Jentzsch, Katharina; Männistö, Elisa; Marushchak, Maija E; Korrensalo, Aino; van Delden, Lona; Tuittila, Eeva-Stiina; Treat, Claire C: Seasonal chamber measurements of CH4 fluxes and pore water data from vegetation removal experiments on the microtopography scale of Siikaneva bog, southern Finland, in 2021 and 2022 [dataset]. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.971358 (dataset in review)

The data set contains chamber measurements of methane (CH4) emissions from vegetation removal experiments consisting of three vegetation treatments (intact vegetation, vascular plants removed, all vegetation removed) at four microtopography types of Siikaneva bog (mud bottoms, hollows, high lawns, and hummocks) with five spatial replicates of the vegetation removal experiment each. Each chamber measurement was performed once under light and once under dark conditions. In summer 2021 each measurement was additionally performed under single and double shading of the measurement plot. We sampled the pore water at 20 cm depth in the peat profile for the concentrations of DOC, TDN and dissolved CH4 and its δ13C values and measured the peat temperature both in an area with intact vegetation as well as where the vascular plants were removed. Additionally, we measured the water table depth and determined the green leaf area index (LAI) of each vascular plant species present at our sampling sites, grouping them to derive total LAI, LAI of aerenchymatous plants and shrub LAI. The flux measurements and pore water samples were collected at Siikaneva bog, Southern Finland in seasonal field campaigns in July and August 2021 and May, July, September, and October 2022. We combined the CH4 flux measurements on the vegetation removal experiments with pore water concentrations and isotopic data to investigate the seasonal change in the spatial variability in CH4 emissions and its environmental and ecological controls. In our study, we furthermore extrapolated the chamber measurements to the area of Siikaneva bog using a microtopography map derived from drone imagery in order to assess the importance of high-resolution land cover mapping for an accurate estimation of ecosystem scale CH4 budgets.