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Oceans alleviate the accumulation of atmospheric CO2 by absorbing approximately a quarter of all anthropogenic emissions. In the deep oceans, carbon uptake is dominated by aquatic phase chemistry, whereas in biologically active coastal seas the marine ecosystem and biogeochemistry play an important role in the carbon uptake. Coastal seas are hotspots of organic and inorganic matter transport between the land and the oceans, and thus they are important for the marine carbon cycling. In this study, we investigate the net air–sea CO2 exchange at the Utö Atmospheric and Marine Research Station, located at the southern edge of the Archipelago Sea within the Baltic Sea, using the data collected during 2017–2021. The air–sea fluxes of CO2 were measured using the eddy covariance technique, supported by the flux parameterization based on the pCO2 and wind speed measurements. During the spring–summer months (April–August), the sea was gaining carbon dioxide from the atmosphere, with the highest monthly sink fluxes typically occurring in May, being −0.26 µmol m−2 s−1 on average. The sea was releasing the CO2 to the atmosphere in September–March, and the highest source fluxes were typically observed in September, being 0.42 µmol m−2 s−1 on average. On an annual basis, the study region was found to be a net source of atmospheric CO2, and on average, the annual net exchange was 27.1 gC m−1 yr−1, which is comparable to the exchange observed in the Gulf of Bothnia, the Baltic Sea. The annual net air–sea CO2 exchanges varied between 18.2 (2018) and 39.1 gC m−1 yr−1 (2017). During the coldest year, 2017, the spring–summer sink fluxes remained low compared to the other years, as a result of relatively high seawater pCO2 in summer, which never fell below 220 µatm during that year. The spring–summer phytoplankton blooms of 2017 were weak, possibly due to the cloudy summer and deeply mixed surface layer, which restrained the photosynthetic fixation of dissolved inorganic carbon in the surface waters. The algal blooms in spring–summer 2018 and the consequent pCO2 drawdown were strong, fueled by high pre-spring nutrient concentrations. The systematic positive annual CO2 balances suggest that our coastal study site is affected by carbon flows originating from elsewhere, possibly as organic carbon, which is remineralized and released to the atmosphere as CO2. This coastal source of CO2 fueled by the organic matter originating probably from land ecosystems stresses the importance of understanding the carbon cycling in the land–sea continuum.

The urgent need to mitigate climate change has evoked a broad interest in better understanding and estimating nitrous oxide (N2O) emissions from different ecosystems. Part of the uncertainty in N2O emission estimates still comes from an inadequate understanding of the temporal and small-scale spatial variability of N2O fluxes. Using 4.5 years of N2O flux data collected in a drained peatland forest with six automated chambers, we explored temporal and small-scale spatial variability of N2O fluxes. A random forest with conditional inference trees was used to find immediate and delayed relationships between N2O flux and environmental conditions across seasons and years. The spatiotemporal variation of the N2O flux was large, with daily mean N2O flux varying between −10 and +1760 µgN2Om-2h-1 and annual N2O budgets of different chambers between +60 and +2110 mgN2Om-2yr-1. Spatial differences in fluxes persisted through years of different environmental conditions. Soil moisture, water table level, and air temperature were the most important variables explaining the temporal variation of N2O fluxes. N2O fluxes responded to precipitation events with peak fluxes measured on average 4 d after peaks in soil moisture and water table level. The length of the time lags varied in space and between seasons indicating possible interactions with temperature and other soil conditions. The high temporal variation in N2O flux was related to (a) temporal variation in environmental conditions, with the highest N2O fluxes measured after summer precipitation events and winter soil freezing, and (b) to annually varying seasonal weather conditions, with the highest N2O emissions measured during wet summers and winters with discontinuous snow cover. Climate change may thus increase winter N2O emissions, which may be offset by lower summer N2O emissions in dry years. The high sensitivity of N2O fluxes to seasonal weather conditions suggests increasing variability in annual peatland forest N2O budgets as the frequency of extreme weather events, such as droughts, is predicted to increase.

