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Dataset are structured following well-established data formats Darwing Core. Three files are provided. The first file (Don_liz-gec_event_20221201) contains the information of the project, the institution and the description each event (time of occurrence, geographical coordinates, habitat type, etc…); the second file (Don_liz-gec_occ_20221201) contains the information of the occurrences of species recorded in each transect, taxonomic classification, geographoical coordinates of its observation, etc…; and the third file (Don_liz-gec_mof_20221201) provide information of the description of other variables measured during counts., The monitoring of lizards and geckos’ community in Doñana was initiated in 2005 as part of the monitoring program of natural resources and processes. One of the aims of this project was to obtain a temporal and continuous series of data of the presence and abundance of these species to detect changes and trends in their wild populations within the protected area. Lizard and gecko counts are collected annually by members of the monitoring team three times per year in the periods when reptile activity is high (two samplings in March-June and one sampling in September-October), with good environmental conditions (temperature between 17 and 25 ºC and absence of rain or strong wind conditions). The method used to record the presence and abundance of lizard and gecko species (kilometric index: number of individuals/km) are the transect censuses. Individuals are visually searched along seven transects (linear or circular) that are carried out by one trained person on foot. Each transect have an established length, but the length surveyed is different (averaged 1858 ± 51.86 meters). Each transect is located in dunes or mediterranean vegetation habitats, representative of Doñana ecosystems. Two transects runs through wooden footpaths (within the Natural Park and five transects are placed on sand-trails (4 within the National Park and one in Natural Park which contains a small part of wooden footpath). Linear transects have been surveyed in the outward track direction and after waiting 15 minutes it has been again performed on the way back. This information is valid to account for species presence in the area. However, we suggest to choose the first survey performed for statistical analyses that require independence of samples. Eight species can be potentially observed during the samplings: Mediterranean house gecko (Hemidactylus turcicus), Common Wall Gecko (Tarentola mauritanica), Fringe-fingered Lizard (Acanthodactylus erythrurus), Algerian Psammodromus (Psammodromus algirus), Western Psammodromus (Psammodromus occidentalis), Carbonell's wall lizard (Podarcis carbonelli), Andalusian wall lizard (Podarcis vaucheri), Ocellated lizard (Timon lepidus). Other reptile species present in Doñana have not been included in this study as the detection with this method is very low. For instance, to detect species with a fossorial behaviour (the Mediterranean Worm Lizard Blanus cinereus) or those cryptic as adders (Vipera latastei), it is required larger investment of survey which consist in looking under vegetation, burrows or logs (there are not stones in Doñana). Data recorded during the surveys include weather description (cloud cover, temperature, rain, or wind speed), species identification, number of individuals, sex and life stage of the reptiles when possible, as well as time and georeferenced data of the observation. Between 2005-2007 data was registered in Excel file and since 2008 data is recorded with the app CyberTracker (see protocol). The protocol used has been supervised by herpetological researchers and the data have been validated by the members who performed the transects., We acknowledge financial support from National Parks Autonomous Agency (OAPN) between 2002-2007; Singular Scientific and Technical Infrastructures from the Spanish Science and Innovation Ministry (ICTS-MICINN); Ministry of Agriculture, Livestock, Fisheries and Sustainable Development from the Regional Government of Andalusia (CAGPDES-JA) since 2007; and Doñana Biological Station from the Spanish National Research Council (EBD-CSIC) since all the study period (2005)., 1. Don_liz-gec_event_20221201: eventID, institutionCode, institutionID, datasetName, continent, country, countryCode, Province, Location, Locality, LocalityID, eventDate, eventTime, decimalLatitude, decimalLongitude, decimalLatitudeEnd, decimalLongitudeEnd, verbatimCoordinate_func, verbatimCoordinate, habitat, sampleSizeValue, sampleSizeUnit, samplingEffort, recordedBy, samplingProtocol.-- 2. Don_liz-gec_occ_20221201: RecordedBy, eventID, OccurrenceID, OcurrenceTime, decimalLatitude, decimalLongitude, basisOfRecord, individualCount, lifeStage, sex, OccurrenceRemarks, behavior, kingdom, Class, Family, scientificName, genus, specificEpithet, scientificNameAuthorship, taxonRank.-- 3. Don_liz-gec_mof_20221201: eventID, measurementID, measurementType, measurementValue, measurementUnit, measurementMethod., Peer reviewed

