Resultados de investigación

This dataset contains soil organic carbon (SOC) and nitrogen (N) stocks, greenhouse gas (GHG) fluxes (N₂O and CH₄), and enzymatic activities related to carbon and nitrogen cycling. The data were collected across different land uses (forest, cereal and vineyard) in a Mediterranean ecosystem (Bosque de Matasnos, Spain), considering two soil depths (0–20 cm and 20–40 cm), The dataset was generated to assess the effects of land-use change on soil carbon storage, greenhouse gas emissions, and soil biochemical functioning, This work has been co-financed by the LIFE Programme of the European Union (Ref: LIFE22-CCM-ES-CLIMAWIN/101113948), Peer reviewed

List of statistical models and figures with their notation in SAS and R for “Phenology Modulates the Top-Down Control of Ants on Bird Ectoparasites: From Mutualism to Antagonism”. The models are organized following the order of the subsections in the Results and were run using the three data sets (chick_data.csv, stress_index.csv and SEM_data.csv) available in Zenodo at https://doi.org/10.5281/zenodo.15721917, Peer reviewed

Biochar is a recognized tool for soil carbon (C) sequestration and climate change mitigation. However, the effectiveness of chemical modifications, such as alkali and alkaline earth metal enrichment, in enhancing C stability and reducing N2O emissions under field conditions has yet to be established. The objective of this study was to assess whether the modification of biochars can enhance their C sequestration potential while mitigating N₂O emissions under field conditions, thereby supporting more sustainable agricultural soil management, This research was supported by the project PID2021-128896OB-I00 funded by MCIN/AEI/10.13039/501100011033/ and ERDF A way of making Europe. Yaiza Blázquez-Nieto was supported by the grant PRE2022-105698 funded by MCIN/AEI/10.13039/501100011033/, Peer reviewed

The PDF file includes: Supplementary Materials and Methods; Figures S1 to S6, Supplementary References. Other supporting materials for this manuscript include the following: Supplementary Data S1 to S11 are spreadsheet files; Supplementary Data S1: Figure 1 source data; Supplementary Data S2: Figure 2 source data; Supplementary Data S3: Figure 3 source data; Supplementary Data S4: Figure 4 source data; Supplementary Data S5: Figure 5 source data; Supplementary Data S6: Figure 6 source data; Supplementary Data S7: Figure 7 source data; Supplementary Data S8: Figure 8 source data; Supplementary Data S9: Supplementary Figures source data; Supplementary Data S10: Primer list; Supplementary Data S11: Strain list, Some strains were provided by the CGC, which is funded by NIH Office of Research Infrastructure Programs (P40 OD010440). This work was supported by European Research Council (COG-101002203), Ministerio de Ciencia, Innovación y Universidades (PID2020-115635RB-I00) and Generalitat Valenciana (CIAICO/2022/195)., Peer reviewed

This repository provides the data and code used in the article “Forecasting size-at-maturity shifts under global warming: a case study on European hake, a widely distributed species.” This is version 2 (post-acceptance, de-anonymized). The record now includes full author information, author contributions (CRediT), funding details, and the article reference in the metadata. Includes lagged temperatures in GAM analyses and weighted means when multiple maturity-size values occur in the same area-year. Changelog (v2) Incorporated lagged temperatures to be considered in GAM analyses. Implemented the calculation of weighted means for cases with multiple maturity size values in the same area and year. Reproducibility & updates Please see the README for instructions to reproduce the analyses. For ongoing updates and issue tracking, refer to the GitHub repository simhake. License & reuse See the LICENSE file. If you use these materials, please cite this dataset (this version) and the article. Related identifiers (to add in Zenodo metadata) Is supplemented by / is derived from: GitHub repository simhake. Is supplementary to: the article in Reviews in Fish Biology and Fisheries (DOI pending / in press; update once available), Ministerio de Ciencia, Innovación y Universidades: Improving Scientific Advice to Fishery Management for Resources of Interest for Spain in Atlantic Waters (IMPRESS) project RTI2018-099868-BI00 Ministerio de Ciencia, Innovación y Universidades: From Single Stock Assessment to Ecosystem-Based Fishery Management (FRESCO) project PID2022-140290OB-I00 Axencia Galega de Innovacion: Competitive Reference Group - Modelling and Evaluation of Exploited Resources (CRG-MERVEX) project IN607A 2022/04 Ministerio de Agricultura, Pesca y Alimentación: FishClim: Scientific Knowledge for the Adaptation of the Spanish Fishing Sector to Climate Change project Axis 4 Ministerio de Agricultura, Pesca y Alimentación: Math4Fish: New Tools for Mathematical Modelling in Spanish Fisheries Science Advice project Axis 6, 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