The subarctic landscape consists of a mosaic of forest, peatland, and aquatic ecosystems and their ecotones. The carbon (C) exchange between ecosystems and the atmosphere through carbon dioxide (CO2) and methane (CH4) fluxes varies spatially and temporally among these ecosystems. Our study area in Kaamanen in northern Finland covered 7 km2 of boreal subarctic landscape with upland forest, open peatland, pine bogs, and lakes. We measured the CO2 and CH4 fluxes with eddy covariance and chambers between June 2017 and June 2019 and studied the C flux responses to varying meteorological conditions. The landscape area was an annual CO2 sink of −45 ± 22 and −33 ± 23 g C m−2 and a CH4 source of 3.0 ± 0.2 and 2.7 ± 0.2 g C m−2 during the first and second study years, respectively. The pine forest had the largest contribution to the landscape-level CO2 sink, −126 ± 21 and −101 ± 19 g C m−2, and the fen to the CH4 emissions, 7.8 ± 0.2 and 6.3 ± 0.3 g C m−2, during the first and second study years, respectively. The lakes within the area acted as CO2 and CH4 sources to the atmosphere throughout the measurement period, and a lake located downstream from the fen with organic sediment showed 4-fold fluxes compared to a mineral sediment lake. The annual C balances were affected most by the rainy peak growing season in 2017, the warm summer in 2018, and a heatwave and drought event in July 2018. The rainy period increased ecosystem respiration (ER) in the pine forest due to continuously high soil moisture content, and ER was on a level similar to the following, notably warmer, summer. A corresponding ER response to abundant precipitation was not observed for the fen ecosystem, which is adapted to high water table levels, and thus a higher ER sum was observed during the warm summer 2018. During the heatwave and drought period, similar responses were observed for all terrestrial ecosystems, with decreased gross primary productivity and net CO2 uptake, caused by the unfavourable growing conditions and plant stress due to the soil moisture and vapour pressure deficits. Additionally, the CH4 emissions from the fen decreased during and after the drought. However, the timing and duration of drought effects varied between the fen and forest ecosystems, as C fluxes were affected sooner and had a shorter post-drought recovery time in the fen than forest. The differing CO2 flux response to weather variations showed that terrestrial ecosystems can have a contrasting impact on the landscape-level C balance in a changing climate, even if they function similarly most of the time.

Vegetation phenology, which refers to the seasonal changes in plant physiology, biomass and plant cover, is affected by many abiotic factors, such as precipitation, temperature and water availability. Phenology is also associated with the carbon dioxide (CO2) exchange between ecosystems and the atmosphere. We employed digital cameras to monitor the vegetation phenology of three northern boreal peatlands during five growing seasons. We derived a greenness index (green chromatic coordinate, GCC) from the images and combined the results with measurements of CO2 flux, air temperature and high-resolution satellite data (Sentinel-2). From the digital camera images it was possible to extract greenness dynamics on the vegetation community and even species level. The highest GCC and daily maximum gross photosynthetic production (GPPmax) were observed at the site with the highest nutrient availability and richest vegetation. The short-term temperature response of GCC depended on temperature and varied among the sites and months. Although the seasonal development and year-to-year variation in GCC and GPPmax showed consistent patterns, the short-term variation in GPPmax was explained by GCC only during limited periods. GCC clearly indicated the main phases of the growing season, and peatland vegetation showed capability to fully compensate for the impaired growth resulting from a late growing season start. The GCC data derived from Sentinel-2 and digital cameras showed similar seasonal courses, but a reliable timing of different phenological phases depended upon the temporal coverage of satellite data.

