data for comparison. Intermediate data products generated by the code used for this paper are also included, and the code to generate these intermediate products as well as the final outputs has been uploaded onto a separate Zenodo repository, "ETNP_ODZ_time_series_code" at https://doi.org/10.5281/zenodo.6519316. More detailed information is available in the README, but should you have any questions, please reach out to Allan Devol or Natalya Evans.
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You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.6519188&type=result"></script>'); --> </script>
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You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.6519188&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection , Dataset 2023Publisher:PANGAEA Ausems, Anne; Kuepper, Nadja; Archuby, Diego; Braun, Christina; Gębczyński, Andrzej; Gladbach, Anja; Hahn, Steffen; Jadwiszczak, Piotr; Krämer, Philipp; Libertelli, Marcela; Lorenz, Stefan; Richter, Benjamin; Ruß, Anja; Schmoll, Tim; Thorn, Simon; Turner, John; Wojczulanis-Jakubas, Katarzyna; Jakubas, Dariusz; Quillfeldt, Petra;This data set describes the population dynamics of Wilson's Storm Petrels (Oceanites oceanicus) at King George Island (Isla 25 de Mayo, Antarctica) over a forty year period (1978 – 2020). It includes all available data on Wilson's Storm Petrels from two colonies: around the Argentinian Base Carlini (62°14′S, 58°40′W; CA, formerly called Base Jubany) and the Henryk Arctowski Polish Antarctic Station (62°09′S, 58°27′W; HA). Data on population productivity (number of nests, eggs, chicks and fledglings) was collected by regular visits to the colonies and searching for nest burrows, or monitoring of the egg or chick if found. Data on adult abundance and estimated age categories (i.e., presence of foot spots; Quillfeldt et al. (2000, doi:10.1007/s003000000167) were collected at CA by using the same size mistnet every study year in the same location within the breeding colony. Chicks were measured regularly (varying intervals depending on the study) at both CA and HA. Chick tarsus was measured using callipers (vernier or digital depending on the study year) to the nearest 0.1 mm, chick wing length was measured using wing rulers to the nearest 1 mm, and chick body mass was measured using mechanical or digital scales depending on the study year to the nearest 0.1 g. Chick growth rates were calculated based on the linear growth period following Ausems et al. (2020, doi:10.1016/j.scitotenv.2020.138768). Chick food loads (g) were recorded at CA and determined based on changes in chick body mass on consecutive days (Gladbach et al. (2009, doi:10.1007/s00300-009-0628-z); Kuepper et al. (2018, doi:10.1016/j.cbpa.2018.06.018). This study was further supported by the Erasmus+ programm and thee German Academic Exchange Service (DAAD)
PANGAEA arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceCollection . 2023License: CC BY SAData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceCollection . 2023License: CC BY SAData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017Publisher:Zenodo Mislan, K. A. S.; Deutsch, Curtis A.; Brill, Richard W.; Dunne, John P.; Sarmiento, Jorge L.;Model results and data used to make future projections of the effects of climate change on the physiology of tuna in the global ocean ------------------------------------------------- Description: Coupled Model Intercomparison Project Phase 5 (CMIP5) model results were downloaded from here: https://esgf-node.llnl.gov/search/cmip5/ World Ocean Atlas (WOA) 2009 data were downloaded from here: https://www.nodc.noaa.gov/OC5/WOA09/netcdf_data.html The model results and data should only be used to reproduce the analysis described in this publication: Mislan, K. A. S., C. A. Deutsch, R. W. Brill, J. P. Dunne, and J. L. Sarmiento. (2017) Projections of climate driven changes in tuna vertical habitat based on species-specific differences in blood oxygen affinity. Global Change Biology. The Zenodo archive of the code is here: https://doi.org/10.5281/zenodo.808742 ------------------------------------------------- Instructions: Download the tar.gz file, unzip, and put the folders in the data folder of the CMIP5_p50_tuna code.
