- Peatlands store large amounts of carbon. This storage function has been reduced through intensive drainage, which leads to the decomposition of peat, resulting in a loss of carbon. Measurements of the real (sigma) and imaginary part (sigma) of electrical conductivity can deliver information on peat properties, such as the pore fluid conductivity (sigma(w)), cation exchange capacity (CEC), bulk density ((b)), water content (WC) and soil organic matter (SOM) content. These properties change with the peat's degree of decomposition (DD). To explore the relationships between the peat properties, sigma, sigma and DD, we focused on three different types of survey and scales. First, point measurements were made with a conductivity probe at various locations over a large area of northeast Germany to determine the degree of correlation between sigma and DD. Second, nine of these locations were selected for sampling to determine which of the properties sigma(w), CEC, (b), WC and SOM predominantly influence sigma and sigma. This multisite datasetPeatlands store large amounts of carbon. This storage function has been reduced through intensive drainage, which leads to the decomposition of peat, resulting in a loss of carbon. Measurements of the real (sigma) and imaginary part (sigma) of electrical conductivity can deliver information on peat properties, such as the pore fluid conductivity (sigma(w)), cation exchange capacity (CEC), bulk density ((b)), water content (WC) and soil organic matter (SOM) content. These properties change with the peat's degree of decomposition (DD). To explore the relationships between the peat properties, sigma, sigma and DD, we focused on three different types of survey and scales. First, point measurements were made with a conductivity probe at various locations over a large area of northeast Germany to determine the degree of correlation between sigma and DD. Second, nine of these locations were selected for sampling to determine which of the properties sigma(w), CEC, (b), WC and SOM predominantly influence sigma and sigma. This multisite dataset includes the entire range of DD and was analysed in the laboratory. Third, one site was selected for a survey of sigma including sampling, to identify which properties mainly control sigma in a single-site approach. Statistical analysis revealed that for the multisite laboratory dataset, sigma(w) has the strongest effect on sigma, followed by CEC, whereas sigma is mainly determined by CEC. In a single-site approach, WC followed by CEC had a dominant effect on sigma. No clear correlation could be observed between (i) DD and peat properties and (ii) DD and sigma or sigma. This is because of the complex changes in properties with increasing DD.…
