Abstract. The focus of current water management in drained peatlands is to facilitate optimal drainage, which has led to soil subsidence and a strong increase in greenhouse gas (GHG) emissions. The Dutch land and water authorities proposed the application of subsoil irrigation (SSI) system on a large scale to potentially reduce GHG emissions, while maintaining high biomass production. Based on model results, the expectation was that SSI would reduce peat decomposition in summer by preventing groundwater tables (GWTs) from dropping below −60 cm. In 2017–2018, we evaluated the effects of SSI on GHG emissions (CO2, CH4, N2O) for four dairy farms on drained peat meadows in the Netherlands. Each farm had a treatment site with SSI installation and a control site drained only by ditches (ditch water level −60 / −90 cm, 100 m distance between ditches). The SSI system consisted of perforated pipes −70 cm from surface level with spacing of 5–6 m to improve drainage during winter–spring and irrigation in summer. GHG emissions were measured using closed chambers every 2–4 weeks for CO2, CH4 and N2O. Measured ecosystem respiration (Reco) only showed a small difference between SSI and control sites when the GWT of SSI sites were substantially higher than the control site (> 20 cm difference). Over all years and locations, however, there was no significant difference found, despite the 6–18 cm higher GWT in summer and 1–20 cm lower GWT in wet conditions at SSI sites. Differences in mean annual GWT remained low (< 5 cm). Direct comparison of measured N2O and CH4 fluxes between SSI and control sites did not show any significant differences. CO2 fluxes varied according to temperature and management events, while differences between control and SSI sites remained small. Therefore, there was no difference between the annual gap-filled net ecosystem exchange (NEE) of the SSI and control sites. The net ecosystem carbon balance (NECB) was on average 40 and 30 t CO2 ha−1 yr−1 in 2017 and 2018 on the SSI sites and 38 and 34 t CO2 ha−1 yr−1 in 2017 and 2018 on the control sites. This lack of SSI effect is probably because the GWT increase remains limited to deeper soil layers (60–120 cm depth), which contribute little to peat oxidation. We conclude that SSI modulates water table dynamics but fails to lower annual carbon emission. SSI seems unsuitable as a climate mitigation strategy. Future research should focus on potential effects of GWT manipulation in the uppermost organic layers (−30 cm and higher) on GHG emissions from drained peatlands.

Water hyacinth beds tend to be net GHG sinks; A low water hyacinth cover offsets open water emissions due to carbon uptake; Depth and plant biomass explain a large share of the variation in GHG fluxes.

Freshwater ecosystems are the largest natural source of the greenhouse gas methane (CH4), with shallow lakes a particular hot spot. Eutrophication and warming generally increase lake CH4 emissions but their impacts on the sole biological methane sink—methane oxidation—and methane-oxidizer community dynamics are poorly understood. We used the world’s longest-running freshwater climate-change mesocosm experiment to determine how methane-oxidizing bacterial (MOB) abundance and composition, and methane oxidation potential in the sediment respond to eutrophication, short-term nitrogen addition and warming. After nitrogen addition, MOB abundance and methane oxidation potential increased, while warming increased MOB abundance without altering methane oxidation potential. MOB community composition was driven by both temperature and nutrient availability. Eutrophication increased relative abundance of type I MOB Methyloparacoccus. Warming favoured type II MOB Methylocystis over type I MOB Methylomonadaceae, shifting the MOB community from type I dominance to type I and II co-dominance, thereby altering MOB community traits involved in growth and stress-responses. This shift to slower-growing MOB may explain why higher MOB abundance in warmed mesocosms did not coincide with higher methane oxidation potential. Overall, we show that eutrophication and warming differentially change the MOB community, resulting in an altered ability to mitigate CH4 emissions from shallow lakes.

