Data were collected in the Seychelles, in the Indian Ocean from 1900 until 2000. These data are the Met Office's 'old' Land Surface Observation data and have been superseded by the MIDAS dataset collection. This dataset remains for historic purposes only. The data contain measurements of hourly and daily meteorological values, such as rainfall, sunshine duration, temperature, and wind speed. The MIDAS dataset supersedes this dataset and new users should apply for access to that by following the on-screen instructions. If necessary, you will be able to access this historic dataset once you have been granted access to the MIDAS data. The dataset contains the measurements of the following parameters: Sunshine duration Snow depth Visibility Wind speed and wind direction Temperature Cloud type Past and present weather

The data consist of leaf extension rates of seagrass growth as the primary response variable; elemental and isotopic compositions of seagrass above- and below-ground biomass; seagrass morphological parameters; site-characterisation environmental parameters and temperature recorded over the experimental windows. This dataset contains in-situ experimental information relating two separate nutrient enrichment experiments that were conducted in January/February 2022 and January 2023 over 2-week periods. The experiments were designed to understand the growth response of seagrass to elevated nutrient concentrations relative to controls plots. We used agricultural fertilisers to elevate local concentrations. In 2022, we used a slow-release fertiliser and compared growth response rates at two contrasting site types with 3 treatment levels (Control, Low N and High N). In 2023, we used an all-purpose granular fertiliser, the same 3 treatment levels but varied how the fertiliser was delivered to the seagrass, i.e., water-column diffusion vs below-ground diffusion. Both experiments were conducted on the same island of Gan, in Laamu atoll, Maldives. The work has been undertaken has been funded by the GCRF-UKRI South Asian Nitrogen Hub and enabled through the University of Edinburgh and Maldivian non-governmental organisation, Maldives Resilient Reefs. Full details about this dataset can be found at https://doi.org/10.5285/8760a6d4-b9df-406d-b910-678ab0f6557f

[This dataset is embargoed until December 15, 2026]. Sites were monitored for key water quality indicators, including: water quality parameters (temperature, pH, electrical conductivity, salinity, dissolved oxygen and turbidity), water samples collected for subsequent nutrient analysis (for dissolved inorganic nitrogen and phosphate), and where possible seagrass or algal samples were collected for isotopic composition. Water quality data was collected across a range of sites in Laamu atoll between 2022 and 2024 to develop a baseline understanding of water quality, to help characterise nutrient loading and identify potential sources of nutrient pollution. The sampling was conducted on varying spatial and temporal scales. This included a variety of island types (e.g., inhabited, uninhabited, agricultural, tourism islands, pristine patch reefs), and within individual islands. Sampling was conducted across a spectrum of uses-types of different sites (e.g., densely populated areas, versus heavy agricultural areas, vs rural areas etc) between different seasons (wet and dry seasons) on monthly, quarterly, bi-annual and annual time-windows. Repeat sampling was conducted on several sites several times a year and over 2 years to get a sense of change over time and within season.

[This dataset is embargoed until December 31, 2026]. The data consist of coral bleaching data; coral elemental and isotopic data (of coral host tissue and algal symbionts); coral metric data (size and depth of coral colonies used in experiment); water nutrient data collected next to corals over the experimental period; diffuser weights of fertiliser bags (to help calculate diffusion rates of fertiliser loss) and temperature data (recorded over the experimental windows in-situ and using satellite data). This dataset contains in-situ experimental information relating two separate nutrient enrichment experiments that were conducted over January - June 2022 and January 2023 - July 2024. The experiments were designed to understand the in-situ bleaching and nutrients responses of corals (Pocillopora spp.) to the interactive effect of elevated temperatures and elevated nutrient concentrations relative to controls. Slow-release agricultural fertilisers were used to elevate local concentrations. In 2022, two types of fertilisers were used (High N = 18-9-10 NPK or High P = 13-13-13 NPK). In 2023-24, the same fertiliser was used (24-7-14 NPK) but at two quantities, medium-N (50-75 g of fertiliser) and high-N (150-200 g of fertiliser) to better understand thresholds. Both experiments were conducted on lagoonal patch reefs in Laamu atoll, Maldives. The work has been undertaken has been funded by the GCRF-UKRI South Asian Nitrogen Hub and enabled through the University of Edinburgh and Maldivian non-governmental organisation, Maldives Resilient Reefs. Full details about this dataset can be found at https://doi.org/10.5285/c176bbd1-7ad6-43e7-b82b-7c707e95522f

This dataset contains raw beaching data computed by marine debris simulations (run using OceanParcels) for a range of physical scenarios (surface currents from GLORYS12V1 (https://doi.org/10.3389/feart.2021.698876), Stokes drift from WAVERYS (https://doi.org/10.1007/s10236-020-01433-w), and surface winds from ERA5 (https://doi.org/10.1002/qj.3803)), as described in the accompanying manuscript. Through postprocessing, debris ‘connectivity’ matrices can be computed, providing predictions for the main terrestrial and marine source regions of plastic debris accumulating at remote islands in the western Indian Ocean. These simulations include beaching and sinking processes, and a set of example matrices is provided here (https://doi.org/10.5287/bodleian:DEdqwXZQw). However, these matrices can be recomputed for different sinking and beaching rates using the scripts archived here (https://doi.org/10.5281/zenodo.7351695), or see here (https://github.com/nvogtvincent/WIO_Marine_Debris/) for the live version with documentation. These predictions will be useful for environmental practitioners in the western Indian Ocean to assess source regions for marine debris accumulating at islands of interest, and when this debris is likely to beach. The data were produced as part of the Marine Dispersal and Retention in the Western Indian Ocean project funded by the Natural Environment Research Council (NERC) grant NE/S007474/1. See linked online references on this record for cited items given above.