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The global carbon cycle is highly affected by peatlands as they accumulate up to 40% of the soil carbon (C) stored globally. Gross primary productivity (GPP) is a key driver of this accumulation, it determines the amount of atmospheric CO2 sequestered into biomass. One of the most widespread techniques to measure CO2 exchange with the atmosphere are closed-chamber method, however, this technique is limited to small-scale studies and is dependent on spatial and temporal interpolations. A multi-model approach combining a water table depth (WTD) based model, classic rectangular hyperbolic (RH) models, modified RH models with temperature factors and an exponential model is used to study the effect of climate manipulation in a temperate peatland, selecting in each timestep the best model based on the Akaike Information Criterion corrected, p-value, root mean square error (RMSE) and R2 results. Climatic conditions are changing rapidly, affecting the peatlands’ capability to sequester and store C, enhancing decomposition and changing vegetation cover and performance. Temperature and precipitation highly impact vegetation performance inducing stress, which is why climate manipulation experiments have increased over time following our concerns about climate change. The effect of temperature on vegetation productivity under warming and reduced precipitation conditions was observed after 3 years of climate manipulation in a temperate peatland. As shown by the partial least-squares regression while during the first year, the variance of GPP explained by temperature was 51% and 59% respectively, it increased to 73% for warming (W) and warming plus reduced precipitation (WP) sites and equally, the correlation between temperature and GPP rose from -0.81 (W) and -0.76 (WP) to -0.85. Additionally, when the annual average values of WTD increased from -19.3 ± 7.4 cm in 2018 to -16.7 ± 6.8 cm in 2021, the effect of 15-day average WTD oscillations in vegetation productivity became minor, from 63% of GPP variance explained by WTD to just 18% as more water was available. The effects are also visible in GPP annual cumulative values, increasing from -671 g CO2-C m-2y-1 and -672 g CO2-C m-2 y-1 in 2019 to -883 g CO2-C m-2 y-1 and -963 g CO2-C m-2 y-1 in 2021 respectively for W and WP sites. It is undeniable that the effect of climate manipulation has induced changes in vegetation composition which produce the changes in temperature and WTD response of GPP and at the same time, the cumulative GPP yearly. The changes in vegetation composition can be observed through the comparison with control plots where the WTD effect remained significant, explaining still in 2021 24.5% of the GPP variance while it is 16% and 13% for W and WP, probably with vegetation less adapted to climate extremes and more WTD-dependent. This work was supported by the National Science Centre of Poland (NCN) under projects No. 2016/21/B/ST10/02271 and 2020/37/B/ST10/01213.

Peatlands play a key role in the global carbon cycle and the greenhouse gas balance of the biosphere, due to the amount of stored organic carbon and rather big methane (CH4) emissions. Climate change can make these very valuable and vulnerable ecosystems a net emitter of greenhouse gases to the atmosphere. The question is however, how the anticipated climate changes may impact the methane emission. Will it decrease due to expected drier conditions, or other processes and factors may play a role leading to higher emissions? To answer this question we carried out a field climate manipulation experiment at Rzecin peatland in Poland to assess how, increased temperature and reduced precipitation may impact the CH4 emission. The field site consists of three times replicated treatments [control (CO); simulated warming (W); reduced precipitation (RP), and warming & RP (WRP)]. Temperature (T) was increased year around with infrared heaters (400Wx4 per site), while precipitation was reduced with an automatic curtain working during growth seasons at night. The average yearly peat (at 5 cm depth) and air temperatures (at 30 cm) increased at manipulated plots by ca. 1.0oC and 0.4oC, respectively, while the precipitation was reduced from 24% in 2017 to 38% in 2016. Methane and carbon dioxide fluxes were measured with an automated prototyped mobile chamber system equipped with LGR and Picarro gas analyzers. Here we present data from three years; very dry and warm 2015 (417 mm, 9.5°C), more wet and colder 2016 (678 mm, 8.9°C) ad very wet and warm 2017 (929 mm, 9.3°C). The net CH4 emissions at the control site were at the same rate of 25 gC·m-2yr-1 for both 2015 and 2016 years, and significantly higher (by 55%) in the very wet 2017 (39 gCH4-C·m2·yr-1). This may indicate that 1) temperature and precipitation play a role in driving the methane emissions from peatland, 2) increase of methane emissions due to higher precipitation can be compensated by lower temperature leading to smaller emission, 3) at more wet and warm years methane emissions may be higher than presently. However, our manipulation clearly indicated that at manipulated sites (W, WRP and RP) methane fluxes were significantly higher (by 28%) than on control plots for both 2015 and 2016 years, while no significant differences between sites exposed for manipulation were found for wet and warm 2017 (although peat temperatures at W, WRD and RD were higher than on CO). This can indicate that in conditions of a high level of groundwater in peatland (due to high rainfall) the sensitivity of methane production processes to temperature changes caused by manipulations may be lower. On the other hand, we found that higher methane fluxes at the manipulated plots are significantly correlated to a higher biomass of vascular plants. This may indicate how important might be the plant species composition on peatland in defining the transport pathways of methane to the atmosphere and overall methane emissions with respect to anticipated climate change.Research was funded within the NCN projects (017/25/N/ST10/02212, 72016/21/B/ST10/02271) and WETMAN project.