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.
Publication date: 2019-03-15
In both the field and the laboratory carbon fluxes were recorded using a LICOR-8100 system and custom chambers. The data were processed using the associated LICOR software, and the results individually visually assessed for quality. The flux for each measurement was entered into an Excel spreadsheet.
In the laboratory, spectral reflectance was measured using a Ger3700 spectrometer mounted in a dark room with a single light source. Reference spectra were taken using a Spectralon panel, and the radiances were processed into reflectances using the associated software. In the field, reflectances were taken using an SVC HR-1024 spectroradiometer mounted on a monopod and held approximately 1m from the surface. A Spectralon reflectance panel was used to give references, and the reflectances were downloaded from the spectroradiometer software. In both the field and the laboratory three measurements from different angles were taken of each sample/collar, and the average calculated. The vegetation indices were then calculated from the average reflectance spectra, and entered into an Excel spreadsheet.
The satellite data products were downloaded from the MODIS server and filtered in Matlab using the associated quality information. The gaps were then filled using the technique described by Wang et al. (2012).