BUSCADOR RECOLECTA

[Methods] Experiment locations and climate Trans-Mediterranean translocation of Posidonia oceanica fragments took place between Catalunya (Spain), Mallorca (Spain) and Cyprus in July 2018 and were monitored until July 2019 (Fig. 1). Sea surface temperature data for each transplant site were based on daily SST maps with a spatial resolution of 1/4°, obtained from the National Center for Environmental Information (NCEI, https://www.ncdc.noaa.gov/oisst ) (Reynolds et al. 2007). These maps have been generated through the optimal interpolation of Advanced Very High Resolution Radiometer (AVHRR) data for the period 1981-2019. Underwater temperature loggers (ONSET Hobo pro v2 Data logger) were deployed at the transplant sites in Catalunya, Mallorca and Cyprus and recorded hourly temperatures throughout the duration of the experiment (one year). In order to obtain an extended time series of temperature at transplant sites, a calibration procedure was performed comparing logger data with sea surface temperature from the nearest point on SST maps. In particular, SST data were linearly fitted to logger data for the common period. Then, the calibration coefficients were applied to the whole SST time series to obtain corrected-SST data and reconstruct daily habitat temperatures from 1981-2019. Local climate data was also compared to the global thermal distribution of P. oceanica to assess how representative experimental sites were of the thermal distribution of the species (Supplementary materials). Collectively, seawater temperatures from the three locations span the 16th - 99th percentile of temperatures observed across the global thermal distribution of P. oceanica. As such Catalunya, Mallorca and Cyprus are herein considered to represent the cool-edge, centre and warm-edge of P. oceanica distribution, respectively. Transplantation took place toward warmer climates and procedural controls were conducted within each source location, resulting in six source-to-recipient combinations (i.e. treatments, Fig. 1). Initial collection of P. oceanica, handling and transplantation was carried out simultaneously by coordinated teams in July 2018 (Table S1). Each recipient location was subsequently resampled four times over the course of the experiment, in August/September 2018 (T1), October 2018 (T2), April 2019 (T3) and May/June 2019 (T4, Table S1). Between 60-100 fragments were collected for each treatment. A fragment was defined as a section of P. oceanica containing one apical shoot connected with approximately five vertical shoots by approximately 10-15 cm of rhizome with intact roots. Collection occurred at two sites within each location, separated by approximately 1 km. Within sites, collections were conducted between 4 – 5 m depth and were spaced across the meadow to minimise the dominance of a single clone and damage to the meadow. Upon collection, fragments were transported for up to one hour back to the nearest laboratory in shaded seawater. Handling methods In the laboratory, fragments were placed into holding tanks with aerated seawater, at ambient temperature and a 14:10 light-dark cycle. All shoots were clipped to 25 cm length (from meristem to the tip of the longest leaves), to standardise initial conditions and reduce biomass for transportation. For transport by plane or ferry between locations, fragments were packed in layers within cool-boxes. Each layer was separated by frozen cool-packs wrapped in wet tea towels (rinsed in sea water). All fragments spent 12 hrs inside a cool-box irrespective of their recipient destination, including procedural controls (i.e. cool-cool, centre-centre and warm-warm) to simulate the transit times of the plants travelling furthest from their source location (Fig. 1a). On arrival at the destination, fragments were placed in holding tanks with aerated seawater at ambient temperature as described above in their recipient location for 48 hrs, prior to field transplantation. Measurement methods One day prior to transplantation, fragments were tagged with a unique number and attached to U-shaped peg with cable-ties. Morphological traits for each fragment were measured and included: 1) length of the longest apical leaf, width and number of leaves 2) total number of bite marks on leaves of three vertical shoots per fragment, 3) number of vertical shoots, 4) leaf count of three vertical shoots per fragment and 5) overall horizontal rhizome length. A subset (n=10) of fragments per treatment were marked prior transplantation to measure shoot growth. To do this, all shoots within a single fragment were pierced using a hypodermic needle. Two holes were pierced side-by-side at the base of the leaf/top of the meristem. Transplant methods All transplant sites were located in 4 – 5 m depth in area of open dead-matte, surrounded by P. oceanica