BUSCADOR RECOLECTA

Four OBS are provided in the input folder, and the parfile. Readme explains how to run the code with this sample data., The work has been supported by projects CONNECT with reference PID2021-128851OA-I00, ATLANTIS (PID2019-109559RB-I00) and THREAT (PID2021-128513OA-I00), funded by the Spanish Ministry of Science and Innovation. ICM has also had funding support of the–Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI), Peer reviewed

1. Description of methods used for collection-generation of data: Grain size fraction (gravel, sand, silt, clay) was determined using a particle-size analyzer. Pb-210 was determined with alpha spectrometry. Metals were analyzed with an Inductively Coupled Plasma Mass Spectrometer. Total mercury was determined by atomic absorption spectrophotometric detection. 4. Instruments, calibration and standards information: Particle-size analyzer: Horiba Partica LA-950v2. Alpha spectrometry: Passivated Implanted Planar Silicon (PIPS) detectors (CANBERRA, Mod. PD-450.18 A.M). Inductively Coupled Plasma Mass Spectrometer: Agilent, 7900 model. Atomic absorption spectrophotometry: AMA-254. Standards for metals: Reference materials NIST 2702, IAEA 457 and MESS-3. 7. Quality-assurance procedures performed on the data: Standard measurements, The dataset Metals_Alorda-Montiel.csv includes data regarding sediment cores collected in the Mar Menor coastal lagoon. Each row corresponds to a sediment section id, which follows this structure: Corename depthmin - depthmax. Example: OPC1 0-1, which applies to the section from 0 to 1 cm from the core OPC1. The variables are Depth (in cm, and accounting for the medium depth of each section), Pb_210 (Pb-210 specific activity, in Bq/kg), Error_Pb_210 (Pb-210 specific activity error, in Bq/kg), Na (g/kg), Al (g/kg), Si (g/kg), P (mg/kg), S (g/kg), K (g/kg), Ca (g/kg), Ti (mg/kg), Cr (mg/kg), Fe (g/kg), Ni (mg/kg), Cu (mg/kg), Zn (mg/kg), As (mg/kg), Sr (mg/kg), Ag (mg/kg), Cd (mg/kg), Pb (mg/kg), Hg (mg/kg), Gravel (%), Sand (%), Silt (%) and Clay (%). The purpose of this dataset is to show the data used in the article "A Century of Sediment Metal Contamination of Mar Menor, Europe's Largest Saltwater Lagoon". (2024-12-03), This work was funded by the Agencia Estatal de Investigación (AEI) of the Spanish Ministry of Science and Innovation through the OPAL project (PID2019-110311RB-C21) and the WINDERS project (TED2021-130710B-I00). This work contributes to the María de Maeztu Programme (CEX2019-000940-M) for Units of Excellence of the Spanish Ministry of Science and Innovation. I.A-M acknowledges financial support from FPI grant PRE2020-092343. A.A-O acknowledges support from MCIN/AEI RYC2021-034455-I. J. R-P acknowledges financial support from FPU grant FPU20/01369. I. A-M, V. R., A. A-O., J. R-P. and J. G-O. belong to the consolidated group Marine and Environmental Biogeosciences Research Group - MERS, funded by grant 2021-SGR 00640 from the Direcció General de Recerca. A.P. belongs to the consolidated research group on littoral and oceanic processes, funded by grant 2021SGR 00433 from Generalitat de Catalunya. C. G-R thanks the sabbatical fellowship awarded by PASPA-DGAPA from Universidad Nacional Autónoma de México. M. D-F acknowledges financial support from grant JDC2022-050316-I funded by MCIN/AEI/10.13039/501100011033 and by the European Union - NextGenerationEU/PRTR, and support from the Grup d'Hidrologia Subterrània - GHS (Universitat Politècnica de Catalunya) funded by grant 2021-SGR 00609 from Generalitat de Catalunya. This work is contributing to the ICM 'Center of Excellence' Severo Ochoa (grant CEX2024-001494-S funded by Spanish Agency of Investigation grant AEI 10.13039/501100011033). This work is also part of the THINKINAZUL programme supported by the Spanish Ministry of Science and Innovation with funding from European Union NextGenerationEU (PRTR-C17.I1) and by Fundación Séneca with funding from Comunidad Autónoma Región de Murcia (CARM) (Spain). A. G. B. acknowledges funding from MerTerMar (PID2019-III722RJ-I00), Peer reviewed