This Excel file includes the data and tracked calculations of the manuscript entitled "Sponge contribution to the silicon cycle of a diatom-rich shallow bay". It includes 7 spreadsheets with the following contents: - READ ME - Standing STOCK living sponges - Sponge Si consumption FLUX - Si RESERVOIR in sediments - Sponge Si FLUXES in sediments - DIATOM Si fluxes&stocks (Fig.5) - Calculations for discussion, This research was supported by: - the Spanish Ministry grants CTM2015-67221-R and MICIU: #PID2019-108627RB-I00 to Manuel Maldonado - the grant 12735 – AO2020 of the French National research program EC2CO to Jacques Grall - the ISblue project, Interdisciplinary graduate school for the blue planet (ANR-17-EURE-0015), co-funded by a grant from the French government under the program "Investissements d'Avenir", and the “Xunta de Galicia” postdoctoral grant IN606B-2019/002 to María López-Acosta., Peer reviewed

This Excel file includes the metadata of the survey of the predation activity of the nudibranch Doris verrucosa on the sponge Hymeniacidon perlevis, This research was supported by: - the grant 12735 – AO2020 of the French National research program EC2CO - the ISblue project, Interdisciplinary graduate school for the blue planet (ANR-17-EURE-0015), co-funded by a grant from the French government under the program "Investissements d'Avenir", and the “Xunta de Galicia” postdoctoral grant IN606B-2019/002, No

Temporal changes in plant cover, functional composition and diversity. This file contains all the data used in the different statistical analyses of this study in order to answer the following questions: : (i) how sensitive are Mediterranean shrubland communities to inter-annual variability in climate?; (ii) are communities with higher functional diversity more stable against climatic fluctuations?; and (iii) are shrubland communities growing on poorer soils more stable over time than those located on resource-richer soils? Dataset_Pérez-Ramos et al. 2017.xlsx, 1.Understanding how different factors mediate the resistance of communities to climatic variability is a question of considerable ecological interest that remains mostly unresolved. This is particularly remarkable to improve predictions about the impact of climate change on vegetation. 2.Here we used a trait-based approach to analyse the sensitivity to climatic variability over nine years of 19 Mediterranean shrubland communities located in southwest Spain. We evaluated the role of functional diversity and soil environment as drivers of community stability (assessed as changes in plant cover, species diversity and composition). 3.The studied shrubland communities were strongly sensitive to inter-annual variability in climate. First, colder and drier conditions caused remarkable decreases in total plant cover but increased functional diversity, likely because the reduction of plant cover after harsh climatic conditions promoted the expansion of functionally dissimilar species in the new open microsites; although communities returned to their initial values of plant cover after nine years, changes in functional diversity and structure persisted over time. Second, drier and colder conditions favoured the predominance of shrubs with a conservative resource-use strategy (i.e. with higher dry matter content in leaves, stems and roots), bigger seeds and a more efficient use of water. 4.The most functionally diverse communities were the most stable over time in terms of species diversity, likely because a higher number of functionally dissimilar species allowed compensatory dynamics among them. 5.Communities inhabiting more acidic and resource-limited environments were less variable over time, probably because they were mainly constituted by slow-growth, stress-tolerant species that are potentially better adapted to harsh climatic conditions. 6.Synthesis: This study highlights the utility of a trait-based approach to evaluate how plant communities respond to climatic variability. We could infer that the increased frequency of extreme climatic events predicted by climatic models will alter the functional structure of shrubland communities, with potential repercussions for ecosystem functioning. Our results also provide new insights into the role of functional diversity and soil environment as buffers of the climate impact on woody communities, as well as potentially useful information to be applied in ecologically-based management and restoration strategies., Peer reviewed

