Peatland vegetation: field and laboratory measurements of carbon dioxide fluxes and spectral reflectance

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Dataset information

Country of origin
Updated
Created
Available languages
English
Keywords
Soil, Sphagnum papillosum, Sphagnum capillifolium
Quality scoring
130

Dataset description

This dataset includes laboratory and field measurements of carbon fluxes and spectral reflectance for peatland vegetation including Sphagnum species. It also includes satellite data relating to the development and use of a Temperature and Greenness (TG) model, and an annual Temperature, Greenness and Wetness (TGWa) model. The laboratory data includes Gross Primary Productivity (GPP) and respiration data from samples of Sphagnum capillifolium and Sphagnum papillosum which were collected from the Forsinard Flows RSPB reserve (Northern Scotland) and subjected to different rainfall simulations, including total drought, in the laboratory. Spectral reflectance of the samples was also measured throughout the experiment, and the vegetation indices calculated are recorded. The field data includes carbon fluxes and spectral reflectance measurements, in this case taken from collars located at three sites within the Forsinard Flows Reserve during the main growing season of 2017 (March to September). Associated measurements of temperature, Photosynthetically Active Radiation (PAR), and moisture content were recorded. The species composition of the collars is also given in the data. The satellite data include Land Surface Temperature (LST) and Normalised Difference Vegetation Index (NDVI) products from the Moderate Resolution Imaging Spectroradiometer (MODIS) used to develop a TG model over the Forsinard Flows reserve, and the Glencar bog in Ireland. The dataset also includes bands used to calculate the Normalised Difference Water Index (NDWI) to develop the TGWa model. The MODIS data used in the implementation of this model to assess restoration progress, and also upscaling effectiveness, are included in the dataset. The work was carried out during a PhD project part-funded by the NERC SCENARIO DTP (Grant number: NE/L002566/1) at the University of Reading, and part-funded by The James Hutton Institute. Full details about this dataset can be found at https://doi.org/10.5285/ab9f47f9-9faf-4403-a57e-25e31f581ed0
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