Arctic tundra is facing unprecedented warming, resulting in shifts in the vegetation, thaw regimes, and potentially in the ecosystem–atmosphere exchange of carbon (C). However, the estimates of regional carbon dioxide (CO2) and methane (CH4) budgets are highly uncertain. We measured CO2 and CH4 fluxes, vegetation composition and leaf area index (LAI), thaw depth, and soil wetness in Tiksi (71∘ N, 128∘ E), a heterogeneous site located within the prostrate dwarf-shrub tundra zone in northeastern Siberia. Using the closed chamber method, we determined the net ecosystem exchange (NEE) of CO2, ecosystem respiration in the dark (ER), ecosystem gross photosynthesis (Pg), and CH4 flux during the growing season. We applied a previously developed high-spatial-resolution land cover map over an area of 35.8 km2 for spatial extrapolation. Among the land cover types varying from barren to dwarf-shrub tundra and tundra wetlands, the NEE and Pg at the photosynthetically active photon flux density of 800 µmol m−2 h−1 (NEE800 and Pg800) were greatest in the graminoid-dominated habitats, i.e., streamside meadow and fens, with NEE800 and Pg800 of up to −21 (uptake) and 28 mmol m−2 h−1, respectively. Vascular LAI was a robust predictor of both NEE800 and Pg800 and, on a landscape scale, the fens were disproportionately important for the summertime CO2 sequestration. Dry tundra, including the dwarf-shrub and lichen tundra, had smaller CO2 exchange rates. The fens were the largest source of CH4, while the dry mineral soil tundra consumed atmospheric CH4, which on a landscape scale amounted to −9 % of the total CH4 balance during the growing season. The largest seasonal mean CH4 consumption rate of 0.02 mmol m−2 h−1 occurred in sand- and stone-covered barren areas. The high consumption rate agrees with the estimate based on the eddy covariance measurements at the same site. We acknowledge the uncertainty involved in spatial extrapolations due to a small number of replicates per land cover type. This study highlights the need to distinguish different land cover types including the dry tundra habitats to account for their different CO2 and CH4 flux patterns, especially the consumption of atmospheric CH4, when estimating tundra C exchange on a larger spatial scale.

The patterned microtopography of subarctic mires generates a variety of environmental conditions, and carbon dioxide (CO2) and methane (CH4) dynamics vary spatially among different plant community types (PCTs). We studied the CO2 and CH4 exchange between a subarctic fen and the atmosphere at Kaamanen in northern Finland based on flux chamber and eddy covariance measurements in 2017–2018. We observed strong spatial variation in carbon dynamics between the four main PCTs studied, which were largely controlled by water table level and differences in vegetation composition. The ecosystem respiration (ER) and gross primary productivity (GPP) increased gradually from the wettest PCT to the drier ones, and both ER and GPP were larger for all PCTs during the warmer and drier growing season 2018. We estimated that in 2017 the growing season CO2 balances of the PCTs ranged from −20 g C m−2 (Trichophorum tussock PCT) to 64 g C m−2 (string margin PCT), while in 2018 all PCTs were small CO2 sources (10–22 g C m−2). We observed small growing season CH4 emissions (< 1 g C m−2) from the driest PCT, while the other three PCTs had significantly larger emissions (mean 7.9, range 5.6–10.1 g C m−2) during the two growing seasons. Compared to the annual CO2 balance (−8.5 ± 4.0 g C m−2) of the fen in 2017, in 2018 the annual balance (−5.6 ± 3.7 g C m−2) was affected by an earlier onset of photosynthesis in spring, which increased the CO2 sink, and a drought event during summer, which decreased the sink. The CH4 emissions were also affected by the drought. The annual CH4 balance of the fen was 7.3 ± 0.2 g C m−2 in 2017 and 6.2 ± 0.1 g C m−2 in 2018. Thus, the carbon balance of the fen was close to zero in both years. The PCTs that were adapted to drier conditions provided ecosystem-level resilience to carbon loss due to water level drawdown.