meadow. In Mallorca and Cyprus, fragments were distributed between two sites, separated by approximately 1 km. In Catalunya, a lack of suitable dead matte habitat, meant that all fragments were placed in one site. Fragments were planted along parallel transects at 50 cm intervals and with a 50 cm gap between parallel transects (Fig. S1). Different treatments were mixed and deployed haphazardly along each transect. Resampling methods and herbivory On day 10 of the experiment, a severe herbivory event was recorded at both warm-edge translocation sites. Scaled photos of all fragments were taken at this time to record the effects of herbivory on transplants. At the end of each main sampling period (T0 – T1, T1-T2 and T3 – T4), all pierced fragments were collected and taken back to the laboratory to measure shoot growth. At T1, T2 and T3, additional sets of fragments (n = 10 per treatment) were marked using the piercing method to record growth in the subsequent time period. In addition, at T1 and T3, n = 20 shoots within the natural meadow at each site were marked to compare growth rates between the native meadow and transplants. Underwater shoot counts and a scaled photo was taken to record fragment survivorship, shoot mortality, bite marks, and shoot length among all remaining fragments within each site and sampling time. In the laboratory, morphological measurements (described above) were repeated on the collected fragments and growth of transplant and natural meadow shoots was measured. Growth (shoot elongation, cm d-1) of the marked shoots was obtained by measuring the length from the base of meristem to marked holes of each leaf (new growth) of the shoot and dividing the leaf elongation per shoot by the marking period (in days). For each shoot, total leaf length (cm shoot-1) and the number of new leaves was also recorded. The rate of new leaf production (new leaves shoot-1 d-1) was estimated dividing the number of new leaves produced per shoot and the marking period. New growth was dried at 60 ºC for 48 hrs to determine carbon and nitrogen content of the leaves, and carbon to nitrogen (C:N) ratios. Carbon and nitrogen concentrations in the new growth leaf tissue was measured at the beginning of the experiment and each subsequent time point for each treatment. Nutrient analyses were conducted at Unidade de Técnicas Instrumentais de Análise (University of Coruña, Spain) with an elemental analyser FlashEA112 (ThermoFinnigan). Underwater photos of shoots were analysed using ImageJ software (https://imagej.net). Maximum leaf length on each shoot in warm-edge transplant sites (cool-warm, centre-warm and warm-warm) were recorded for the initial (day 10) herbivore impact, T1, T2 and T3 time-points and related to transplant nutrient concentrations. Herbivore impact was estimated as the proportional change in length of the longest leaf relative to initial length at T0. Thermal stress Long term maximum temperatures were recorded as the average of annual maximum daily temperatures in each transplant site, averaged between years from 1981-2019. Maximum thermal anomalies were calculated as the difference between daily temperatures in a recipient site over the course of the experiment and the long-term maximum temperature in the source site for each corresponding population. ‘Heat stress’ and ‘recovery’ growth periods of the experiment were defined as T0 -T2 (July-October) and T2-T4 (November-June), respectively, corresponding to periods of positive and negative maximum thermal anomalies. Thermal anomalies experienced by the different transplant treatments were plotted using the ‘geom_flame’, function in the ‘HeatwavesR’ package (Schlegel & Smit 2018) of R (version 3.6.1, 2019) ., 1. The prevalence of local adaptation and phenotypic plasticity among populations is critical to accurately predicting when and where climate change impacts will occur. Currently, comparisons of thermal performance between populations are untested for most marine species or overlooked by models predicting the thermal sensitivity of species to extirpation. 2. Here we compared the ecological response and recovery of seagrass populations (Posidonia oceanica) to thermal stress throughout a year-long translocation experiment across a 2800 km gradient in ocean climate. Transplants in central and warm-edge locations experienced temperatures >29 ºC, representing thermal anomalies >5ºC above long-term maxima for cool-edge populations, 1.5ºC for central and <1ºC for warm-edge populations. 3. Cool, central and warm-edge populations differed in thermal performance when grown under common conditions, but patterns contrasted with expectations based on thermal geography. Cool-edge populations did not differ from warm-edge populations under common conditions and performed significantly better than central populations in growth and survival. 4. Our findings reveal that thermal performance does not necessarily reflect the thermal geography of a species. We demonstrate that warm-edge populations can be less sensitive to thermal stress than cooler, central populations suggesting that Mediterranean seagrasses have greater resilience to warming than current paradigms suggest., Australian Research Council, Award: DE200100900. Horizon 2020 Framework Programme, Award: 659246. Fundación BBVA., Peer reviewed