Supplementary material for "Complex architecture of mud volcano systems: new insights on flow pathways unravel intricate fluid circulation" https://doi.org/10.1130/B37954.1, Shuhui Xu is supported by the China Scholarship Council (CSC), and Walter Menapace is supported by the H2020 MSCA-IF-TURBOMUD project (grant 101018321). This research was funded in part by the Austrian Science Fund (FWF; grant M 3146-417 N) and projects CTM2015-70155-R (INSIGHT) and PID2020-114856RB-100 (ICEFLAME) funded by the Spanish Ministry of Science and Innovation (MCIN/ AEI/10.13039/501100011033). The European project EUMarineRobots (EUMR) is acknowledged for cofunding the M167 expedition (grant 731103), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed

[Data description:] Excel file with variables used in model selection to analyse the reaction and breeding success probabilities of Bonelli’s Eagles. All variables are described in the document., Fieldwork for the long-term breeding monitoring was self-financed throughout the study period by J.E. Martínez., Peer reviewed

Climate change is impacting ecosystems worldwide, and the Mediterranean Sea is no exception. Extreme climatic events, such as marine heat waves (MHWs), are increasing in frequency, extent, and intensity during the last decades, which has been associated with an increase in mass mortality events for multiple species. Coralligenous assemblages, where the octocoral Paramuricea clavata lives, are strongly affected by MHWs. The Medes Islands Marine Reserve (NW Mediterranean) was considered a climate refugia for P. clavata, as their populations were showing some resilience to these changing conditions. In this study, we assessed the impacts of the MHWs that occurred between 2016 and 2022 in seven shallow populations of the octocoral P. clavata from a Mediterranean Marine Protected Area. The years that the mortality rates increased significantly were associated with the ones with strong MHWs, 2022 being the one with higher mortalities. In 2022, with 50 MHW days, the proportion of total affected colonies was almost 70%, with a proportion of the injured surface of almost 40%, reaching levels never attained in our study site since the monitoring was started. We also found spatial variability between the monitored populations. Whereas few of them showed low levels of mortality, others lost around 75% of their biomass. The significant impacts documented here raise concerns about the future of shallow P. clavata populations across the Mediterranean, suggesting that the resilience of this species may not be maintained to sustain these populations face the ongoing warming trends, This work was supported by the long-term monitoring programme of the marine natural parks of Catalonia, funded by Departament de Territori i Sostenibilitat of the Generalitat de Catalunya public agreements PTOP2017-130 and PTOP-2021-3. This work was also financially supported by Heatmed project RTI2018-095346-BI00 funded by Agencia Española de Investigación AEI MICIU/AEI/10.13039/501100011033 and ‘ERDF A way of making Europe’, and Corfun project TED2021-131622B-I00 funded by MICIU/AEI/10.13039/501100011033 and ‘European Union NextGenerationEU/PRT’. C.L acknowledges the support by Catalan Institution for Research and Advanced Studies ICREA. All authors are part of the Marine Conservation research group funded by Generalitat de Catalunya [2021 SGR 01073], Peer reviewed

With funding form the Spanish government through the "Severa Ochoa Centre of Excellence" accreditation (CEX2019-000928-S), This work was supported by the long-term monitoring program of the marine natural parks of Catalonia, funded by Departament de Territori i Sostenibilitat of the Generalitat de Catalunya public agreements PTOP2017-130 and PTOP-2021-3. This work was also financially supported by Heatmed project RTI2018-095346-BI00 funded by MICIU/AEI/10.13039/501100011033 and ‘ERDF A way of making Europe’, and Corfun project TED2021-131622B-I00 funded by MICIU/AEI/10.13039/501100011033 and ‘European Union NextGenerationEU/PRT’. P.C. was supported by the European Union-Next Generation EU Maria Zambrano Program (ZAMBRANO 21-26). C.L. acknowledges the support by ICREA Academia. All authors are part of the Marine Conservation research group [2021 SGR 01073], Peer reviewed

