| Summary: | Northern circumpolar permafrost peatlands store ~300 Pg of organic carbon (C), and play a critical role in regulating global biogeochemical cycles. Amplified warming in high-latitude regions is threatening this large C stock, because permafrost thawing will expose previously frozen C to decomposition. Permafrost thaw-induced hydrological changes together with warming will influence plant photosynthesis and decomposition processes and thus C accumulation patterns. However, it is still unresolved how C accumulation, warming and associated hydrological changes are interlinked. In this study, I used 14 peat records from four sites in northeast European Russia and Finnish Lapland to reconstruct permafrost peatland vegetation, hydrology and C dynamics. The studied records were dated by radiocarbon (14C) and lead (210Pb) methods. In order to reconstruct hydrology, i.e. water-table depth (WTD), I first developed a new modern testate amoeba-WTD training set. The training set represented different habitats and comprised 145 surface peat samples collected from the four study sites. The training set data were then applied to six peat records to reconstruct last millennium hydrological changes. Plant macrofossil analysis was also conducted for these six cores to study changes in the vegetation, habitat conditions and permafrost dynamics, and to evaluate testate amoeba-based WTD reconstructions. In order to calculate and model C accumulation patterns, bulk density and C content (occasionally loss on ignition) analyses were carried out for 14 cores. C modelling enabled the C capacity analyses of peat that was accumulated during recent centuries vs. older peat layers. Several environmental variables, such as nitrogen (N) content, C/N ratio, WTD, plant functional types and summer temperature were used to evaluate allogenic C accumulation forcing in the past. The data show that testate amoebae are powerful indicators of hydrological conditions in permafrost peatlands. Testate amoeba and plant macrofossil reconstructions suggest ...
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