The Global 0.5° gridded SPEI dataset is made available under the Open Database License. Any rights in individual contents of the database are licensed under the Database Contents License. Users of the dataset are free to share, create and adapt under the conditions of attribution and share-alike. The Global SPEI database, SPEIbase, offers long-time, robust information on the drought conditions at the global scale, with a 0.5 degrees spatial resolution and a monthly time resolution. It has a multi-scale character, providing SPEI time-scales between 1 and 48 months. The Standardized Precipitatin-Evapotranspiration Index (SPEI) expresses, as a standardized variate (mean zero and unit variance), the deviations of the current climatic balance (precipitation minus evapotranspiration potential) with respect to the long-term balance. The reference period for the calculation, in the SPEIbase, corresponds to the whole study period. Being a standardized variate means that the SPEI condition can be compared across space and time. Calculation of the evapotranspiration potential in SPEIbase is based on the FAO-56 Penman-Monteith method. Data type: float; units: z-values (standard deviations). No land pixels are assigned a value of 1.0x10^30. In some rare cases it was not possible to achieve a good fit to the log-logistic distribution, resulting in a NAN (not a number) value in the database. Dimensions of the dataset: lon = 720; lat = 360; time = 1356. Resolution of the dataset: lon = 0.5º; lat = 0.5º; time = 1 month. Created in R using the SPEI package (http://cran.r-project.org/web/packages/SPEI)., Global gridded dataset of the Standardized Precipitation-Evapotranspiration Index (SPEI) at time scales between 1 and 48 months.-- Spatial resolution of 0.5º lat/lon.-- This is an update of the SPEIbase v2.6 (https://digital.csic.es/handle/10261/202305).-- What’s new in version 2.7: 1) Based on the CRU TS 4.05 dataset, spanning the period between January 1901 to December 2020. Using TLMoments::PWM instead of lmomco::pwm.ub for calculating distribution parameters. For more details on the SPEI visit http://sac.csic.es/spei, No

6 pages. -- Supplementary Figure 1. Current mean maximum summer temperature (average 𝑇!"# """""" for the period 1980-2005) across potential seagrass distribution. -- Supplementary Figure 2. Difference between current mean maximum summer temperature ( 𝑇!"# """""" ) and the Tlimit as a function of latitude. Negative and positive latitude values for southern and northern hemispheres, respectively. -- Supplementary Figure 3. Uncertainty associated to the time (in years) for mean maximum summer temperature to reach seagrass upper thermal limit (Tlim) at the warming rates projected under the RCP8.5 scenario around potential seagrass sites. -- Supplementary Figure 4. Time (in years) for mean maximum summer temperature to reach the upper thermal limits (Tlim) of temperate and tropical affinity seagrass flora at the warming rates projected under the RCP8.5 scenario around potential seagrass sites in the Mediterranean Sea and Queensland (Australia) coastal areas. -- Supplementary Figure 5. The time (in years) to reach Tlimit at the warming rates predicted under the RCP4.5 scenario around potential seagrass sites. -- Supplementary Figure 6. Time (in years) for mean maximum summer temperature to reach the upper thermal limits (Tlim) of temperate and tropical affinity seagrass flora at the warming rates projected under the RCP4.5 scenario around potential seagrass sites in the Mediterranean Sea and Queensland (Australia) coastal areas., Seagrasses have experienced major losses globally mostly attributed to human impacts. Recently they are also associated with marine heat waves. The paucity of information on seagrass mortality thermal thresholds prevents the assessment of the risk of seagrass loss under marine heat waves. We conducted a synthesis of reported empirically- or experimentally-determined seagrass upper thermal limits (Tlimit) and tested the hypothesis that they increase with increasing local annual temperature. We found that Tlimit increases 0.42± 0.07°C per°C increase in in situ annual temperature (R2 = 0.52). By combining modelled seagrass Tlimit across global coastal areas with current and projected thermal regimes derived from an ocean reanalysis and global climate models (GCMs), we assessed the proximity