GENERAL INFORMATION ------------------ 1. Dataset title: Dataset Morillas et al., 2024. Consistent geographical gradient of water use efficiency evidences local adaptations to drought across the complete latitudinal distribution of Quercus suber” Plant Stress, 10.1016/j.stress.2024.100432 2. Authorship: Name:Morillas, Lourdes Institution: Universidad de Sevilla Email:lmorillas@us.es ORCID:https://orcid.org/0000-0002-9544-1188 Name: Leiva, María José Institution:Universidad de Sevilla Email:leiva@us.es ORCID:https://orcid.org/0000-0003-0895-2455 Name: Gandullo, Jacinto Institution:Universidad de Sevilla Email:jacintogt@us.es ORCID:https://orcid.org/0000-0002-9147-5874 Name: Pérez-Ramos, Ignacio M. Institution: Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS-CSIC Email:imperez@irnase.csic.es ORCID: Name:Cambrollé, Jesús Institution:Universidad de Sevilla Email:cambrolle@us.es ORCID:https://orcid.org/0000-0002-9750-6328 Name: Matías, Luis Institution:Universidad de Sevilla Email:lmatias@us.es ORCID:https://orcid.org/0000-0001-5603-5390 DESCRIPTION ---------- 1. Dataset language: English 2. Abstract: Dataset (Metadata, chemical variables (MDA and proline), isotopes (d13C, d15N and C/N), physiological variables (A, Ca, Ci y GSW) and aboveground biomass related to the manuscript Morillas et al., 2024. “Consistent geographical gradient of water use efficiency evidences local adaptations to drought across the complete latitudinal distribution of Quercus suber” published at the journal Plant Stress. See the abstract of the manuscript for more details. 3. Keywords: Cork oak; Drought resistance; Functional response; Physiological traits; Climate change; Phenotypic plasticity Alcornoque; resistencia a la sequía; respuesta funcional; rasgos fisiológicos; cambio climático; plasticidad fenotípica. 4. Date of data collection (fecha única o rango de fechas): From 10-01-2021 to 20-09-2021 5. Publication Date: 15-03-2024 6. Grant information: Grant Agency:Spanish Ministry of Science, Innovation and Universities Grant Number:PID2019-108288R Grant Agency:Spanish Ministry of Universities Grant Number:MZAMBRANO-2022-22400 Grant Agency: Andalusian Council for Economy, Knowledge and Universities Grant Number:FEDER US-1380871 Grant Agency:Contrato de Acceso by VII PPIT-US from the University of Seville Grant Number: 7. Geographical location/s of data collection: From northern Spain to northern Morocco ACCESS INFORMATION ------------------------ 1. Creative Commons License of the dataset: CC-BY 4.0 2. Dataset DOI: https://doi.org/10.12795/11441/156332 3. Related publication: Morillas, L.*, Leiva, M. J., Gandullo, J., Pérez-Ramos, I., Cambrollé, J., Matías, L. 2024. Consistent geographical gradient of water use efficiency evidences local adaptations to drought across the complete latitudinal distribution of Quercus suber. Plant Stress, 10.1016/j.stress.2024.100432. VERSIONING AND PROVENANCE --------------- 1. Last modification date: 10-03-2023 2. Were data derived from another source?: No METHODOLOGICAL INFORMATION ----------------------- 1. Description of the methods used to collect and generate the data: Description of the methods used to collect the data acon be found in section "Materials and Methods" of the manuscript "Morillas, L.et al., 2024. Consistent geographical gradient of water use efficiency evidences local adaptations to drought across the complete latitudinal distribution of Quercus suber. Plant Stress, 10.1016/j.stress.2024.100432" 2. Data processing methods: Description of the data processing methods "Materials and Methods" of the manuscript "Morillas, L.et al., 2024. Consistent geographical gradient of water use efficiency evidences local adaptations to drought across the complete latitudinal distribution of Quercus suber. Plant Stress, 10.1016/j.stress.2024.100432" 3. Environmental or experimental conditions: We simulated four different watering scenarios, each of them with 10 replicates: 1) 100% of WHC, corresponding with a rainy growing season where soils remain wet most of the time, simulated through an irrigation until field capacity twice per week; 2) 50% of WHC, simulating average moisture availability conditions in a cork oak forest during the spring season ; 3) 25% of WHC, simulating a reduction of approximately 30% over the previous scenario and according with the projections of the A1B scenario for the Mediterranean area at the end of the current century; 4) 10% of WHC, corresponding with an infrequently dry spring, an extreme event that is expected to become more usual in the coming years. These watering treatments were applied to experimental pots by adding a constant amount of water to all seedlings within the same watering level from 12 April to 1 July 2021, simulating the natural growing season. Following this differential treatment, watering was completely stopped simulating an extreme drought period and seedlings were subjected to a progressive drought until death to determine seedling resistance to extreme drought conditions across provenances and watering levels. FILE OVERVIEW ---------------------- [Se han de mencionar todos los archivos incluidos en el conjunto de datos, con el nombre y la extensión (.csv, .pdf, etc.) de cada archivo. Incluya la estructura de directorios]. 1. Explain the file naming conversion, si es aplicable: The Excel file has 5 leaflets: Metadata: includes codes, full names and units for each variable. For each population (experimental site), it shows latitudes, longitudes and elevations. Chemical: includes codes for population (experimental site) and water treatment and data and units for MDA and proline. Isotopes: includes codes for population (experimental site) and water treatment and data and units for d13C, d15N and C/N. Physiological: includes codes for population (experimental site) and water treatment and data and units for A, Ca, Ci and GSW. Aboveground biomass: includes codes for population (experimental site) and water treatment and data and units for aboveground biomass. 2. File list: File name: Row data Morillas et al., 2024, Plant Stress Description:The Excel file has 5 leaflets: Metadata: includes codes, full names and units for each variable. For each population (experimental site), it shows latitudes, longitudes and elevations. Chemical: includes codes for population (experimental site) and water treatment and data and units for MDA and proline. Isotopes: includes codes for population (experimental site) and water treatment and data and units for d13C, d15N and C/N. Physiological: includes codes for population (experimental site) and water treatment and data and units for A, Ca, Ci and GSW. Aboveground biomass: includes codes for population (experimental site) and water treatment and data and units for aboveground biomass. 3. Relationship between files: There in one unique file 4. File format: Excel