[Description of methods used for collection/generation of data] In both stations a SAMI-pH (Sunburst Sensors LCC) was attached, at 1 m in the Bay of Palma and at 4 m depth in Cabrera. The pH sensors were measuring pH, in the total scale (pH𝑇T), hourly since December 2018 in the Bay of Palma and since November 2019 in Cabrera. The sensor precision and accuracy are < 0.001 pH and ± 0.003 pH units, respectively. Monthly maintenance of the sensors was performed including data download and surface cleaning. Temperature and salinity for the Cabrera mooring line was obtained starting November 2019 with a CT SBE37 (Sea-Bird Scientific©). Accuracy of the CT is ± 0.002 ∘C for temperature and ± 0.003 mS cm−1−1 for conductivity. Additionally, oxygen data from a SBE 63 (Sea-Bird Scientific ©) sensor attached to the CT in Cabrera were used. Accuracy of oxygen sensors is ± 2% for the SBE 63., [Methods for processing the data] Periodically water samplings for dissolved oxygen (DO), pH in total scale at 25 ∘C (pH𝑇25) and total alkalinity (TA) were obtained during the sensor maintenance campaigns. DO and (pH𝑇25) samples were collected in order to validate the data obtained by the sensors. DO concentrations were evaluated with the Winkler method modified by Benson and Krause by potentiometric titration with a Metrohm 808 Titrando with a accuracy of the method of ± 2.9 μmol kg−1μmol kg−1 and with an obtained standard deviation from the sensors data and the water samples collected of ± 5.9 μmol kg−1μmol kg−1. pH𝑇25T25 data was obtained by the spectrophotometric method with a Shimadzu UV-2501 spectrophotometer containing a 25 ∘C-thermostated cells with unpurified m-cresol purple as indicator following the methodology established by Clayton and Byrne by using Certified Reference Material (CRM Batch #176 supplied by Prof. Andrew Dickson, Scripps Institution of Oceanography, La Jolla, CA, USA). The accuracy obtained from the CRM Batch was of ± 0.0051 pH units and the precision of the method of ± 0.0034 pH units. The mean difference between the SAMI-pH and discrete samples was of 0.0017 pH units., Funding for this work was provided by the projects RTI2018-095441-B-C21 (SuMaEco) and, the BBVA Foundation project Posi-COIN and the Balearic Islands Government projects AAEE111/2017 and SEPPO (2018). SF was supported by a “Margalida Comas” postdoctoral scholarship, also from the Balearic Islands Government. FFP was supported by the BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033.This work is a contribution to CSIC’s Thematic Interdisciplinary Platform PTI WATER:iOS., Peer reviewed

[Description of methods used for collection/generation of data] Data was acquired in both stations using a SAMI-pH (Sunburst Sensors LCC) was attached, at 1 m in the Bay of Palma and at 4 m depth in Cabrera. The pH sensors were measuring pH, in the total scale (pH𝑇), hourly since December 2018 in the Bay of Palma and since November 2019 in Cabrera. The sensor precision and accuracy are < 0.001 pH and ± 0.003 pH units, respectively. Monthly maintenance of the sensors was performed including data download and surface cleaning. Temperature and salinity for the Cabrera mooring line was obtained starting November 2019 with a CT SBE37 (Sea-Bird Scientific©). Accuracy of the CT is ± 0.002 ∘C for temperature and ± 0.003 mS cm−1−1 for conductivity. Additionally, oxygen data from a SBE 63 (Sea-Bird Scientific ©) sensor attached to the CT in Cabrera were used. Accuracy of oxygen sensors is ± 2% for the SBE 63., [Methods for processing the data] Once data (available at https://doi.org/XXX/DigitalCSIC/XXX) was validated, several processing steps were performed to ensure an optimal training process for the neural network models. First, all the data of the time series were re-sampled by averaging the data points obtaining a daily frequency. Afterwards, a standard feature-scaling procedure (min-max normalization) was applied to every feature (temperature, salinity and oxygen) and to pHT. Finally, we built our training and validations sets as tensors with dimensions (batchsize, windowsize, 𝑁features), where batchsize is the number of examples to train per iteration, windowsize is the number of past and future points considered and 𝑁features is the number of features used to predict the target series. Temperature values below 𝑇=12.5T=12.5 °C were discarded as they are considered outliers in sensor