of extant seagrass meadows to their Tlimit and the time required for Tlimit to be met under high (RCP8.5) and moderate (RCP4.5) emission scenarios of greenhouse gases. Seagrass meadows worldwide showed a modal difference of 5°C between present Tmax and seagrass Tlimit. This difference was lower than 3°C at the southern Red Sea, the Arabian Gulf, the Gulf of Mexico, revealing these are the areas most in risk of warming-derived seagrass die-off, and up to 24°C at high latitude regions. Seagrasses could meet their Tlimit regularly in summer within 50-60 years or 100 years under, respectively, RCP8.5 or RCP4.5 scenarios for the areas most at risk, to more than 200 years for the Arctic under both scenarios. This study shows that implementation of the goals under the Paris Agreement would safeguard much of global seagrass from heat-derived mass mortality and identifies regions where actions to remove local anthropogenic stresses would be particularly relevant to meet the Target 10 of the Aichi Targets of the Convention of the Biological Diversity., Peer reviewed

The dataset contains data on sediment C02 efflux rates, carbon emissions during the experiment (gm-2), % Organic Carbon, Organic Matter content of the Posidonia oceanica seagrass sediments collected in Pollença bay (North of Mallorca Island). Sediments were cultivated in 5 different seawater temperature treatments and two different agitation conditions. Sediments used in the experiment were extracted in October 2017 from the P. Oceanica meadow of Pollença in Mallorca Island at six-meter depth Figure (1). Sediments were sampled in October 2017 using sediment cores (9 cm ID and 30cm long) and directly transported to the laboratory. Only the top 10 cm of the sediment cores were used since this fraction is the most susceptible to erosion. Living seagrass tissues (roots, rhizomes, and leaves) were removed and sediment was mixed and homogenized. 40ml of sediments were poured into glass containers of 750ml with 500ml of seawater. Finally, each recipient contained a sediment layer of approximately 1.1cm in each container. Containers were placed at five different temperature baths (26,27.5, 29, 30.5, 32 ºC) simulating summer temperatures in the bay (Garcias-Bonet et al., 2019) at different agitation regimes (agitation/repose) to simulate exposed and sheltered conditions.10 containers were sampled right after the experiment started to provide initial sediment conditions. Five containers per temperature and agitation treatment were removed 7, 21, 43, 67, and 98 days from the experiment start, to analyse sediment organic matter and CaCO3 content. CO2 incubations were run 5, 14, 56, and 91 days from the experiment start. Sampling times were distributed considering that organic matter remineralisation was likely to follow an exponential trend, including a rapid phase of loss of the more labile material followed by a slower loss of more recalcitrant substrates (Arndt et al., 2013). The experiment was run in the dark to avoid photosynthesis in an isothermal chamber at 21ºC., Organic carbon analysis: In each sampling time, organic matter content in sediments (OM %DW) was estimated as the percentage weight loss of dry sediment sample after combustion at 550ºC for 4 hours. Organic carbon (Corg) was calculated from OM content using the relation described in (Mazarrasa et al., 2017b) y = 0.29x – 0.64; (R2=0.98, p< 0.0001, n=60) OM and POC stocks along the experiment (mg OM ml-1 and mg POC ml-1) were estimated by multiplying the OM and POC (%DW) by the sediment dry weight (mg) remaining in each experimental unit and standardized to the initial volume of sediment (40 ml) introduced in every glass container. Inorganic carbon was estimated as the percentage weight loss of already combusted sediment (550ºC) after combustion at 1000ºC., Sediment CO2 production: Container headspace CO2 gas concentration was measured during 20 minutes continuum incubations (4 replicates) in each temperature and agitation treatment in all sampling times. CO2 air concentration measures were carried out using an Infra Red Gas Analyser EGM4 from PPSystems. Concentration of dissolved CO2 in seawater (in μmol CO2 L−1) was calculated from the concentration of CO2 (in ppm) measured in headspace air samples after equilibration as described in (Garcias-Bonet and Duarte, 2017; Wilson et al., 2012). Briefly, we calculate the dissolved CO2 remaining in seawater after equilibration with the air phase ([CO2]SW−eq) by, [CO2]SW−eq = 10−6 β [C CO2]Air P where β is the Bunsen solubility coefficient of CO2, calculated according to Wiesenburg and Guinasso (1979), as a function of seawater temperature and salinity; [CO2]Air is the CO2 concentration measured in containers headspace air (in ppm) and P is the atmospheric pressure (in atm) of dry air that was corrected by the effect of multiple