The zip. file contains information on a database, the explanation of each modification made to this database and a timetable used to input information onto this database. Database: Excel file with all data gathered from the systematic review using the PRISMA method (Page et al., 2021). The first sheet includes data on the general aspects of each publication, location, taxa, formal data, age, impacts and effect measures. Columns in grey were modified from the original data, while columns in white contain the original information. The second sheet presents the legend for each variable in the first sheet. Explanations of the database: Word document with the explanations made to each variable retried from the original publications (grey columns) and from which sources. Timetable: Word document with a table of terms regarding different geologic, climatic and cultural periods, divided by each subregion of the Mediterranean Sea, placed in time using the system years BP (Before Present), This work was supported by the Erasmus+ Program Grant no. 2022-1-PT01-KA131-HED-000061155. The author acknowledges the institutional support of the Severo Ochoa Centre of Excellence accreditation (CEX2019-000928-S). This research contributes to the objectives of Q-MARE (a PAGES working group). This research is part of the Integrated Marine Ecosystem Assessments (iMARES) research group funded by Agència de Gestió d'Ajuts Universitaris i de Recerca (Generalitat de Catalunya) Grant no. 2021 SGR 00435, Peer reviewed

[Methods] The data is a part of an extensive tree growth and drought monitoring network (www.treenet.info) in Switzerland. In this network, radial stem growth is derived from measurements of stem radius changes of trees with high-precision point dendrometers on mainly mature dominant trees. Tree radial growth was measured at about 1.3 m above the ground. The data was recorded and transmitted with Decentlab data transfer nodes (Decentlab GmbH, Duebendorf, Switzerland) with a logging resolution <1 µm at every 5-10 mins. The measurements were processed to a 10-min time aligned data set using the R-package ‘treenetproc’, including outlier removal, jump correction and linear interpolation of short gaps. Radial growth data, extracted with the zero-growth assumption were aggregated on a daily, weekly, monthly, and yearly sum basis. As growth strongly varies within individual trees, across years, species, sites and climatic regions, annual growth was standardized by converting it to relative annual growth. This was done by calculating the difference between each tree’s annual growth to its tree-specific long-term average, calculated over the available data from 2012 to 2022. Air temperature (°C) data was obtained from weather stations www.meteoswiss.admin.ch, mean distance: 8 km, max: 15 km) or were measured at the site and aggregated to daily values. Air temperature and relative humidity (%) at the sites were measured at 2 m height within the forest stands. Precipitation was extracted from MeteoSwiss model generated CombiPrecip combining data from weather stations and precipitation radar. The vapour pressure deficit (VPD, in kPa) was calculated using temperature and relative humidity. Soil water potential (SWP) was measured with dielectric MPS-2/MPS-6 sensors (Decagon Devices, Pullman, US) at 10-20 cm soil depth at each site and the values were corrected for soil temperature fluctuations. All analyses, including statistical model runs and figures, were produced using the R statistical software., Recent findings suggest that global warming is altering the timing of trees’ phenological activities including earlier emergence from winter dormancy. While early-season warming can boost carbon uptake, tree growth does not seem to benefit. The underlying mechanisms and the altered intra- and inter-annual growth dynamics, as well as their interaction with environmental factors, remain poorly understood. We analysed daily-resolved dendrometer data from 228 trees across 48 Swiss forest sites over 2012–2022 to examine stem radial growth timing, intra- and inter-annual dynamics, and environmental controls for five tree species. We examined how weekly tree growth is related to envrionmental variables including day length, temperature, preciipitation, vapor pressure deficit, soil water potential and their interactions. We found a significant negative growth trend for Picea abies, Abies alba, and Fagus sylvatica across a wide climatic gradient. The reduction in growth was associated with the decrease in number of days with growth. The positive effect of higher temperatures in spring was canceled out by a negative effect towards the end of the growth period. Overall, such negative effect of increased temperature at annual scale was strongest in Pinus sylvestris and persisted over 2012-2022. To provide a comprehensive understanding of the data analysis process, we have uploaded an R script that details all analyses and datasets used. The script includes thorough documentation of the analyses corresponding to each figure, table, and supplementary material. The dataset contains information on tree growth, site characteristics, and the environmental conditions in which the trees are growing. It is available for reuse in other scientific studies, with no legal or ethical restrictions., Federal Office for the Environment : 00.5053. PZ / 935559972, Peer reviewed