data outside the normal range in the study area. A BiDireccional Long Short-Term Memory (BD-LSTM) neural network was selected as the best architecture to reconstruct the pHT time series, with no signs of overfitting and achieving less than 1% error in both training and validation sets. Data corresponding to the Bay of Palma were used in the selection of the best neural network architecture. The code and data used to determine the best neural network architecture can be found in a GitHub repository mentioned in the context information., Funding for this work was provided by the projects RTI2018-095441-B-C21, RTI2018-095441-B-C22 (SuMaEco) and Grant MDM-2017-0711 (María de Maeztu Excellence Unit) funded by MCIN/AEI/10.13039/501100011033 and by the “ERDF A way of making Europe", the BBVA Foundation project Posi-COIN and the Balearic Islands Government projects AAEE111/2017 and SEPPO (2018). SF was supported by a “Margalida Comas” postdoctoral scholarship, also from the Balearic Islands Government. FFP was supported by the BOCATS2 (PID2019-104279GB-C21) project funded by MCIN/AEI/10.13039/501100011033.This work is a contribution to CSIC’s Thematic Interdisciplinary Platform PTI WATER:iOS (https://pti-waterios.csic.es/)., Peer reviewed

Dataset are structured following well-established data formats. Three files are provided. The first file (Meta-data) contains the information of each event (time of occurrence, geographical coordinates, Ecosystem, Sampling mehtod, etc…); the second file (Fish) contains the information of the occurrences of fish species recorded in each station, taxonomic classification, etc…; and the third file (Macroinvertebrates) provide information of the occurrences of macroinvertebrates recorded in each station, taxonomic classification, abundance clases, etc…, The monitoring of the macroinvertebrates and fish community in Doñana wetlands was initiated in 2004 as part of the Monitoring Program of Natural Resources and Processes. The aim was to obtain a temporal and continuous series of data in the abundance and distribution of macroinvertebrates and fish species to analyze the evolution of their numbers and estimates biodiversity values. Data were recorded annually between 2004-2019 by more than 2 members of the monitoring team which performed samplings in different locations twice per year in winter-spring and summer seasons when the study sites are flooded. The macroinvertebrates and fishes were sampled at the 140 stations classified according to their location (on either aeolian sands or marshland). Funnel traps were used as a sampling method. Between 5-9 funnel traps were randomly distributed (until 50 cm of depth) in each location, depending of the flooded area and depth. The traps were left for 24 hours and emptied the content into white sorting pans. Individuals were counted and identified until the maximun taxonomic level in the field and realease. During samplings, it was identified 66 and 16 families, of macroinvertebrates and fishes respectively. The most abundances were Notonectidae and Corixidae in macroinvertebrates, and Poecilidae and Cyprinidae in fishes. Data recorded during the surveys included species identification, number of individuals, sex and life stage (pupa, larvae, inmature, adult) of the organisms when possible, as well as the time and georreferenced data of the observation. Between 2004-2007 data was registered in Excel file and since 2008 data was recorded in CyberTracker sequence). The protocol used has been supervised by researchers and the data have been validated by the members who performed the sampling., We acknowledge financial support from National Parks Autonomous Agency (OAPN) between 2002-2007; Singular Scientific and Technical Infrastructures from the Spanish Science and Innovation Ministry (ICTS-MICINN); Ministry of Agriculture, Livestock, Fisheries and Sustainable Development from the Regional Government of Andalusia (CAGPDES-JA) since 2007; and Doñana Biological Station from the Spanish National Research Council (EBD-CSIC) since all the study period (2005)., 1. Metadata: Taxa group, Site ID, Site name, Country, y coordinate, x coordinate, Ecosystem River/lake name, Sampling method, Starting year, Ending year, 1st Name, 1st Mail, 2nd Name, 2nd Mail, 3rd Name, 3rd Mail.-- 2. Fish: Site ID, Sample ID, Sampling date, Taxon name, Taxon ID, Definition of abundance class, Abundance class.-- 3. Macroinvertebrates: Site ID, Sample ID, Sampling date, Taxon name, Taxon ID, 0+, 1+, Adult, All., Peer reviewed