sampling applying Boyle’s Law. Then, the initial CO2 concentration in seawater before the equilibrium ([CO2]SW−before eq) was calculated (in ml CO2 /ml H2O) by [CO2]SW−before eq = ([CH4]SW−eq VSw + 10−6 ([CO2]Air −[CO2]Air background) VAir)/VSW Where VSw is the volume of seawater in the core or in the seawater closed circuit, [CO2]Air background is the atmospheric CO2 background level and VAir is the volume of the headspace or the closed air circuit. Finally, the initial CO2 concentration was transformed to µmol CH4 L−1 by applying the ideal gas law. CO2 efflux values were calculated from CO2 variation per time unit. Then, we converted the rates to aerial (taking in account container surface) base, and thickness (in μmol m-2 s-1)., The dataset provides data on sediment C02 efflux rates (μmol CO2 m-2 s-1), carbon emissions during the experiment (gm-2), % Organic Carbon, Organic Matter content (g m-2) of the Posidonia oceanica seagrass sediments collected in Pollença bay (North of Mallorca Island). Sediments were cultivated in 5 different seawater temperature treatments and two different agitation conditions., CO2 efflux.xlsx, dataset_units.xlsx, Sediment_Organic_Carbon.xlsx, Peer reviewed

[EN] SPI01 grid: plain text. 5219 rows (excluding the header) and 1261 columns (excluding the X and Y coordinates). SPI12 grid: plain text. 5219 rows (excluding the header) and 1250 columns (excluding the X and Y coordinates). Episode descriptive files: duration and intensity integral maps, SPI01 and SPI12 averages, and spatial propagation maps., [ES] Malla SPI01: texto plano. 5219 filas -descontando el encabezado- y 1261 columnas -descontando las coordenadas X e Y-. Malla SPI12: texto plano. 5219 filas -descontando el encabezado- y 1250 columnas -descontando las coordenadas X e Y-. Archivos descriptivos de los episodios: mapas integrales de duración e intensidad, promedios de SPI’1 y SPI12 y mapas de la propagación espacial., Open Data Commons Attribution (ODC-By 1.0)., [EN] The database consists of two files in .txt format with the precipitation anomaly grids (Standardized Precipitation Index) calculated at 1 and 12 months over the Spanish peninsular domain, covering the period 2015/12_2020/12. These have been calculated from the monthly data of the MOPREDAScentury precipitation grid (https://doi.org/10.20350/digitalCSIC/15136). In addition, a descriptive analysis of the 40 drought episodes identified according to the criteria of drought intensity (SPI12 =< -0.84) and affected area (>20 % of the grid area) is included. For each episode we include the time series of the SPI01 and SPI12 average of the whole grid (expressed in anomalies); the area of the grid under drought conditions (SPI12 =< -0.84) (expressed in percent per one); the integral maps of the episode according to its duration (expressed in number of months) and intensity (average of the cells under drought conditions); and the maps representing the spatial propagation of the episode. This record corresponds to version 1.0.0 of the dataset. The database is distributed under an open license (Open Data Commons Attribution, ODC-By)., [ES] La base de datos consta de dos archivos en formato .txt con las mallas de anomalías de precipitación (Standardized Precipitation Index) calculadas a 1 y 12 meses sobre el dominio peninsular español, cubriendo el periodo 12/2015_12/2020. Estas han sido calculadas a partir de los datos mensuales de la malla de precipitación MOPREDAScentury (https://doi.org/10.20350/digitalCSIC/15136). Además, se incluye un análisis descriptivo de los 40 episodios de sequía identificados según los criterios de intensidad de la sequía (SPI12 =< -0.84) y superficie afectada (>20 % de la superficie de la malla). Para cada episodio se incluyen las series temporales del SPI01 y SPI12 promedio de toda la malla (expresadas en anomalías); el área de la malla en condiciones de sequía (SPI12 =< -0.84) (expresada en tanto por uno); los mapas integrales del episodio atendiendo a su duración (expresada en número de meses) e intensidad (promedio de las celdas en condiciones de sequía); y los mapas que representan la propagación espacial del episodio. Este registro se corresponde con la versión 1.0.0 del conjunto de datos. La base de datos se distribuye bajo una licencia abierta (Open Data Commons Attribution, ODC-By)., Project PID2020-116860RB-C22: Extremos térmicos y pluviométricos en la España peninsular 1916-2020), funded by the Spanish Ministry of Science., Peer reviewed