Abstract. Current water management in drained peatlands to facilitate agricultural use, leads to soil subsidence and strongly increases greenhouse gas (GHG) emission. High-density, sub-soil irrigation/drainage systems have been proposed as a potential climate mitigation measure, while maintaining high biomass production. In summer, sub-soil irrigation can potentially reduce peat decomposition by preventing groundwater tables to drop below −60 cm. In 2017–2018, we evaluated the effects of sub-soil irrigation on GHG emissions (CO2, CH4, N2O) for four dairy farms on drained peat meadows in the Netherlands. Each farm had a treatment site with perforated pipes at 70 cm below soil level spacing 5–6 m to improve both drainage (winter- spring) and irrigation (summer) of the subsoil, and a control site drained only by ditches (ditch water level −60/−90 cm, 100 m distance between ditches). GHG emissions were measured using closed chambers (0.8 x 0.8 m) every 2–4 weeks. C inputs by manure and C export by grass yields were accounted for. Unexpectedly, sub-soil irrigation hardly affected ecosystem respiration (Reco) despite raising summer groundwater tables (GWT) by 6–18 cm, and even up to 50 cm during drought. Only when the groundwater table of sub-soil irrigation sites was substantially higher than the control value (> 20 cm), Reco was significantly lower (p<0.01), indicating a small effect of irrigation on C turnover. During wet conditions sub-soil pipes lowered water levels by 1–20 cm, without a significant effect on Reco. As a result, Reco differed little (>3 %) between sub-soil irrigation and control sites on an annual base. CO2 fluxes were high at all locations, exceeding 45 t CO2 ha−1a−1, even where peat was covered by clay (25–40 cm). Despite extended drought episodes and lower water levels in 2018, we found lower annual CO2 fluxes than in 2017 indicating drought stress for microbial respiration. Contrary to our expectation, there was no difference between the yearly greenhouse balance of the sub-soil irrigated (64 t CO2–eq ha−1yr−1 in 2017, 53 in 2018) and control sites (61 t CO2–eq ha−1 yr−1 in 2017, 51 in 2018). Emissions of N2O were lower (3 ± 1 t CO2–eq ha−1 yr−1) in 2017 than in 2018 (5 ± 2 t CO2–eq ha−1 yr−1), without treatment effects. The contribution of CH4 to the total GHG budget was negligible (<0.1 %), with lower GWT favoring CH4 oxidation over its production. Even during the 2018 drought, sub-soil irrigation had only little effect on yields (9.7 vs. 9.1 t DM ha−1yr−1), suggesting that increased GWT failed to increase plant water supply. This indicates that peat oxidation is hardly affected, probably because GWT increase only takes place in deeper soil layers (60–120 cm depth). We conclude that, although our field-scale experimental research revealed substantial differences in summer GWT and timing/intensity of irrigation and drainage, sub-soil irrigation fails to lower annual GHG emission and is unsuitable as a climate mitigation strategy. Future research should focus on potential effects of GWT manipulation in the uppermost organic layers (−30 cm and higher) on GHG emissions from drained peatlands.

Estimating annual CO2 budgets on drained peatlands is important in understanding the significance of CO2 emissions from peatland degradation and evaluating the effectiveness of mitigation techniques. The closed-chamber technique is widely used in combination with gap-filling of CO2 fluxes by parameter fitting empirical models of ecosystem respiration (Reco) and gross primary production (GPP). However, numerous gap-filling strategies are available which are suitable for different circumstances and can result in large variances in annual budget estimates. Therefore, a need for guidance on the selection of gap-filling methodology and its influence on the results exists. Here, we propose a framework of gap-filling methods with four Tiers following increasing model complexity at structural and temporal levels. Tier one is a simple parameter fitting of basic empirical models on an annual basis. Tier two adds structural complexity by including extra environmental factors such as grass height, groundwater level and drought condition. Tier three introduces temporal complexity by separation of annual datasets into seasons. Tier four is a campaign-specific parameter fitting approach, representing highest temporal complexity. The methods were demonstrated on two chamber-based CO2 flux datasets, one of which was previously published. Performance of the empirical models were compared in terms of error statistics. Annual budget estimates were indirectly validated with carbon export values. In conclusion, different gap-filling methodologies gave similar annual estimates but different intra-annual CO2 fluxes, which did not affect the detection of the treatment effects. The campaign-wise gap-filling at Tier four gave the best model performances, while Tier three seasonal gap-filling produced satisfactory results throughout, even under data scarcity. Given the need for more complete carbon balances in drained peatlands, our four-Tier framework can serve as a methodological guidance to the handling of chamber-measured CO2 fluxes, which is fundamental in understanding emissions from degraded peatlands and its mitigation. The performance of models on intra-annual data should be validated in future research with continuous measured CO2 flux data.