Dataset are structured following well-established data formats. Two files are provided. The first file (icts-rbd-dungBe_event_20221107) contains the information of each event (time of occurrence, geographical coordinates, habitat, sampling effort, etc…); the second file (icts-rbd-dungBe_occ_20221107) contains the information of the occurrences of dung-beetles species recorded in each site, numbers of individual recorded and taxonomic classification., The monitoring of the roller dung-beetles (Scarabaeinidae) in Doñana, southwestern Spain, was initiated in 2004 as part of the Monitoring Program of Natural Resources and Processes. The aim was to obtain a temporal and continuous series of data in the abundance and distribution of two species (Scarabeus sacer and S. cicatricosus) present in the area. Data were recorded annually from 2004 to 2012 by members of the monitoring team which performed one sampling (between May and August) in different habitats (sand dunes, mediterranean schrublands, flooplain meadows, and marshlands). Dung-baited pitfalls traps were used as a method to obtain samples of individuals of the two species. These traps were plastic cilinder of 30 cm diameter x 20 cm high buried on the ground. A baited grill of 2cm x 2 cm mesh rested on top of the trap. Bait was fresh horse or cow feaces (250 g) collected around the area early in the morning the day before of trapping. Five pitfall traps were established at each site separated 15 m each other during 24 hours. Two checking were conducted every 12 hours after baiting to avoid the mortality of individuals. Individual of each species were counted and release after it. Data recorded during the surveys included species identification and number of individuals. Between 2004-2008 data was registered in Excel file and since 2008 data was recorded in CyberTracker sequence. The protocol used has been supervised by researchers and the data have been validated by the members who performed the sampling., We acknowledge financial support from National Parks Autonomous Agency (OAPN) between 2004-2007; Singular Scientific and Technical Infrastructures from the Spanish Science and Innovation Ministry (ICTS-MICINN); Ministry of Agriculture, Livestock, Fisheries and Sustainable Development from the Regional Government of Andalusia (CAGPDES-JA) since 2007; and Doñana Biological Station from the Spanish National Research Council (EBD-CSIC) since all the study period (2004-2012)., 1.icts-rbd-dungBeetles_event_20221107: intitutionCode, institutionID, datasetName, eventID, eventDate, eventTime, continent, country, countryCode, stateProvince, locality, decimalLatitude, decimalLongitude, habitat, eventRemarks, sampleSizeValue, sampleSizeUnit, sampleEffort, dynamicPropertiesEvents, recordyBy and scientificName 2.icts-rbd-dungBeetles_occ_20221107: eventID, OccurrenceID, basisOfRecords, individualCount, kingdom, class, family, scientificName, genus, specificEpithet and scientificNameAuthorship., Peer reviewed

Dataset are structured following well-established data formats. Three files are provided. The first file (Don_macroinv_ev_20221222) contains the information of each event (eventID, event date, geographical coordinates, sample effort, etc…); the second file (Don_macroinv_occ_20221222) contains the information of the occurrences of individuals recorded in each station and its taxonomic classification; and the third file (Don_macroinv_mof_20221222) provide information of biometric variable (weithg) of macroinvertebrates samples recorded in each occurrence., The monitoring of the macroinvertebrates community in Doñana wetlands was initiated in 2004 as part of the Monitoring Program of Natural Resources and Processes. The aim was to obtain a temporal and continuous series of data in the abundance and distribution of macroinvertebrates species to analyze the evolution of their numbers and estimates biodiversity values. Data were recorded annually between 2004-2019 by more than 2 members of the monitoring team which performed samplings in different locations twice per year in winter-spring and summer seasons when the study sites are flooded. The macroinvertebrates were sampled at the 139 stations classified according to their location (on either aeolian sands or marshland). Funnel traps were used as a sampling method. Between 5-9 funnel traps were randomly distributed (until 50 cm of depth) in each location, depending of the flooded area and depth. The traps were left for 24 hours and emptied the content into white sorting pans. Individuals were counted and identified until the maximun taxonomic level in the field and realease. During samplings, it was identified 65 families. The most abundances were Notonectidae and Corixidae. Data recorded during the surveys included species identification, number