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You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.807748&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Embargo end date: 30 May 2023Publisher:Dryad Braun, Camrin; Arostegui, Martin; Farchadi, Nima; Alexander, Michael; Afonso, Pedro; Allyn, Andrew; Bograd, Steven; Brodie, Stephanie; Crear, Daniel; Culhane, Emmett; Curtis, Tobey; Hazen, Elliott; Kerney, Alex; Lezama-Ochoa, Nerea; Mills, Katherine; Pugh, Dylan; Queiroz, Nuno; Scott, James; Skomal, Gregory; Sims, David; Thorrold, Simon; Welch, Heather; Young-Morse, Riley; Lewison, Rebecca;Species distribution models (SDMs) are becoming an important tool for marine conservation and management. Yet while there is an increasing diversity and volume of marine biodiversity data for training SDMs, little practical guidance is available on how to leverage distinct data types to build robust models. We explored the effect of different data types on the fit, performance and predictive ability of SDMs by comparing models trained with four data types for a heavily exploited pelagic fish, the blue shark (Prionace glauca), in the Northwest Atlantic: two fishery-dependent (conventional mark-recapture tags, fisheries observer records) and two fishery-independent (satellite-linked electronic tags, pop-up archival tags). We found that all four data types can result in robust models, but differences among spatial predictions highlighted the need to consider ecological realism in model selection and interpretation regardless of data type. Differences among models were primarily attributed to biases in how each data type, and the associated representation of absences, sampled the environment and summarized the resulting species distributions. Outputs from model ensembles and a model trained on all pooled data both proved effective for combining inferences across data types and provided more ecologically realistic predictions than individual models. Our results provide valuable guidance for practitioners developing SDMs. With increasing access to diverse data sources, future work should further develop truly integrative modeling approaches that can explicitly leverage strengths of individual data types while statistically accounting for limitations, such as sampling biases. Please see the README document ("README.md") and the accompanying published article: Braun, C. D., M. C. Arostegui, N. Farchadi, M. Alexander, P. Afonso, A. Allyn, S. J. Bograd, S. Brodie, D. P. Crear, E. F. Culhane, T. H. Curtis, E. L. Hazen, A. Kerney, N. Lezama-Ochoa, K. E. Mills, D. Pugh, N. Queiroz, J. D. Scott, G. B. Skomal, D. W. Sims, S. R. Thorrold, H. Welch, R. Young-Morse, R. Lewison. In press. Building use-inspired species distribution models: using multiple data types to examine and improve model performance. Ecological Applications. Accepted. DOI: < article DOI will be added when it is assigned >
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020Publisher:PANGAEA Funded by:NSF | Collaborative research: U...NSF| Collaborative research: Understanding the effects of acidification and hypoxia within and across generations in a coastal marine fishAuthors: Murray, Christopher S; Baumann, Hannes;Whether marine fish will grow differently in future high pCO2 environments remains surprisingly uncertain. Long-term and whole-life cycle effects are particularly unknown, because such experiments are logistically challenging, space demanding, exclude long-lived species, and require controlled, restricted feeding regimes—otherwise increased consumption could mask potential growth effects. Here, we report on repeated, long-term, food-controlled experiments to rear large populations (>4,000 individuals total) of the experimental model and ecologically important forage fish Menidia menidia (Atlantic silverside) under contrasting temperature (17°, 24°, and 28°C) and pCO2 conditions (450 vs. 2,200 μatm) from fertilization to a third of this annual species' life span. Quantile analyses of trait distributions showed mostly negative effects of high pCO2 on long-term growth. At 17°C and 28°C, but not at 24°C, high pCO2 fish were significantly shorter [17°C: -5 to -9%; 28°C: -3%] and weighed less [17°C: -6 to -18%; 28°C: -8%] compared to ambient pCO2 fish. Reductions in fish weight were smaller than in length, which is why high pCO2 fish at 17°C consistently exhibited a higher Fulton's k (weight/length ratio). Notably, it took more than 100 days of rearing for statistically significant length differences to emerge between treatment populations, showing that cumulative, long-term CO2 effects could exist elsewhere but are easily missed by short experiments. Long-term rearing had another benefit: it allowed sexing the surviving fish, thereby enabling rare sex-specific analyses of trait distributions under contrasting CO2 environments. We found that female silversides grew faster than males, but there was no interaction between CO2 and sex, indicating that males and females were similarly affected by high pCO2. Because Atlantic silversides are known to exhibit temperature-dependent sex determination, we also analyzed sex ratios, revealing no evidence for CO2-dependent sex determination in this species. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2020) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-12-25.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1594/pangaea.926048&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:PANGAEA Price, James T; McLachlan, Rowan H; Jury, Christopher P; Toonen, Robert J; Wilkins, Michael J; Grottoli, Andréa G;In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2022) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2023-10-17. This dataset includes physiological parameters of three Hawaiian coral species (Porites compressa, Porites lobata, and Montipora capitata) over 22-month mesocosm experiment. The corals were exposed to one of four treatments: control, ocean acidification, ocean warming, or combined future ocean conditions.
PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2023License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2023License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1594/pangaea.963864&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020Publisher:PANGAEA Funded by:NSF | Collaborative Research: O..., NSF | Collaborative Research: O...NSF| Collaborative Research: Ocean Acidification: microbes as sentinels of adaptive responses to multiple stressors: contrasting estuarine and open ocean environments ,NSF| Collaborative Research: Ocean Acidification: microbes as sentinels of adaptive responses to multiple stressors: contrasting estuarine and open ocean environmentsWang, Z; Tsementzi, Despina; Williams, Tiffany C; Juarez, Doris L; Blinebry, Sara K; Garcia, Nathan S; Sienkiewicz, Brooke K; Konstantinidis, Konstantinos T; Johnson, Zackary I; Hunt, Dana E;Ambient conditions shape microbiome responses to both short- and long-duration environment changes through processes including physiological acclimation, compositional shifts, and evolution. Thus, we predict that microbial communities inhabiting locations with larger diel, episodic, and annual variability in temperature and pH should be less sensitive to shifts in these climate-change factors. To test this hypothesis, we compared responses of surface ocean microbes from more variable (nearshore) and more constant (offshore) sites to short-term factorial warming (+3 °C) and/or acidification (pH -0.3). In all cases, warming alone significantly altered microbial community composition, while acidification had a minor influence. Compared with nearshore microbes, warmed offshore microbiomes exhibited larger changes in community composition, phylotype abundances, respiration rates, and metatranscriptomes, suggesting increased sensitivity of microbes from the less-variable environment. Moreover, while warming increased respiration rates, offshore metatranscriptomes yielded evidence of thermal stress responses in protein synthesis, heat shock proteins, and regulation. Future oceans with warmer waters may enhance overall metabolic and biogeochemical rates, but they will host altered microbial communities, especially in relatively thermally stable regions of the oceans. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2019) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-10-20.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Embargo end date: 21 May 2024Publisher:Dryad Receveur, Aurore; Leprieur, Fabien; Ellingsen, Kari E.; Keith, David; Kleisner, Kristin M.; Mclean, Matthew; Merigot, Bastien; Mills, Katherine E.; Mouillot, David; Rufino, Marta; Trindade-Santos, Isaac; Van Hoey, Gert; Albouy, Camille; Auber, Arnaud;# 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.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: von Schuckmann, Karina; Minière, Audrey; Gues, Flora; Cuesta-Valero, Francisco José; +58 Authorsvon Schuckmann, Karina; Minière, Audrey; Gues, Flora; Cuesta-Valero, Francisco José; Kirchengast, Gottfried; Adusumilli, Susheel; Straneo, Fiammetta; Allan, Richard; Barker, Paul M.; Beltrami, Hugo; Boyer, Tim; Cheng, Lijing; Church, John; Desbruyeres, Damien; Dolman, Han; Domingues, Catia M.; García-García, Almudena; Gilson, John; Gorfer, Maximilian; Haimberger, Leopold; Hendricks, Stefan; Hosoda, Shigeki; Johnson, Gregory C.; Killick, Rachel; King, Brian A.; Kolodziejczyk, Nicolas; Korosov, Anton; Krinner, Gerhard; Kuusela, Mikael; Langer, Moritz; Lavergne, Thomas; Lawrence, Isobel; Li, Yuehua; Lyman, John; Marzeion, Ben; Mayer, Michael; MacDougall, Andrew; McDougall, Trevor; Monselesan, Didier Paolo; Nitzbon, Jean; Otosaka, Inès; Peng, Jian; Purkey, Sarah; Roemmich, Dean; Sato, Kanako; Sato, Katsunari; Savita, Abhishek; Schweiger, Axel; Shepherd, Andrew; Seneviratne, Sonia I.; Slater, Donald A.; Slater, Thomas; Simons, Leon; Steiner, Andrea K.; Szekely, Tanguy; Suga, Toshio; Thiery, Wim; Timmermanns, Mary-Louise; Vanderkelen, Inne; Wijffels, Susan E.; Wu, Tonghua; Zemp, Michael;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).