Northern peatlands are projected to be crucial in future atmospheric methane (CH4) budgets and have a positive feedback on global warming. Fens receive nutrients from catchments via inflowing water and are more sensitive than bogs to variations in their ecohydrology. Yet, due to a lack of data detailing the impacts of moving water on microhabitats and CH4 fluxes in fens, large uncertainties remain with respect to predicting CH4 emissions from these sites under climate changes. We measured CH4 fluxes with manual chambers over three growing seasons (2017–2019) at a northern boreal fen. To address the spatial variation at the site where a stream flows through the long and narrow valley fen, we established sample plots at varying distances from the stream. To link the variations in CH4 emissions to environmental controls, we quantified water levels, peat temperature, dissolved oxygen concentration, vegetation composition, and leaf area index in combination with flux measurements during the growing season in 2019. We found that due to the flowing water, there was a higher water level, cooler peat temperatures, and more oxygen in the peat close to the stream, which also had the highest total leaf area and gross primary production (GPP) values but the lowest CH4 emissions. CH4 emissions were highest at an intermediate distance from the stream where the oxygen concentration in the surface peat was low but GPP was still high. Further from the stream, the conditions were drier and produced low CH4 emissions. Our results emphasize the key role of ecohydrology in CH4 dynamics in fens and, for the first time, show how a stream controls CH4 emissions in a flow-through fen. As valley fens are common peatland ecosystems from the Arctic to the temperate zones, future projections of global CH4 budgets need to take flowing water features into account.

The impact of atmospheric reactive nitrogen (Nr) deposition on carbon (C) sequestration in soils and biomass of unfertilized, natural, semi-natural and forest ecosystems has been much debated. Many previous results of this dC∕dN response were based on changes in carbon stocks from periodical soil and ecosystem inventories, associated with estimates of Nr deposition obtained from large-scale chemical transport models. This study and a companion paper (Flechard et al., 2020) strive to reduce uncertainties of N effects on C sequestration by linking multi-annual gross and net ecosystem productivity estimates from 40 eddy covariance flux towers across Europe to local measurement-based estimates of dry and wet Nr deposition from a dedicated collocated monitoring network. To identify possible ecological drivers and processes affecting the interplay between C and Nr inputs and losses, these data were also combined with in situ flux measurements of NO, N2O and CH4 fluxes; soil NO3- leaching sampling; and results of soil incubation experiments for N and greenhouse gas (GHG) emissions, as well as surveys of available data from online databases and from the literature, together with forest ecosystem (BASFOR) modelling. Multi-year averages of net ecosystem productivity (NEP) in forests ranged from −70 to 826 g C m−2 yr−1 at total wet + dry inorganic Nr deposition rates (Ndep) of 0.3 to 4.3 g N m−2 yr−1 and from −4 to 361 g C m−2 yr−1 at Ndep rates of 0.1 to 3.1 g N m−2 yr−1 in short semi-natural vegetation (moorlands, wetlands and unfertilized extensively managed grasslands). The GHG budgets of the forests were strongly dominated by CO2 exchange, while CH4 and N2O exchange comprised a larger proportion of the GHG balance in short semi-natural vegetation. Uncertainties in elemental budgets were much larger for nitrogen than carbon, especially at sites with elevated Ndep where Nr leaching losses were also very large, and compounded by the lack of reliable data on organic nitrogen and N2 losses by denitrification. Nitrogen losses in the form of NO, N2O and especially NO3- were on average 27 % (range 6 %–54 %) of Ndep at sites with Ndep −2 yr−1 versus 65 % (range 35 %–85 %) for Ndep > 3 g N m−2 yr−1. Such large levels of Nr loss likely indicate that different stages of N saturation occurred at a number of sites. The joint analysis of the C and N budgets provided further hints that N saturation could be detected in altered patterns of forest growth. Net ecosystem productivity increased with Nr deposition up to 2–2.5 g N m−2 yr−1, with large scatter associated with a wide range in carbon sequestration efficiency (CSE, defined as the NEP ∕ GPP ratio). At elevated Ndep levels (> 2.5 g N m−2 yr−1), where inorganic Nr losses were also increasingly large, NEP levelled off and then decreased. The apparent increase in NEP at low to intermediate Ndep levels was partly the result of geographical cross-correlations between Ndep and climate, indicating that the actual mean dC∕dN response at individual sites was significantly lower than would be suggested by a simple, straightforward regression of NEP vs. Ndep.

The effects of atmospheric nitrogen deposition (Ndep) on carbon (C) sequestration in forests have often been assessed by relating differences in productivity to spatial variations of Ndep across a large geographic domain. These correlations generally suffer from covariation of other confounding variables related to climate and other growth-limiting factors, as well as large uncertainties in total (dry + wet) reactive nitrogen (Nr) deposition. We propose a methodology for untangling the effects of Ndep from those of meteorological variables, soil water retention capacity and stand age, using a mechanistic forest growth model in combination with eddy covariance CO2 exchange fluxes from a Europe-wide network of 22 forest flux towers. Total Nr deposition rates were estimated from local measurements as far as possible. The forest data were compared with data from natural or semi-natural, non-woody vegetation sites. The response of forest net ecosystem productivity to nitrogen deposition (dNEP ∕ dNdep) was estimated after accounting for the effects on gross primary productivity (GPP) of the co-correlates by means of a meta-modelling standardization procedure, which resulted in a reduction by a factor of about 2 of the uncorrected, apparent dGPP ∕ dNdep value. This model-enhanced analysis of the C and Ndep flux observations at the scale of the European network suggests a mean overall dNEP ∕ dNdep response of forest lifetime C sequestration to Ndep of the order of 40–50 g C per g N, which is slightly larger but not significantly different from the range of estimates published in the most recent reviews. Importantly, patterns of gross primary and net ecosystem productivity versus Ndep were non-linear, with no further growth responses at high Ndep levels (Ndep > 2.5–3 g N m−2 yr−1) but accompanied by increasingly large ecosystem N losses by leaching and gaseous emissions. The reduced increase in productivity per unit N deposited at high Ndep levels implies that the forecast increased Nr emissions and increased Ndep levels in large areas of Asia may not positively impact the continent's forest CO2 sink. The large level of unexplained variability in observed carbon sequestration efficiency (CSE) across sites further adds to the uncertainty in the dC∕dN response.

The non-uniform spatial integration, an inherent feature of the eddy covariance (EC) method, creates a challenge for flux data interpretation in a heterogeneous environment, where the contribution of different land cover types varies with flow conditions, potentially resulting in biased estimates in comparison to the areally averaged fluxes and land cover attributes. We modelled flux footprints and characterized the spatial scale of our EC measurements in Tiksi, a tundra site in northern Siberia. We used leaf area index (LAI) and land cover class (LCC) data, derived from very-high-spatial-resolution satellite imagery and field surveys, and quantified the sensor location bias. We found that methane (CH4) fluxes varied strongly with wind direction (−0.09 to 0.59 µgCH4m-2s-1 on average) during summer 2014, reflecting the distribution of different LCCs. Other environmental factors had only a minor effect on short-term flux variations but influenced the seasonal trend. Using footprint weights of grouped LCCs as explanatory variables for the measured CH4 flux, we developed a multiple regression model to estimate LCC group-specific fluxes. This model showed that wet fen and graminoid tundra patches in locations with topography-enhanced wetness acted as strong sources (1.0 µgCH4m-2s-1 during the peak emission period), while mineral soils were significant sinks (−0.13 µgCH4m-2s-1). To assess the representativeness of measurements, we upscaled the LCC group-specific fluxes to different spatial scales. Despite the landscape heterogeneity and rather poor representativeness of EC data with respect to the areally averaged LAI and coverage of some LCCs, the mean flux was close to the CH4 balance upscaled to an area of 6.3 km2, with a location bias of 14 %. We recommend that EC site descriptions in a heterogeneous environment should be complemented with footprint-weighted high-resolution data on vegetation and other site characteristics.

Surface–atmosphere energy exchange is strongly ecosystem-specific. At the same time, as the energy balance constitutes responses of an ecosystem to environmental stressors including precipitation, humidity and solar radiation, it results in feedbacks of potential importance for the regional climate. Northern peatlands represent a diverse class of ecosystems that cover nearly 6 × 106 km2 in the Boreal region, which makes the inter-comparison of their energy balances an important objective. With this in mind we studied energy exchange across a broad spectrum of peatlands from pristine fens and bogs to forested and agriculturally managed peatlands, which represent a large fraction of the landscape in Finland and Sweden. The effects of management activities on the energy balance were extensively examined from the micrometeorological point of view, using eddy covariance data from eight sites in these two countries (56º 12'–62º 11' N, 13º 03'–30º 05' E). It appears that the surface energy balance varies widely amongst the different peatland types. Generally, energy exchange features including the Bowen ratio, surface conductance, coupling to the atmosphere, responses to water table fluctuations and vapour pressure deficit could be associated directly with the peatland type. The relative constancy of the Bowen ratio in natural open mires contrasted with its variation in tree-covered and agricultural peatlands. We conclude that the impacts of management and the consequences of land-use change in peatlands for the local and regional climate might be substantial.

Drainage of peatlands is expected to turn these ecosystems into carbon sources to the atmosphere. We measured carbon dynamics of a drained forested peatland in southern Finland over 4 years, including one with severe drought during growing season. Net ecosystem exchange (NEE) of carbon dioxide (CO2) was measured with the eddy covariance method from a mast above the forest. Soil and forest floor CO2 and methane (CH4) fluxes were measured from the strips and from ditches with closed chambers. Biomass and litter production were sampled, and soil subsidence was measured by repeated levellings of the soil surface. The drained peatland ecosystem was a strong sink of carbon dioxide in all studied years. Soil CO2 balance was estimated by subtracting the carbon sink of the growing tree stand from NEE, and it showed that the soil itself was a carbon sink as well. A drought period in one summer significantly decreased the sink through decreased gross primary production. Drought also decreased ecosystem respiration. The site was a small sink for CH4, even when emissions from ditches were taken into account. Despite the continuous carbon sink, peat surface subsided slightly during the 10-year measurement period, which was probably mainly due to compaction of peat. It is concluded that even 50 years after drainage this peatland site acted as a soil C sink due to relatively small changes in the water table and in plant community structure compared to similar undrained sites, and the significantly increased tree stand growth and litter production. Although the site is currently a soil C sink, simulation studies with process models are needed to test whether such sites could remain C sinks when managed for forestry over several tree-stand rotations.

Arctic tundra ecosystems will play a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity of Arctic landscapes. We examined spatial variation and linkages of soil and plant attributes in a site of Siberian Arctic tundra in Tiksi, northeast Russia, and evaluated possibilities to capture this variation by remote sensing for the benefit of carbon exchange measurements and landscape extrapolation. We distinguished nine land cover types (LCTs) and to characterize them, sampled 92 study plots for plant and soil attributes in 2014. Moreover, to test if variation in plant and soil attributes can be detected using remote sensing, we produced a normalized difference vegetation index (NDVI) and topographical parameters for each study plot using three very high spatial resolution multispectral satellite images. We found that soils ranged from mineral soils in bare soil and lichen tundra LCTs to soils of high percentage of organic matter (OM) in graminoid tundra, bog, dry fen and wet fen. OM content of the top soil was on average 14 g dm−3 in bare soil and lichen tundra and 89 g dm−3 in other LCTs. Total moss biomass varied from 0 to 820 g m−2, total vascular shoot mass from 7 to 112 g m−2 and vascular leaf area index (LAI) from 0.04 to 0.95 among LCTs. In late summer, soil temperatures at 15 cm depth were on average 14 °C in bare soil and lichen tundra, and varied from 5 to 9 °C in other LCTs. On average, depth of the biologically active, unfrozen soil layer doubled from early July to mid-August. When contrasted across study plots, moss biomass was positively associated with soil OM % and OM content and negatively associated with soil temperature, explaining 14–34 % of variation. Vascular shoot mass and LAI were also positively associated with soil OM content, and LAI with active layer depth, but only explained 6–15 % of variation. NDVI captured variation in vascular LAI better than in moss biomass, but while this difference was significant with late season NDVI, it was minimal with early season NDVI. For this reason, soil attributes associated with moss mass were better captured by early season NDVI. Topographic attributes were related to LAI and many soil attributes, but not to moss biomass and could not increase the amount of spatial variation explained in plant and soil attributes above that achieved by NDVI. The LCT map we produced had low to moderate uncertainty in predictions for plant and soil properties except for moss biomass and bare soil and lichen tundra LCTs. Our results illustrate a typical tundra ecosystem with great fine-scale spatial variation in both plant and soil attributes. Mosses dominate plant biomass and control many soil attributes, including OM % and temperature, but variation in moss biomass is difficult to capture by remote sensing reflectance, topography or a LCT map. Despite the general accuracy of landscape level predictions in our LCT approach, this indicates challenges in the spatial extrapolation of some of those vegetation and soil attributes that are relevant for the regional ecosystem and global climate models.

The influence of drought on plant functioning has received considerable attention in recent years, however our understanding of the response of carbon and water coupling to drought in terrestrial ecosystems still needs to be improved. A severe soil moisture drought occurred in southern Finland in the late summer of 2006. In this study, we investigated the response of water use efficiency to summer drought in a boreal Scots pine forest (Pinus sylvestris) on the daily time scale mainly using eddy covariance flux data from the Hyytiälä (southern Finland) flux site. In addition, simulation results from the JSBACH land surface model were evaluated against the observed results. Based on observed data, the ecosystem level water use efficiency (EWUE; the ratio of gross primary production, GPP, to evapotranspiration, ET) showed a decrease during the severe soil moisture drought, while the inherent water use efficiency (IWUE; a quantity defined as EWUE multiplied with mean daytime vapour pressure deficit, VPD) increased and the underlying water use efficiency (uWUE, a metric based on IWUE and a simple stomatal model, is the ratio of GPP multiplied with a square root of VPD to ET) was unchanged during the drought. The decrease in EWUE was due to the stronger decline in GPP than in ET. The increase in IWUE was because of the decreased stomatal conductance under increased VPD. The unchanged uWUE indicates that the trade-off between carbon assimilation and transpiration of the boreal Scots pine forest was not disturbed by this drought event at the site. The JSBACH simulation showed declines of both GPP and ET under the severe soil moisture drought, but to a smaller extent compared to the observed GPP and ET. Simulated GPP and ET led to a smaller decrease in EWUE but a larger increase in IWUE because of the severe soil moisture drought in comparison to observations. As in the observations, the simulated uWUE showed no changes in the drought event. The model deficiencies exist mainly due to the lack of the limiting effect of increased VPD on stomatal conductance during the low soil moisture condition. Our study provides a deeper understanding of the coupling of carbon and water cycles in the boreal Scots pine forest ecosystem and suggests possible improvements to land surface models, which play an important role in the prediction of biosphere–atmosphere feedbacks in the climate system.

Recent satellite observations of sun-induced chlorophyll fluorescence (SIF) are thought to provide a large-scale proxy for gross primary production (GPP), thus providing a new way to assess the performance of land surface models (LSMs). In this study, we assessed how well SIF is able to predict GPP in the Fenno-Scandinavian region and what potential limitations for its application exist. We implemented a SIF model into the JSBACH LSM and used active leaf-level chlorophyll fluorescence measurements (Chl F) to evaluate the performance of the SIF module at a coniferous forest at Hyytiälä, Finland. We also compared simulated GPP and SIF at four Finnish micrometeorological flux measurement sites to observed GPP as well as to satellite-observed SIF. Finally, we conducted a regional model simulation for the Fenno-Scandinavian region with JSBACH and compared the results to SIF retrievals from the GOME-2 (Global Ozone Monitoring Experiment-2) space-borne spectrometer and to observation-based regional GPP estimates. Both observations and simulations revealed that SIF can be used to estimate GPP at both site and regional scales. At regional scale the model was able to simulate observed SIF averaged over 5 years with r2 of 0.86. The GOME-2-based SIF was a better proxy for GPP than the remotely sensed fAPAR (fraction of absorbed photosynthetic active radiation by vegetation). The observed SIF captured the seasonality of the photosynthesis at site scale and showed feasibility for use in improving of model seasonality at site and regional scale.