[EN] It contains a collection of .csv files by country and a netCDF file. Last one need specific data analyse software. [ES] Contiene una colección de archivos .csv por país y un archivo netCDF. Este último necesita software de análisis de datos específico., [EN] This database includes the representative Standardized Precipitation Evapotranspiration Index (SPEI) series for the different countries of the world from 1901 at the time scales from 1 to 48 months. The data is based on the average precipitation and reference evapotranspiration series from the Climatic Research Unit (last version) for the different world countries., [ES] Esta base de datos incluye la serie representativa del Índice Estandarizado de Precipitación y Evapotranspiración (SPEI) para los diferentes países del mundo desde 1901 en las escalas de tiempo de 1 a 48 meses. Los datos se basan en las series de precipitación media y evapotranspiración de referencia de la Unidad de Investigación Climática (última versión) para los diferentes países del mundo., Peer reviewed

[EN] It contains a netCDF file which needs specific data analysis software. [ES] Contiene un fichero netCDF que necesita software de análisis de datos específico., [EN] It is a gridded dataset for the whole of Europe, which employed a set of 125 climate indices from 1950. Climate indices were computed at different temporal scales (i.e. monthly, seasonal and annual) and mapped at a grid interval of 0.25°., [ES] Es una rejilla de 125 índices climáticos con una resolución espacial de 0.25 grados calculados para toda Europa desde 1950. Los índices climáticos han sido calculados a diferentes escalas temporales (mensual, estacional y anual)., Spanish Commission of Science and Technology and FEDER by the research projects PCIN-2015-220, CGL2017-82216-R and CGL2017-83866-C3-1-R, AXIS (Assessment of Cross(X) - sectorial climate Impacts and pathways for Sustainable transformation), JPI-Climate co-funded call of the European Commission by the project CROSSDRO, FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462) by the reserach project INDECIS which is part of ERA4CS, an ERA-NET initiated by JPI Climate, Peer reviewed

[EN] It contains a netCDF file which needs specific data analysis software. [ES] Contiene un fichero netCDF que necesita software de análisis de datos específico., [EN] ECTACI database contains four statistical parameters (climatology, coefficient of variation, slope, and significant trend) from 125 standard climate indices for the whole Europe at 0.25° grid intervals from 1979 to 2017 at various temporal scales (monthly, seasonal, and annual)., [ES] La base de datos ECTACI proporciona cuatro parámetros estadísticos (climatología, coeficiente de variación, pendiente y significatividad de tendencia) de 125 índices climáticos para toda Europa con una resolución espacial de 0.25 grados desde 1979 a 2017 a tres escalas temporales (mensual, estacional y anual)., Spanish Commission of Science and Technology and FEDER by the research projects CGL2017‐82216‐R, CGL2017‐83866‐C3‐1‐R and PCI2019‐103631, the AXIS (Assessment of Cross(X) ‐ sectorial climate Impacts and pathways for Sustainable transformation), JPI‐Climate cofunded call of the European Commission by the research projects CROSSDRO, FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), and ANR (FR) with cofunding by the European Union (grant 690462) by the research projects INDECIS which is part of ERA4CS, an ERA‐NET, Peer reviewed

Series temporales mensuales de caudal., [EN] This dataset includes series of monthly streamflow of 3224 gauging stations throughout Europe with reconstructed data for the period 1962-2017., [ES] Base de datos de caudal mensual de 3224 estaciones de aforo a lo largo de Europa con datos reconstruidos para el periodo 1962-2017., Spanish Commission of Science and Technology and FEDER by the research projects CGL2017‐82216‐R and CGL2017‐83866‐C3‐1‐R and PCI2019‐103631, AXIS (Assessment of Cross(X) ‐ sectorial climate Impacts and pathways for Sustainable transformation), JPI‐Climate cofunded call of the European Commission by the research project CROSSDRO, FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), and ANR (FR) with cofunding by the European Union (grant 690462) by the research project INDECIS which is part of ERA4CS, an ERA‐NET initiated by JPI Climate, Peer reviewed

Modelizaciones ecohidrológicas en parques continentales de España, [EN] This dataset provide information about evapotranspiration, leaf area index, net primary productivity, precipitation, potential evapotranspiration, soil moisture, maximum and minimum temperature at 7 National Parks from peninsular Spain., [ES] Esta base de datos proporciona información de evapotranspiración, índice de área foliar, producción primaria neta, precipitación, evapotranspiración potencial, humedad del suelo, temperatura máxima y mínima para 7 parques nacionales de la España peninsular., Parques Naturales - Ministerio de agricutura y medio ambiente, a través del proyecto: Herramientas de monitorización de la vegetación mediante modelización ecohidrológica en parques continentales: Evolución reciente y proyecciones futuras (ECOHIDRO, 1560/2105), Peer reviewed