[Data Availability Statement] Data are available in the Environmental Data Initiative repository at https://doi.org/10.6073/pasta/d63489af723aec3b4a608c54ba7d636d. The code that supports the analyses in this study is uploaded to Zenodo and is available at https://doi.org/10.5281/zenodo.18276533. Measurements: Organismal elemental content (carbon, nitrogen, phosphorus) and ecosystem attributes. Temporal range: Varies by location, 1922–2024. Frequency or sampling interval: Varies by location. Spatial scale: Global., All organisms contain carbon, nitrogen, and phosphorus in widely ranging amounts and proportions. Integrating existing datasets enables quantification of this variation at global scales. Such efforts could leverage ecological stoichiometry theory, the study of elemental supply and imbalances in ecological interactions, to connect ecological drivers and taxonomic constraints to ecosystem structure and function. Towards this goal, we developed the Limnology Stoichiometric Traits of Organisms In their Chemical Habitats (Limno-STOICH) database. The Limno-STOICH database includes 51,576 observations of organismal elemental stoichiometry from >3100 rivers, lakes, wetlands, and other aquatic ecosystem sites on seven continents, derived from 190+ sources. It also includes extensive spatial and temporal metadata to link elemental stoichiometry with ecosystem type, trophic status, etc., and information on organismal data (body size, taxonomic classifications, stable isotope composition) and water physicochemical parameters. The Limno-STOICH database sets the stage for significant applications across food web ecology, evolutionary ecology, biogeochemistry, and other disciplines., Office of Experimental Program to Stimulate Competitive Research. Grant Number: OIA-2019596, Peer reviewed

R.N.F. was supported by the University of Bergen (Norway). This work was also sup-ported by the Spanish Ministry of Science, Innovation and Universities (MICIU/AEI/10.13039/501100011033), Grant no. PID2022-138066OB-I00 (to J.C.), and the Agency for Management of University and Research Grants (Government of Catalonia), Grant no. 2021 SGR 00068 (to J.C.). The authors also acknowledge the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S) funded by the Spanish Agencia Estatal de Investigación (AEI) 10.13039/501100011033, Peer reviewed

[Motivation] The accelerated and widespread conversion of once continuous ecosystems into fragmented landscapes has driven ecological research to understand the response of biodiversity to local (fragment size) and landscape (forest cover and fragmentation) changes. This information has important theoretical and applied implications, but is still far from complete. We compiled the most comprehensive and updated database to investigate how these local and landscape changes determine species composition, abundance and trait diversity of multiple taxonomic groups in forest fragments across the globe., [Main Types of Variables Contained] We gathered data for 1472 forest fragments, providing information on the abundance and composition of 9154 species belonging to vertebrates, invertebrates, and plants. For 2703 of these species, we obtained more than 20 functional traits. We provided the spatial location and size of each fragment and metrics of landscape composition and configuration., [Spatial Location and Grain] The dataset includes 1472 forest fragments sampled in 121 studies from all continents except Antarctica. Most datasets (77%) are from tropical regions, 17% are from temperate regions, and 6% are from subtropical regions. Species abundance and composition were collected at the plot or fragment scale, whereas the landscape metrics were extracted with buffer size ranging from a radius of 200–2000 m., [Time Period and Grain] Data on the abundance of species and community composition were collected between 1994 and 2022, and the landscape metrics were extracted from the same year that a given study collected the abundance and composition data., [Major Taxa and Level of Measurement] The studied organisms included invertebrates (Arachnida, Insecta and Gastropoda; 41% of the datasets), vertebrates (Amphibia, Squamata, Aves and Mammalia; 44%), and vascular plants (19%), and the lowest level of identification was species or morphospecies., [Software Format] The dataset and code can be downloaded on Zenodo or GitHub., This study was supported by the Institute for Global Change Biology in the School for Environment and Sustainability and the Department of Ecology and Evolutionary Biology at the University of Michigan. M.H.V. (#2022/01899-6, São Paulo Research Foundation—FAPESP), J.C.P. (#2018/00107-3), and F.R.d.S. (#2013/50714-0 and #2022/04012-2) were supported by grants from FAPESP. A.L. was supported by the project PRPPID2020-117863RB-I00 (MCIN/AEI/10.13039/501100011033). F.P.L.M. (470574/2013-5), M.B. (304189/2022-7), and L.F.S.M. (307984/2022-2) received support from CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico). M.V.G. was funded by UNILA (PRPPG 205/2021 and 77/2022). N.S. received support from Fundação Araucária (PBA2022011000042)., Peer reviewed

47 files.-- The dataset is used as a foundation for the scientific article Product Environmental Footprint (PEF) of gilthead seabream (Sparus aurata) juveniles fed side-streams from farmed blue mussel. This study analysed the environmental footprints of rearing juvenile gilthead seabream using Life Cycle Assessment (LCA) principles aligned with the Product Environmental Footprint (PEF) method. Data were collected from a research facility where fish juveniles were fed diets with fishmeal partially or fully substituted at 100%, 50%, or 0%, with blue mussel (Mytilus galloprovincialis) meal. The results showed that the use of electricity and the feed were the largest contributors to most impact categories. Electricity use was primarily driven by the indoor flow-through facility's high-water renewal and lighting requirements. The sensitivity analyses showed a high uncertainty related to impacts from the blue mussel production. This dataset is connected to the interdisciplinary research project SECURE (Novel Marine Resources for Food Security and Food Safety) which investigate the potential of low-trophic marine species. The overall goal of the project is to develop knowledge that enables sustainable food security. More information is available through https://en.uit.no/project/secure, Transparent and precise information on the environmental impacts of products is critical for informed decision-making. In the EU, gilthead seabream (Sparus aurata) is among the most profitable aquaculture species. The environmental impacts of aquaculture vary depending on input factors. Despite the importance of hatcheries and nurseries in aquaculture, there are currently several knowledge gaps related to footprints, particularly outside of salmonid life cycle assessments. This study analysed the environmental footprints of rearing juvenile gilthead seabream using Life Cycle Assessment (LCA) principles aligned with the Product Environmental Footprint (PEF) method. Data were collected from a research facility where fish juveniles were fed diets with fishmeal partially or fully substituted at 100%, 50%, or 0%, with blue mussel (Mytilus galloprovincialis) meal. The results showed that the use of electricity and the feed were the largest contributors to most impact categories. Electricity use was primarily driven by the indoor flow-through facility's high-water renewal and lighting requirements. The sensitivity analyses showed a high uncertainty related to impacts from the blue mussel production. The total environmental footprint of juveniles was significantly higher than that of fully grown finfish aquaculture per functional unit, mirroring the higher care required during early life stages. Blue mussel meal shows promise as a feed ingredient from a palatability and growth perspective, however, its use may increase environmental impacts. Nevertheless, as the aquaculture industry continues to expand to meet global food demands, utilising a current waste stream might be among few feasible options to cover nutrient demands in fish fee, UiT—The Arctic University of Norway: Cristin grant ID 2061344 European Union’s Horizon 2020 Research and Innovation Programme project AquaVitae: grant agreement number 818173 Fundação para a Ciência e Tecnologia: projects [UIDB/04326/2020], [UIDP/04326/2020], [LA/P/0101/2020] Xunta de Galicia: IN607B 2021/11, Peer reviewed

2 files, This dataset contains the source data used to generate the figures and statistical analyses presented in the manuscript “Temperature-driven decline in recalcitrant dissolved organic carbon weakens coastal macrophyte’s blue carbon storage potential”, Consejería de Universidad, Investigación e Innovación FINOCAME project (PCM_00104.C17.I03) Next Generation EU funds of the Recovery, Transformation and Resilience Plan Ministerio de Ciencia, Innovación y Universidades DAME (PDC2021-120792-100) project the European Union (Next Generation EU Recovery Funds) Recovery, Transformation and Resilience Plan Consejería de Economía, Conocimiento, Empresas y Universidad SER-CADY project [FEDER-UCA18-107451] project 2014-2020 ERDF Operational Programme and by the Department of Economic Transformation, Industry, Knowledge, and Universities of the Regional Government of Andalusia Ministerio de Ciencia, Innovación y Universidades Alba Yamuza Magdaleno FPU grant from the Spanish Ministry of Science, Innovation and Universities Ministerio de Ciencia, Innovación y Universidades Tomás Acárate-García Severo Ochoa FPI predoctoral grant (PRE2020-096185) of the Spanish Ministry of Science, Innovation and Universities through the “Severo Ochoa Centre of Excellence” Institute of Marine Sciences (ICM-CSIC) of Barcelona (CEX2019-000928-S) Alexander von Humboldt Foundation Pedro Beca-Carretero Humboldt Research Fellowship, Peer reviewed