of individuals, sex and life stage (pupa, larvae, juvenile, adult) of the organisms when possible, as well as the time and georreferenced data of the observation. Between 2004-2007 data was registered in Excel file and since 2008 data was recorded in CyberTracker sequence). The protocol used has been supervised by researchers and the data have been validated by the members who performed the sampling., We acknowledge financial support from National Parks Autonomous Agency (OAPN) between 2002-2007; Singular Scientific and Technical Infrastructures from the Spanish Science and Innovation Ministry (ICTS-MICINN); Ministry of Agriculture, Livestock, Fisheries and Sustainable Development from the Regional Government of Andalusia (CAGPDES-JA) since 2007; and Doñana Biological Station from the Spanish National Research Council (EBD-CSIC) since all the study period (2005)., 1. Don_macroinv_ev_20221222: eventID, intitutionCode, datasetName, eventDate, year, month, day, continent, country, stateProvince, location, localityID, locality, sampleSizeUnit, sampleSizeEffort, DynamicPropiertiesEvent, eventRemarks, recordedBy.-- 2. Don_macroinv_occ_20221222: eventID, occurrenceID, basisOfRecord, individualCount, sex, lifeStage, kingdom, phylum, order, family, genus, specificEpithet, scientificName.-- 3. Don_macroinv_mof_20221222: ocurrenceID, measurementID, measurementValue, measurementUnit, measurementType, measurementAccuracy, measurementMethod., Peer reviewed

Dataset are structured following well-established data formats. Three files are provided. The first file (Don_fish_ev_20221222) contains the information of each event (eventID, event date, geographical coordinates, sample effort, etc…); the second file (Don_fish_occ_20221222) contains the information of the occurrences of fish species recorded in each station, taxonomic classification; and the third file (Don_fish_mof_20221222) provide information of the biometric variable (weight) of fish sample in each occurrence., The monitoring of the fish community in Doñana wetlands was initiated in 2004 as part of the Monitoring Program of Natural Resources and Processes. The aim was to obtain a temporal and continuous series of data in the abundance and distribution of fish species to analyze the evolution of their numbers and estimates biodiversity values. Data were recorded annually between 2004-2019 by more than 2 members of the monitoring team which performed samplings in different locations twice per year in winter-spring and summer seasons when the study sites are flooded. The fishes were sampled at the 139 stations classified according to their location (on either aeolian sands or marshland). Funnel traps were used as a sampling method. Between 5-9 funnel traps were randomly distributed (until 50 cm of depth) in each location, depending of the flooded area and depth. The traps were left for 24 hours and emptied the content into white sorting pans. Individuals were counted and identified until the maximun taxonomic level in the field and realease. During samplings, it was identified 15 families. The most abundances were Poecilidae and Cyprinidae. Data recorded during the surveys included species identification, number of individuals, sex and life stage (pupa, larvae, inmature, mature) of the organisms when possible, as well as the time and georreferenced data of the observation. Between 2004-2007 data was registered in Excel file and since 2008 data was recorded in CyberTracker sequence). The protocol used has been supervised by researchers and the data have been validated by the members who performed the sampling., We acknowledge financial support from National Parks Autonomous Agency (OAPN) between 2002-2007; Singular Scientific and Technical Infrastructures from the Spanish Science and Innovation Ministry (ICTS-MICINN); Ministry of Agriculture, Livestock, Fisheries and Sustainable Development from the Regional Government of Andalusia (CAGPDES-JA) since 2007; and Doñana Biological Station from the Spanish National Research Council (EBD-CSIC) since all the study period (2005)., 1. Don_fish_ev_20221222: eventID, intitutionCode, institutionID, datasetName, eventDate, year, month, day, country, stateProvince, location, localityID, locality, decimalLatitude, decimalLongitude, habitat, sampleSizeUnit, sampleSizeEffort, DynamicPropiertiesEvent, eventRemarks, recordeBy.-- 2. Don_fish_occ_20221222: eventID, occurrenceID, individualCount, sex, lifeStage, kingdom, phylum, order, family, genus, specificEpithet, scientificName.-- 3. Don_fish_mof_20221222: OccurrenceID, measurementID, measurementType, measurementValue, measurementUnit, measurementMethod., Peer reviewed