R codes for the publication: Blanca Figuerola, Pol Capdevila, Marc Cerdà-Domènech, Joaquim Garrabou, Alice Mirasole, Pol Bassols, Javier del Campo, Núria Teixidó. Interactive effects of ocean acidification and warming disrupt calcification and microbiome composition in bryozoans, BF has received funding by a Ramon y Cajal grant (RYC2022-036268-I) funded by MICIU/AEI/10.13039/501100011033 and FSE + , a Beatriu de Pinós grant (2019 BP 00183), from the Catalan Government and the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 801370, and by a Juan de la Cierva- Incorporación grant (IJCI-2017-31478) from the Ministry of Science and Innovation. This work has been developed in the framework of the MedCalRes project Grant PID2021-125323OA-I00 to BF funded by MICIU/AEI/10.13039/501100011033 and ERDF/EU. BF and JG acknowledge the grant CEX2024-001494-S funded by AEI 10.13039/501100011033. JG acknowledges the funding by the European Union Horizon 2020 research and innovation program (Futuremares SEP-210597628). NT was supported by the Agence Nationale de la Recherche (4Oceans, MOPGA, grant no. ANR-17-MOPGA-0001) and the National Recovery and Resilience Plan (NRRP), Mission 4 Component 2 Investment 1.4 - Call for tender No. 3138 of 16 December 2021, rectified by Decree n.3175 of 18 December 2021 of Italian Ministry of University and Research funded by the European Union – NextGenerationEU; Award Number: Project code CN_00000033, Concession Decree No. 1034 of 17 June 2022 adopted by the Italian Ministry of University and Research, CUP C63C22000520001 Project title “National Biodiversity Future Center - NBFC. BF, PC, and JG are part of the Marine Conservation research group funded by Generalitat de Catalunya [2021 SGR 01073], Peer reviewed

One file is for demultiplexing the plant metabarcoding dataset, generated using the trnL p6-loop gh primers of Taberlet et al. The other is for the animal metabarcoding dataset, generated using the 16S MamP007 primers of Giguet-Covex et al. Each file contains forward and reverse primer tags for eight PCR replicates applied to 844 sediment samples or controls, together with European Nucleotide Archive (ENA) accession codes for their associated amplicon libraries, which are publicly available at ENA projects PRJEB85748 and PRJEB52290. Sequencing facilities GSCT: Genomics Support Centre Tromsø TMU: The Arctic University Museum of Norway NCFS: Norwegian College of Fishery Science, I.G.A. and Y.L. were supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 819192) and the ECOGEN project “Ecosystem change and species persistence over time: A genome-based approach,” financed by Research Council of Norway grant 250963/F20, the latter also supported P.D.H., S.G.-P., and S.Z., most fieldwork, and other running costs. Open access funding was provided by UiT The Arctic University of Norway. S.G.-P. was also supported by the Beatriu de Pinós Programme (BP-2021-00131) and a fellowship from “la Caixa” Foundation (ID 100010434, fellowship code LCF/BQ/PI24/12040011). P.D.H. acknowledges support from the Knut and Alice Wallenberg Foundation (KAW 2021.0048 and KAW 2022.0033). Coring and stratigraphic analyses at Lake Sulzkar were funded through an Earth System Sciences grant from the Austrian Academy of Sciences: “Pulling the plug—Restoration of an Alpine lake”. Coring at Lakes Sangiatto, Hopschu, Emines, Bretaye, and Sulsseewli was supported by the Oeschger Centre for Climate Change Research (OCCR) as part of the Graduate School of Climate Sciences at the University of Bern. The PhyloAlps reference database was built thanks to the following projects: the joint ANR-SNF project Origin-Alps (ANR-16-CE93-0004, SNF-310030L_170059), European Research Council under the European Community’s Seventh Framework Programme FP7/2007-2013 grant agreement 281422 (TEEMBIO), and by the SNF grant 31003A_149508. The sequencing for the PhyloAlps reference database was performed within the framework of the PhyloAlps project, funded by France Génomique (ANR-10-INBS-09-08), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed