A drained nutrient-poor peatland forest in boreal Sweden constitutes a net carbon sink after integrating terrestrial and aquatic fluxes.

Northern peatlands provide a globally important carbon (C) store. Since the beginning of the 20th century, however, large areas of natural peatlands have been drained for biomass production across Fennoscandia. Today, drained peatland forests constitute a common feature of the managed boreal landscape, yet their ecosystem C balance and associated climate impact are not well understood, particularly within the nutrient-poor boreal region. In this study, we estimated the net ecosystem carbon balance (NECB) from a nutrient-poor drained peatland forest and an adjacent natural mire in northern Sweden by integrating terrestrial carbon dioxide (CO2 ) and methane (CH4 ) fluxes with aquatic losses of dissolved organic C (DOC) and inorganic C based on eddy covariance and stream discharge measurements, respectively, over two hydrological years. Since the forest included a dense spruce-birch area and a sparse pine area, we were able to further evaluate the effect of contrasting forest structure on the NECB and component fluxes. We found that the drained peatland forest was a net C sink with a 2-year mean NECB of -115 ± 5 g C m-2 year-1 while the adjacent mire was close to C neutral with 14.6 ± 1.7 g C m-2 year-1 . The NECB of the drained peatland forest was dominated by the net CO2 exchange (net ecosystem exchange [NEE]), whereas NEE and DOC export fluxes contributed equally to the mire NECB. We further found that the C sink strength in the sparse pine forest area (-153 ± 8 g C m-2 year-1 ) was about 1.5 times as high as in the dense spruce-birch forest area (-95 ± 8 g C m-2 year-1 ) due to enhanced C uptake by ground vegetation and lower DOC export. Our study suggests that historically drained peatland forests in nutrient-poor boreal regions may provide a significant net ecosystem C sink and associated climate benefits.

Statistical upscaling of ecosystem CO2 fluxes across the terrestrial tundra and boreal domain: Regional patterns and uncertainties.

The regional variability in tundra and boreal carbon dioxide (CO2 ) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990-2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2 ) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE -46 and -29 g C m-2  yr-1 , respectively) compared to tundra (average annual NEE +10 and -2 g C m-2  yr-1 ). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990-2015, although uncertainty remains high.

Refining the role of phenology in regulating gross ecosystem productivity across European peatlands.

The role of plant phenology as a regulator for gross ecosystem productivity (GEP) in peatlands is empirically not well constrained. This is because proxies to track vegetation development with daily coverage at the ecosystem scale have only recently become available and the lack of such data has hampered the disentangling of biotic and abiotic effects. This study aimed at unraveling the mechanisms that regulate the seasonal variation in GEP across a network of eight European peatlands. Therefore, we described phenology with canopy greenness derived from digital repeat photography and disentangled the effects of radiation, temperature and phenology on GEP with commonality analysis and structural equation modeling. The resulting relational network could not only delineate direct effects but also accounted for possible effect combinations such as interdependencies (mediation) and interactions (moderation). We found that peatland GEP was controlled by the same mechanisms across all sites: phenology constituted a key predictor for the seasonal variation in GEP and further acted as a distinct mediator for temperature and radiation effects on GEP. In particular, the effect of air temperature on GEP was fully mediated through phenology, implying that direct temperature effects representing the thermoregulation of photosynthesis were negligible. The tight coupling between temperature, phenology and GEP applied especially to high latitude and high altitude peatlands and during phenological transition phases. Our study highlights the importance of phenological effects when evaluating the future response of peatland GEP to climate change. Climate change will affect peatland GEP especially through changing temperature patterns during plant phenologically sensitive phases in high latitude and high altitude regions.

COSORE: A community database for continuous soil respiration and other soil-atmosphere greenhouse gas flux data.

Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soil-to-atmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS ), is one of the largest carbon fluxes in the Earth system. An increasing number of high-frequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, open-source COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and long-term GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS , the database design accommodates other soil-atmosphere measurements (e.g. ecosystem respiration, chamber-measured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package.

Partitioning of the net CO2 exchange using an automated chamber system reveals plant phenology as key control of production and respiration fluxes in a boreal peatland.

The net ecosystem CO2 exchange (NEE) drives the carbon (C) sink-source strength of northern peatlands. Since NEE represents a balance between various production and respiration fluxes, accurate predictions of its response to global changes require an in depth understanding of these underlying processes. Currently, however, detailed information of the temporal dynamics as well as the separate biotic and abiotic controls of the NEE component fluxes is lacking in peatland ecosystems. In this study, we address this knowledge gap by using an automated chamber system established across natural and trenching/vegetation removal plots to partition NEE into its production (i.e., gross and net primary production; GPP and NPP) and respiration (i.e., ecosystem, heterotrophic and autotrophic respiration; ER, Rh and Ra) fluxes in a boreal peatland in northern Sweden. Our results showed that daily NEE patterns were driven by GPP while variations in ER were governed by Ra rather than Rh. Moreover, we observed pronounced seasonal shifts in the Ra/Rh and above/belowground NPP ratios throughout the main phenological phases. Generalized linear model analysis revealed that the greenness index derived from digital images (as a proxy for plant phenology) was the strongest control of NEE, GPP and NPP while explaining considerable fractions also in the variations of ER and Ra. In addition, our data exposed greater temperature sensitivity of NPP compared to Rh resulting in enhanced C sequestration with increasing temperature. Overall, our study suggests that the temporal patterns in NEE and its component fluxes are tightly coupled to vegetation dynamics in boreal peatlands and thus challenges previous studies that commonly identify abiotic factors as key drivers. These findings further emphasize the need for integrating detailed information on plant phenology into process-based models to improve predictions of global change impacts on the peatland C cycle.

