BUSCADOR RECOLECTA

64 pages, This public ICATMAR report presents the analysis of operational data products derived from the first operating year of the ICATMAR High-Frequency Radar (HFR) network. The report is divided in three sections. The first one presents a description of the technical characteristics of the ICATMAR HFR network and the data period analysed here. The second one presents de description of the Quality Control (QC) model applied on the level 2 (L2) products, which correspond to radial velocity measures. Then, the performance of the L2 QC model on the 1st year of available data is analysed, together with a general statistical assessment of radial velocity measures that passed the QC. Last section presents de description of the QC model applied on the level 3 (L3) products, which correspond to total velocity measures derived from the combination of radial velocities measured by each HFR. As in the previous section, the performance of the L3 QC model on the 1st year of available data is analysed, together with a general statistical assessment of total velocity measures that passed the QC. Final part of this section includes the first exercise of ICATMAR HFR-derived data validation through the comparison with marine current measures from a Puertos del Estado fixed buoy and with Lagrangian trajectories of drifting objects, This work contributes to the Institut de Ciències del Mar "Severo Ochoa Centre of Excellence" accreditation CEX2024-001494-S funded by AEI 10.13039/501100011033 of the Spanish Ministry of Science and Innovation, Peer reviewed

The left panel shows temperature and the right panel shows salinity. Warmer temperatures and higher salinity are represented in red tones, while cooler and fresher values appear in blue. Grid smoothing was applied to reduce artifacts due to sparse data coverage, particularly near islands and continental slopes. These maps provide an indicative overview of oceanographic conditions at the onset of the study period, but are not directly comparable to GLORYS12V1-based maps of potential temperature., Peer reviewed

Description of methods used for collection/generation/processing of data: Described in the Materials and Methods section from “García-Martínez, M., Saiz, E. & Calbet, A. (2025). Thermal performance of the heterotrophic dinoflagellate Oxyrrhis marina under long-term warming and acute heat stress. Journal of Plankton Research, 47(5), fbaf013. https://doi.org/10.1093/plankt/fbaf013”, This research was funded by Grants PID2020-118645RB-I00 and PID2023-150548NB-I00 by MICIU/AEI/10.13039/501100011033 and “ERDF/EU”. M. G.-M. was supported by Grant PRE2021-096866 funded by MICIU/AEI/10.13039/501100011033 and FSE+, This work contributes to the Institut de Ciències del Mar "Severo Ochoa Centre of Excellence" accreditation CEX2024-001494-S funded by AEI 10.13039/501100011033 of the Spanish Ministry of Science and Innovation, 1. Number of variables: “Thermal performance curves” sheet – 3; “Functional responses” sheet – 30; “Growth, ingestion and doubling” sheet – 5. // 2. Number of cases/rows: “Thermal performance curves” sheet – 21; “Functional responses” sheet – 14; “Growth, ingestion and doubling” sheet – 12. // 3. Variable List: “Thermal performance curves” sheet – Oxyrrhis marina line, Thermal performance curve temperature (ºC), Growth rate (µ; d-1), SE. “Functional responses” sheet – 16ºC line - 16ºC: Prey concentration (prey mL-1), Prey concentration (pg Cprey mL-1), Clearance rate (µL ind-1 d-1), Ingestion rate (prey ind-1 d-1), Ingestion rate (pg Cprey ind-1 d-1); 16ºC line - HS+3ºC: Prey concentration (prey mL-1), Prey concentration (pg Cprey mL-1), Clearance rate (µL ind-1 d-1), Ingestion rate (prey ind-1 d-1), Ingestion rate (pg Cprey ind-1 d-1); 19ºC line - 19ºC: Prey concentration (prey mL-1), Prey concentration (pg Cprey mL-1), Clearance rate (µL ind-1 d-1), Ingestion rate (prey ind-1 d-1), Ingestion rate (pg Cprey ind-1 d-1); 19ºC line - HS+3ºC: Prey concentration (prey mL-1), Prey concentration (pg Cprey mL-1), Clearance rate (µL ind-1 d-1), Ingestion rate (prey ind-1 d-1), Ingestion rate (pg Cprey ind-1 d-1); 22ºC line - 22ºC: Prey concentration (prey mL-1), Prey concentration (pg Cprey mL-1), Clearance rate (µL ind-1 d-1), Ingestion rate (prey ind-1 d-1), Ingestion rate (pg Cprey ind-1 d-1); 22ºC line - HS+3ºC: Prey concentration (prey mL-1), Prey concentration (pg Cprey mL-1), Clearance rate (µL ind-1 d-1), Ingestion rate (prey ind-1 d-1), Ingestion rate (pg Cprey ind-1 d-1). “Growth, ingestion and doubling” sheet – Oxyrrhis marina line, Temperature stress, Growth rate (µ; d-1), Ingestion rate (µg Cprey ind-1 d-1), Doubling efficiency (doublings day-1 ingestion rate-1), Peer reviewed

Osmeriformes represent an important component of freshwater ecosystems in Australia and New Zealand and yet are poorly represented in the fossil record in these countries. Here we describe a new species of fossil osmeriform from the Miocene of New South Wales. Australia. Phylogenetic analyses place the species as an early diverging member of the southern radiation of Osmeriformes. The fossils are embedded and mineralized in the iron oxide-hydroxide mineral goethite, resulting in an unusual degree of preservation. Preserved stomach contents indicate an opportunistic benthopelagic diet, evidenced by the remains of numerous phantom midge larvae (Chaoborus abundans), two insect wings, and a bivalve. Another bivalve (Unionidae) was found attached to the tail of one of the specimens. The distribution of melanophores indicates that the species was counter-shaded with two lateral stripes. Discovering this species west of the Great Dividing Range, with a population that includes a range of body sizes, suggests that at least this population if not the species spent its entire life in fresh water, unlike most extant Osmeriformes. The description of F. brocksi highlights the ability of specimens with preserved soft tissues to reveal aspects of the paleobiology of extinct species., Peer reviewed

1 .xlsx file. Published February 13, 2025; Version v1. Under a Creative Commons Attribution 4.0 International License., Only 87.9% of the Little Ice Age glaciers remain in the Maladeta massif (Central Pyrenees). This deglaciation has led to an increase in proglacial areas, allowing the development of new habitats. 86 samples of incipient soils were selected in this massif to study which variables have more influence on the development of incipient soils. Geochemical, microbiological and statistical analyses were carried out under the hypothesis that the time of deglaciation controls the evolution of these incipient soils. In these very incipient soils, the time of deglaciation does not seem to be a key factor that determines the development of the soils. Despite this, the duration of the snow cover (strongly influenced by the topography) is a factor that explains the degree of development of the soils. Moreover, the percentage of silt content has been shown to give the soil a higher reactivity, water and nutrient retention capacity and greater stability. A pattern of biological succession was found, from bacteria as colonisers to fungi in subsequent stages, and finally to plants colonising the habitats. Finally, the impact of mountain tourism in the most transited sector of the Maladeta massif (the Aneto cirque) showed a high concentration of nitrate which favours primary productivity and increases the abundance of microorganisms., Peer reviewed

4 pages, 2 tables, This work also acknowledges to ANID/FONDAP No. 1511009; to the Severo Ochoa Centre of Excellence accreditation (CEX2024-001494-S), funded by AEI 10.13039/501100011033, and to the project Highlands.3 from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 872328, Projects: UCV2095, Centro de Acción Climática-PUCV, DI emergent 039.340/2021 PUCV and IAEA project CRPF33031. Celine L. was funded by the projects ANID InES I + D 2021 grant number INID210013 and Marie Curie Postdoctoral Fellowship HORIZON-MSCA-2022-PF-01 project grant number 101106387, Table S1. WS: water source; SPA: sample point altitude in m. asl; MCA: mean catchment altitude in m. asl; CA: catchment area in Km2; EC: electrical conductivity in µs cm−1; Ca: calcium; Mg: magnesium; Na: sodium; K: potassium; HCO3: bicarbonates; Cl: chlorides; SO4: sulphates. All the ions are expressed in meq L-1.-- Table S2. Social perception survey answers. A: perception of the major origin of water during drought years; B: perception of the major origin of water during normal to rainy/snowy years; C: whether they were affected by the megadrought; D: perceptions of the causes of water, Peer reviewed

This work was supported by the UK Natural Environment Research Council funded Seabed Mining and Resilience to Experimental impact (SMARTEX) project (grant reference NE/T003537/1). Novel methods for distance- decay analyses used in this study were developed through grant no. PID2020-112935GB-I00/AEI/10.13039/501100011033 to A.B. and C.G.R. D.J.A. received funding from UC Santa Barbara's Benioff Ocean Science Laboratory. J.M.D. was funded by UK Natural Environment Research Council's Climate Linked Atlantic Sector Science project (NE-R015953/1) and AtlantiS project (NE/Y005589/1). A.M.S. was funded by la Caixa Foundation (Fellowship Code LCF/BQ/DI21/11860043). [...] With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed

D.G.G. acknowledges the funding of Margarita Salas 2021–2023 postdoctoral Fellowship program (Ministerio de Universidades). CL gratefully acknowledges the financial support by ICREA under the ICREA Academia program. D.G.G., N.V., A.G., C.L. & Y.Z. are part of the Marine Conservation research group –MedRecover (2021 SGR 01073) from the ‘Generalitat de Catalunya’. JSM acknowledges funding from the National Science Foundation (1948946), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), The OctocoralTraits_v2_2 ZIP file contains structured data and code to create all figures from the manuscript: “The Octocoral Trait Database: a global database of trait information for octocoral species”. The folder also contains the code used to validate the data descriptor. Specifically, the folder contains the following files: · Code.R – This is the annotated code used to create all figures in R. (v R studio; 2023.06.0+421) · OctocoralTraits_v2_2.csv – This is the first data realase of the octocoral trait database, used to create all figures of the manuscript. · sp_id.csv – This is a file containing the list of accepted octocoral species contained in the database · iqtree.tre – This is a tree object used to create a family-resolved tree of octocorals. It has been downloaded from McFadden et al. 2022. Revisionary systematics of Octocorallia (Cnidaria: Anthozoa) guided by phylogenomics · MEOW folder – A folder containing regional information from Spalding et al. 2007. Marine Ecoregions of the World: A Bioregionalization of Coastal and Shelf Areas · Provinces_coord.csv: A file containing the coordinates of marine provinces, also derived from Spalding et al. 2007 · Table_ids folder - A folder containing tables with information of the corresponding ids that appear in the file database. · Validation folder: A folder containing a Technical_validation.R file that was used to flag outliers and extreme outliers, duplicated rows and potential structural errors in the data (e.g., a given observation_id linked to more than one resource, species or location), Peer reviewed

The data we provide here have been assembled to categorise fish into feeding guilds and determine change in populations of fish with different feeding traits relevant to food web status assessment advocated by OSPAR. We provide four datasets: the first is a csv file titled ‘stomach data observations’ contains observations from fish stomach contents of individual prey weight, prey functional group (i.e., zooplankton, benthos, fish, nekton and other), predator taxonomy, predator size, and the region and year the samples were collected (Table 1; see Columnheadersreadme.txt); the second is a csv file titled ‘modelled stomach data’ provides predictions from a linear mixed effects model of individual prey weight based on those stomach contents observations, alongside modelled estimates of prey counts and biomass which enable the full collation of stomach contents information to be used in our feeding guild classification (Table 2; feeding guilds are predatory categories assigned using cluster analysis on stomach content data; see Thompson et al., 2023); the third dataset is a shapefile titled ‘feeding guild responses in survey data’ and provides haul-level estimates of feeding guild species richness, numbers of fish and their biomass based on scientific trawl surveys from the Northeast Atlantic (Tables 3-4); the fourth is a shapefile titled ‘temporal changes in feeding guilds’ which contains correlation coefficients and p values following Kendall’s τ trend analysis between mean haul-level values of feeding guild biomass and species richness for each assessment strata and year. Kendall’s τ scores of –1 to +1 represent a 100% probability of a decreasing or increasing trend, respectively (Table 5). Stomach contents data., We draw together stomach contents data primarily collected from the North Atlantic shelf seas, with important contributions from the Baltic, Barents and Norwegian Seas in the Arctic Ocean. These data were sourced from a combination of previously published and unpublished data including DAPSTOM (Pinnegar, 2019), ICES Year of the Stomach (Daan, 1981; ICES, 1997), the Northeast US continental shelf (Smith & Link, 2010), Northern Spanish shelf (Arroyo et al., 2017), Gulf of Cadiz (Torres et al., 2013), Swedish-, Icelandic-, Norwegian-, French- (Cachera et al., 2017; Timmerman et al., 2020; Travers-Trolet, 2017; Verin, 2018) and German-led surveys (e.g., FishNet, https://www.nationalpark-wattenmeer.de/wissensbeitrag/fishnet/; BioConsult, 2023). The observations used to model prey weight contain information from 621,040 fish stomachs (Table 1), from 146 predator taxa collected between 1963 – 2020 and includes larvae (<1 g) to adults (up to 351 kg). The full dataset contains predictions of prey weights and counts based on predator size, predator taxa and prey functional group information from 944,129 fish stomachs (Table 2), 227 predator taxa collected between 1836 – 2020 and includes larvae (<1 g) to adults (up to 351 kg)., [Scientific trawl survey data] Scientific trawl data were obtained from Lynam and Ribeiro (2022), a data product derived from Northeast Atlantic groundfish data from surveys undertaken between 1983-2020 with observations for the biomass and numbers of species size classes standardised to the area swept for each haul. We make use of data collected using otter trawls between 1997 – 2020. We process the data by categorising fish into feeding guilds using taxonomic and size information and sum estimates of biomass, numbers, and species richness by feeding guild for each haul observation. We provide the unique assessment units used in the pilot assessment to determine change in feeding guild responses (Lynam et al., 2022; Lynam & Piet, 2022; Thompson et al., 2023). We provide details of the columns used in Table 3, a summary of the specific surveys used in Table 4. Details of the columns in the data containing correlations and p values based following Kendall’s τ trend analysis are provided in Table 5., [Associated scientific study] These data were processed for the study "Fish functional groups of the North Atlantic and Arctic Oceans ", by Murray S.A. Thompson, Izaskun Preciado, Federico Maioli, Valerio Bartolino, Andrea Belgrano, Michele Casini, Pierre Cresson, Elena Eriksen, Gema Hernandez-Milian, Ingibjörg G. Jónsdóttir, Stefan Neuenfeldt, John K. Pinnegar, Stefán Ragnarsson, Sabine Schückel, Ulrike Schückel, Brian E. Smith, María Ángeles Torres, Thomas J. Webb, and Christopher P. Lynam (in prep; see also Thompson et al., 2023)., [Data Links] https://data.cefas.co.uk/#/View/21771, [Data access and use - comments] Publicly available data licensed under the Open Government Licence v3.0 (https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/) – Please note the applicable attribution statement is as follows: ‘includes Crown copyright, Cefas 2023', Peer reviewed

1 file.-- Data from a discrete choice experiment collected through face-to-face surveys at the city of Vigo (Pontevedra, Spain), Discrete choice data for 402 individuals, 6 choices by individual, 3 alternatives each choice card, Grant TED2021-130267B-I00 funded by MCIN/AEI/10.13039/501100011033 and by the European Union and the European Union NextGenerationEU/PRTR, Peer reviewed