Modelling Mediterranean Olive Systems From Current Climate to SSP585 Climate Change Scenarios Using DayCent

Dataset Overview: Modelling Olive Systems under Climate Change This open dataset was created to support modelling of Mediterranean olive systems under both current and future climate scenarios using the DAYCENT biogeochemical model. It contains detailed biophysical measurements collected from a terraced olive farm in Mallorca, Spain, and is intended to facilitate research on soil and vegetation dynamics in response to environmental change. The data cover key variables including above-ground tree biomass, soil moisture, bulk density, vegetation cover, soil pH, particle size distribution, and infiltration rates. The dataset provides the necessary inputs for DAYCENT model runs, including weather files for the current climate in Andratx, as well as a processed file for the SSP5-8.5 climate change scenario. The raw climate projection data from AEMET DeepESD are also publicly available, and a supporting R script (Rprocessingfuture.R) is included to process these files into DAYCENT-ready .wth weather files. Site parameters and scheduling files for the terraced location in Sa Font de la Vila are also included, allowing the model to simulate soil carbon dynamics, tree growth and trace gas fluxes under varying climatic conditions. Authors and Data Collection The dataset was compiled by Taylor Seddon, Florence Masters, Aletheia Connearn, and Patrick Timmins from Durham University. Fieldwork was conducted from September 29th to October 1st, 2025, along transects crossing the lower field and terraces of the olive farm. Sampling included both Picual and Arbequina olive varieties, and measurements were recorded at multiple points along each transect to capture spatial variability. Funding and logistical support were provided by Durham University and the researchers themselves. Methods Tree measurements included circumference at 10 cm height (C10cm), which was converted to diameter (D10cm), and tree height. Above-ground biomass (AGB) was calculated using published Italian and Moroccan olive tree allometric equations. After comparison, the Italian model was chosen as it provided more realistic estimates consistent with observed tree heights. D10 was used instead of the standard diameter at breast height (DB) because many trees were multi-stemmed or irregular near 1.3 m, making measurements at that height unreliable. Soil properties were measured using standard protocols. Bulk density was determined with 80.6 cm³ rings, while volumetric soil moisture was recorded at 10 cm depth using a digital soil moisture probe. Saturated hydraulic conductivity (Ksat) was measured in the field using a Mini Disk Infiltrometer. Soil pH and nutrient concentrations (N and P) were measured using field test kits, and particle size fractions were determined with handheld sieves. GPS coordinates, distances along transects, and other metadata were recorded for all sampling points. Data Processing and Format Raw field data were entered into Excel, cleaned, and processed for analysis. AGB was calculated via the Brunori et al. (2017) allometric method. Soil bulk density, moisture, Ksat, and nutrient status were computed and converted into formats suitable for DAYCENT, including .100, .sch, and .wth files. GPS data were refined using ArcGIS to ensure accurate site identification. DAYCENT output files in the dataset include logs of daily and annual carbon fluxes, soil properties, and climate data. Supplementary scripts, such as Daycent_visualisation_ver02.R, facilitate processing and visualization of model outputs. Dataset Scope and Accessibility The dataset covers 46 tree and soil sampling points across multiple transects, with measurements for tree size, biomass, soil physical and chemical properties, and infiltration. Missing values reflect locations without nearby trees or unavailable testing kits. Climate data are provided both as processed DAYCENT weather files and as raw AEMET DeepESD files, with an accompanying R script to convert the raw data for model use. The data are provided for academic, non-commercial use, with redistribution requiring author permission. Recommended citation:Masters, F., Seddon, T., Connearn, A., & Timmins, P. (2025). Mallorcan Olive Farms DayCent Projections [Dataset]. Durham University Department of Geography.