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Research data keyboard_double_arrow_right Dataset 2020Publisher:Zenodo Funded by:EC | EdgeStressEC| EdgeStressThyrring, Jakob; Wegeberg, Susse; Blicher, Martin E.; Krause-Jensen, Dorte; Høgslund, Signe; Olesen, Birgit; Wiktor Jr, Jozef; Mouritsen, Kim N.; Peck, Lloyd S.; Sejr, Mikael K.;The data contains three supporting datasets: 1. Mid-intertidal data 2. Vertical transect data 3. GPS coordinates for all sites
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Publisher:Zenodo Evans, Natalya; Tichota, Juliana; Ruef, Wendi; Moffett, James W.; Devol, Allan H.;Time series of data corresponding to Evans et al. (2022) "Natural variability and expansion of the nitrogen deficit within the Eastern Tropical North Pacific Oxygen Deficient Zone", containing secondary quality controlled data of 8 cruises in the ETNP ODZ, seven of which on the 110 W line, as well as supplemental sediment core data and CalCOFI oxygen data for comparison. Intermediate data products generated by the code used for this paper are also included, and the code to generate these intermediate products as well as the final outputs has been uploaded onto a separate Zenodo repository, "ETNP_ODZ_time_series_code" at https://doi.org/10.5281/zenodo.6519316. More detailed information is available in the README, but should you have any questions, please reach out to Allan Devol or Natalya Evans.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection , Dataset 2023Publisher:PANGAEA Ausems, Anne; Kuepper, Nadja; Archuby, Diego; Braun, Christina; Gębczyński, Andrzej; Gladbach, Anja; Hahn, Steffen; Jadwiszczak, Piotr; Krämer, Philipp; Libertelli, Marcela; Lorenz, Stefan; Richter, Benjamin; Ruß, Anja; Schmoll, Tim; Thorn, Simon; Turner, John; Wojczulanis-Jakubas, Katarzyna; Jakubas, Dariusz; Quillfeldt, Petra;This data set describes the population dynamics of Wilson's Storm Petrels (Oceanites oceanicus) at King George Island (Isla 25 de Mayo, Antarctica) over a forty year period (1978 – 2020). It includes all available data on Wilson's Storm Petrels from two colonies: around the Argentinian Base Carlini (62°14′S, 58°40′W; CA, formerly called Base Jubany) and the Henryk Arctowski Polish Antarctic Station (62°09′S, 58°27′W; HA). Data on population productivity (number of nests, eggs, chicks and fledglings) was collected by regular visits to the colonies and searching for nest burrows, or monitoring of the egg or chick if found. Data on adult abundance and estimated age categories (i.e., presence of foot spots; Quillfeldt et al. (2000, doi:10.1007/s003000000167) were collected at CA by using the same size mistnet every study year in the same location within the breeding colony. Chicks were measured regularly (varying intervals depending on the study) at both CA and HA. Chick tarsus was measured using callipers (vernier or digital depending on the study year) to the nearest 0.1 mm, chick wing length was measured using wing rulers to the nearest 1 mm, and chick body mass was measured using mechanical or digital scales depending on the study year to the nearest 0.1 g. Chick growth rates were calculated based on the linear growth period following Ausems et al. (2020, doi:10.1016/j.scitotenv.2020.138768). Chick food loads (g) were recorded at CA and determined based on changes in chick body mass on consecutive days (Gladbach et al. (2009, doi:10.1007/s00300-009-0628-z); Kuepper et al. (2018, doi:10.1016/j.cbpa.2018.06.018). This study was further supported by the Erasmus+ programm and thee German Academic Exchange Service (DAAD)
PANGAEA arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceCollection . 2023License: CC BY SAData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceCollection . 2023License: CC BY SAData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2017Publisher:Zenodo Mislan, K. A. S.; Deutsch, Curtis A.; Brill, Richard W.; Dunne, John P.; Sarmiento, Jorge L.;Model results and data used to make future projections of the effects of climate change on the physiology of tuna in the global ocean ------------------------------------------------- Description: Coupled Model Intercomparison Project Phase 5 (CMIP5) model results were downloaded from here: https://esgf-node.llnl.gov/search/cmip5/ World Ocean Atlas (WOA) 2009 data were downloaded from here: https://www.nodc.noaa.gov/OC5/WOA09/netcdf_data.html The model results and data should only be used to reproduce the analysis described in this publication: Mislan, K. A. S., C. A. Deutsch, R. W. Brill, J. P. Dunne, and J. L. Sarmiento. (2017) Projections of climate driven changes in tuna vertical habitat based on species-specific differences in blood oxygen affinity. Global Change Biology. The Zenodo archive of the code is here: https://doi.org/10.5281/zenodo.808742 ------------------------------------------------- Instructions: Download the tar.gz file, unzip, and put the folders in the data folder of the CMIP5_p50_tuna code.