Consequences of rewetting and ditch cleaning on hydrology, water quality and greenhouse gas balance in a drained northern landscape.

Drainage for forestry has created ~ 1 million km of artificial waterways in Sweden, making it one of the largest human-induced environmental disturbances in the country. These extensive modifications of both peatland and mineral soil dominated landscapes still carry largely unknown, but potentially enormous environmental legacy effects. However, the consequences of contemporary ditch management strategies, such as hydrological restoration via ditch blocking or enhancing forest drainage to promote biomass production via ditch cleaning, on water resources and greenhouse gas (GHG) fluxes are unclear. To close the gap between science and management, we have developed a unique field research platform to experimentally evaluate key environmental strategies for drained northern landscapes with the aim to avoid further environmental degeneration. The Trollberget Experimental Area (TEA) includes replicated and controlled treatments applied at the catchment scale based on a BACI approach (before-after and control-impact). The treatments represent the dominant ecosystem types impacted by ditching in Sweden and the boreal zone: (1) rewetting of a drained peatland, (2) ditch cleaning in productive upland forests and (3) leaving these ditches unmanaged. Here we describe the TEA platform, report initial results, suggest ways forward for how to best manage this historical large-scale alteration of the boreal landscape, as well as warn against applying these treatments broadly before more long-term results are reported.

Bimodal diel pattern in peatland ecosystem respiration rebuts uniform temperature response.

Accurate projections of climate change impacts on the vast carbon stores of northern peatlands require detailed knowledge of ecosystem respiration (ER) and its heterotrophic (Rh) and autotrophic (Ra) components. Currently, however, standard flux measurement techniques, i.e. eddy covariance and manual chambers, generate empirical ER data during only night- or daytime, respectively, which are extrapolated to the daily scale based on the paradigm that assumes a uniform diel temperature response. Here, using continuous autochamber measurements, we demonstrate a distinct bimodal pattern in diel peatland ER which contrasts the unimodal pattern inherent to the classical assumption. This feature results from divergent temperature dependencies of day- and nighttime ER due to varying contributions from Rh and Ra. We further find that disregarding these bimodal dynamics causes significant bias in ER estimates across multiple temporal scales. This calls for improved process-based understanding of ER to advance our ability to simulate peatland carbon cycle-climate feedbacks.

Author Correction: Nitrogen-rich organic soils under warm well-drained conditions are global nitrous oxide emission hotspots.

The original version of this Article contained an error in the first sentence of the Acknowledgements section, which incorrectly referred to the Estonian Research Council grant identifier as "PUTJD618". The correct version replaces the grant identifier with "PUTJD619". This has been corrected in both the PDF and HTML versions of the Article.

Nitrogen-rich organic soils under warm well-drained conditions are global nitrous oxide emission hotspots.

Nitrous oxide (N2O) is a powerful greenhouse gas and the main driver of stratospheric ozone depletion. Since soils are the largest source of N2O, predicting soil response to changes in climate or land use is central to understanding and managing N2O. Here we find that N2O flux can be predicted by models incorporating soil nitrate concentration (NO3-), water content and temperature using a global field survey of N2O emissions and potential driving factors across a wide range of organic soils. N2O emissions increase with NO3- and follow a bell-shaped distribution with water content. Combining the two functions explains 72% of N2O emission from all organic soils. Above 5 mg NO3--N kg-1, either draining wet soils or irrigating well-drained soils increases N2O emission by orders of magnitude. As soil temperature together with NO3- explains 69% of N2O emission, tropical wetlands should be a priority for N2O management.

Impact of Reed Canary Grass Cultivation and Mineral Fertilisation on the Microbial Abundance and Genetic Potential for Methane Production in Residual Peat of an Abandoned Peat Extraction Area.

This study examined physiochemical conditions and prokaryotic community structure (the bacterial and archaeal 16S rRNA genes and mcrA gene abundances and proportions), and evaluated the effect of reed canary grass cultivation and mineral fertilisation on these factors, in the 60 cm thick residual peat layer of experimental plots located on an abandoned peat extraction area. The archaeal proportion was 0.67-39.56% in the prokaryotic community and the methanogens proportion was 0.01-1.77% in the archaeal community. When bacterial abundance was higher in the top 20 cm of peat, the archaea were more abundant in the 20-60 cm layer and methanogens in the 40-60 cm layer of the residual peat. The bacterial abundance was significantly increased, but archaeal abundance was not affected by cultivation. The fertiliser application had a slight effect on peat properties and on archaeal and methanogen abundances in the deeper layer of cultivated peat. The CH4 emission was positively related to mcrA abundance in the 20-60 cm of the bare peat, while in case of reed canary grass cultivation these two parameters were not correlated. Reed canary grass cultivation mitigated CH4 emission, although methanogen abundance remained approximately the same or even increased in different layers of residual peat under cultivated sites over time. This study supports the outlook of using abandoned peat extraction areas to produce reed canary grass for energy purposes as an advisable land-use practice from the perspective of atmospheric impact in peatland-rich Northern Europe.