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Embargo end date: 30 May 2023Publisher:Dryad Braun, Camrin; Arostegui, Martin; Farchadi, Nima; Alexander, Michael; Afonso, Pedro; Allyn, Andrew; Bograd, Steven; Brodie, Stephanie; Crear, Daniel; Culhane, Emmett; Curtis, Tobey; Hazen, Elliott; Kerney, Alex; Lezama-Ochoa, Nerea; Mills, Katherine; Pugh, Dylan; Queiroz, Nuno; Scott, James; Skomal, Gregory; Sims, David; Thorrold, Simon; Welch, Heather; Young-Morse, Riley; Lewison, Rebecca;Species distribution models (SDMs) are becoming an important tool for marine conservation and management. Yet while there is an increasing diversity and volume of marine biodiversity data for training SDMs, little practical guidance is available on how to leverage distinct data types to build robust models. We explored the effect of different data types on the fit, performance and predictive ability of SDMs by comparing models trained with four data types for a heavily exploited pelagic fish, the blue shark (Prionace glauca), in the Northwest Atlantic: two fishery-dependent (conventional mark-recapture tags, fisheries observer records) and two fishery-independent (satellite-linked electronic tags, pop-up archival tags). We found that all four data types can result in robust models, but differences among spatial predictions highlighted the need to consider ecological realism in model selection and interpretation regardless of data type. Differences among models were primarily attributed to biases in how each data type, and the associated representation of absences, sampled the environment and summarized the resulting species distributions. Outputs from model ensembles and a model trained on all pooled data both proved effective for combining inferences across data types and provided more ecologically realistic predictions than individual models. Our results provide valuable guidance for practitioners developing SDMs. With increasing access to diverse data sources, future work should further develop truly integrative modeling approaches that can explicitly leverage strengths of individual data types while statistically accounting for limitations, such as sampling biases. Please see the README document ("README.md") and the accompanying published article: Braun, C. D., M. C. Arostegui, N. Farchadi, M. Alexander, P. Afonso, A. Allyn, S. J. Bograd, S. Brodie, D. P. Crear, E. F. Culhane, T. H. Curtis, E. L. Hazen, A. Kerney, N. Lezama-Ochoa, K. E. Mills, D. Pugh, N. Queiroz, J. D. Scott, G. B. Skomal, D. W. Sims, S. R. Thorrold, H. Welch, R. Young-Morse, R. Lewison. In press. Building use-inspired species distribution models: using multiple data types to examine and improve model performance. Ecological Applications. Accepted. DOI: < article DOI will be added when it is assigned >
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020Publisher:PANGAEA Funded by:NSF | Collaborative research: U...NSF| Collaborative research: Understanding the effects of acidification and hypoxia within and across generations in a coastal marine fishAuthors: Murray, Christopher S; Baumann, Hannes;Whether marine fish will grow differently in future high pCO2 environments remains surprisingly uncertain. Long-term and whole-life cycle effects are particularly unknown, because such experiments are logistically challenging, space demanding, exclude long-lived species, and require controlled, restricted feeding regimes—otherwise increased consumption could mask potential growth effects. Here, we report on repeated, long-term, food-controlled experiments to rear large populations (>4,000 individuals total) of the experimental model and ecologically important forage fish Menidia menidia (Atlantic silverside) under contrasting temperature (17°, 24°, and 28°C) and pCO2 conditions (450 vs. 2,200 μatm) from fertilization to a third of this annual species' life span. Quantile analyses of trait distributions showed mostly negative effects of high pCO2 on long-term growth. At 17°C and 28°C, but not at 24°C, high pCO2 fish were significantly shorter [17°C: -5 to -9%; 28°C: -3%] and weighed less [17°C: -6 to -18%; 28°C: -8%] compared to ambient pCO2 fish. Reductions in fish weight were smaller than in length, which is why high pCO2 fish at 17°C consistently exhibited a higher Fulton's k (weight/length ratio). Notably, it took more than 100 days of rearing for statistically significant length differences to emerge between treatment populations, showing that cumulative, long-term CO2 effects could exist elsewhere but are easily missed by short experiments. Long-term rearing had another benefit: it allowed sexing the surviving fish, thereby enabling rare sex-specific analyses of trait distributions under contrasting CO2 environments. We found that female silversides grew faster than males, but there was no interaction between CO2 and sex, indicating that males and females were similarly affected by high pCO2. Because Atlantic silversides are known to exhibit temperature-dependent sex determination, we also analyzed sex ratios, revealing no evidence for CO2-dependent sex determination in this species. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2020) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-12-25.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:PANGAEA Price, James T; McLachlan, Rowan H; Jury, Christopher P; Toonen, Robert J; Wilkins, Michael J; Grottoli, Andréa G;In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2022) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2023-10-17. This dataset includes physiological parameters of three Hawaiian coral species (Porites compressa, Porites lobata, and Montipora capitata) over 22-month mesocosm experiment. The corals were exposed to one of four treatments: control, ocean acidification, ocean warming, or combined future ocean conditions.
PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2023License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA - Data Publi... arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceDataset . 2023License: CC BYData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2020Publisher:PANGAEA Funded by:NSF | Collaborative Research: O..., NSF | Collaborative Research: O...NSF| Collaborative Research: Ocean Acidification: microbes as sentinels of adaptive responses to multiple stressors: contrasting estuarine and open ocean environments ,NSF| Collaborative Research: Ocean Acidification: microbes as sentinels of adaptive responses to multiple stressors: contrasting estuarine and open ocean environmentsWang, Z; Tsementzi, Despina; Williams, Tiffany C; Juarez, Doris L; Blinebry, Sara K; Garcia, Nathan S; Sienkiewicz, Brooke K; Konstantinidis, Konstantinos T; Johnson, Zackary I; Hunt, Dana E;Ambient conditions shape microbiome responses to both short- and long-duration environment changes through processes including physiological acclimation, compositional shifts, and evolution. Thus, we predict that microbial communities inhabiting locations with larger diel, episodic, and annual variability in temperature and pH should be less sensitive to shifts in these climate-change factors. To test this hypothesis, we compared responses of surface ocean microbes from more variable (nearshore) and more constant (offshore) sites to short-term factorial warming (+3 °C) and/or acidification (pH -0.3). In all cases, warming alone significantly altered microbial community composition, while acidification had a minor influence. Compared with nearshore microbes, warmed offshore microbiomes exhibited larger changes in community composition, phylotype abundances, respiration rates, and metatranscriptomes, suggesting increased sensitivity of microbes from the less-variable environment. Moreover, while warming increased respiration rates, offshore metatranscriptomes yielded evidence of thermal stress responses in protein synthesis, heat shock proteins, and regulation. Future oceans with warmer waters may enhance overall metabolic and biogeochemical rates, but they will host altered microbial communities, especially in relatively thermally stable regions of the oceans. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2019) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-10-20.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Embargo end date: 21 May 2024Publisher:Dryad Receveur, Aurore; Leprieur, Fabien; Ellingsen, Kari E.; Keith, David; Kleisner, Kristin M.; Mclean, Matthew; Merigot, Bastien; Mills, Katherine E.; Mouillot, David; Rufino, Marta; Trindade-Santos, Isaac; Van Hoey, Gert; Albouy, Camille; Auber, Arnaud;# 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.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors: von Schuckmann, Karina; Minière, Audrey; Gues, Flora; Cuesta-Valero, Francisco José; +58 Authorsvon Schuckmann, Karina; Minière, Audrey; Gues, Flora; Cuesta-Valero, Francisco José; Kirchengast, Gottfried; Adusumilli, Susheel; Straneo, Fiammetta; Allan, Richard; Barker, Paul M.; Beltrami, Hugo; Boyer, Tim; Cheng, Lijing; Church, John; Desbruyeres, Damien; Dolman, Han; Domingues, Catia M.; García-García, Almudena; Gilson, John; Gorfer, Maximilian; Haimberger, Leopold; Hendricks, Stefan; Hosoda, Shigeki; Johnson, Gregory C.; Killick, Rachel; King, Brian A.; Kolodziejczyk, Nicolas; Korosov, Anton; Krinner, Gerhard; Kuusela, Mikael; Langer, Moritz; Lavergne, Thomas; Lawrence, Isobel; Li, Yuehua; Lyman, John; Marzeion, Ben; Mayer, Michael; MacDougall, Andrew; McDougall, Trevor; Monselesan, Didier Paolo; Nitzbon, Jean; Otosaka, Inès; Peng, Jian; Purkey, Sarah; Roemmich, Dean; Sato, Kanako; Sato, Katsunari; Savita, Abhishek; Schweiger, Axel; Shepherd, Andrew; Seneviratne, Sonia I.; Slater, Donald A.; Slater, Thomas; Simons, Leon; Steiner, Andrea K.; Szekely, Tanguy; Suga, Toshio; Thiery, Wim; Timmermanns, Mary-Louise; Vanderkelen, Inne; Wijffels, Susan E.; Wu, Tonghua; Zemp, Michael;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).
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