We measured methane (CH4) exchange rates with automatic chambers at the forest floor of a nutrient-rich drained peatland in 2011–2013. The fen, located in southern Finland, was drained for forestry in 1969 and the tree stand is now a mixture of Scots pine, Norway spruce, and pubescent birch. Our measurement system consisted of six transparent chambers and stainless steel frames, positioned on a number of different field and moss layer compositions. Gas concentrations were measured with an online cavity ring-down spectroscopy gas analyzer. Fluxes were calculated with both linear and exponential regression. The use of linear regression resulted in systematically smaller CH4 fluxes by 10–45 % as compared to exponential regression. However, the use of exponential regression with small fluxes ( 4 m−2 h−1) typically resulted in anomalously large absolute fluxes and high hour-to-hour deviations. Therefore, we recommend that fluxes are initially calculated with linear regression to determine the threshold for low fluxes and that higher fluxes are then recalculated using exponential regression. The exponential flux was clearly affected by the length of the fitting period when this period was 4 flux: the forest floor acted as a CH4 sink particularly from early summer until the end of the year, while in late winter the flux was very small and fluctuated around zero. However, the magnitude of fluxes was relatively small throughout the year, ranging mainly from −130 to +100 µg CH4 m−2 h−1. CH4 emission peaks were observed occasionally, mostly in summer during heavy rainfall events. Diurnal variation, showing a lower CH4 uptake rate during the daytime, was observed in all of the chambers, mainly in the summer and late spring, particularly in dry conditions. It was attributed more to changes in wind speed than air or soil temperature, which suggest that physical rather than biological phenomena are responsible for the observed variation. The annual net CH4 exchange varied from −104 ± 30 to −505 ± 39 mg CH4 m−2 yr−1 among the six chambers, with an average of −219 mg CH4 m−2 yr−1 over the 2-year measurement period.

Tropical savannas and grasslands are estimated to contribute significantly to the total primary production of all terrestrial vegetation. Large parts of African savannas and grasslands are used for agriculture and cattle grazing, but the carbon flux data available from these areas are limited. This study explores carbon dioxide fluxes measured with the eddy covariance method for 3 years at a grazed savanna grassland in Welgegund, South Africa. The tree cover around the measurement site, grazed by cattle and sheep, was around 15 %. The night-time respiration was not significantly dependent on either soil moisture or soil temperature on a weekly temporal scale, whereas on an annual timescale higher respiration rates were observed when soil temperatures were higher. The carbon dioxide balances of the years 2010–2011, 2011–2012 and 2012–2013 were −85 ± 16, 67 ± 20 and 139 ± 13 gC m−2 yr−1, respectively. The yearly variation was largely determined by the changes in the early wet season fluxes (September to November) and in the mid-growing season fluxes (December to January). Early rainfall enhanced the respiratory capacity of the ecosystem throughout the year, whereas during the mid-growing season high rainfall resulted in high carbon uptake.

Subarctic and boreal emissions of CH4 are important contributors to the atmospheric greenhouse gas (GHG) balance and subsequently the global radiative forcing. Whilst N2O emissions may be lower, the much greater radiative forcing they produce justifies their inclusion in GHG studies. In addition to the quantification of flux magnitude, it is essential that we understand the drivers of emissions to be able to accurately predict climate-driven changes and potential feedback mechanisms. Hence this study aims to increase our understanding of what drives fluxes of CH4 and N2O in a subarctic forest/wetland landscape during peak summer conditions and into the shoulder season, exploring both spatial and temporal variability, and uses satellite-derived spectral data to extrapolate from chamber-scale fluxes to a 2 km × 2 km landscape area.From static chamber measurements made during summer and autumn campaigns in 2012 in the Sodankylä region of northern Finland, we concluded that wetlands represent a significant source of CH4 (3.35 ± 0.44 mg C m−2 h−1 during the summer campaign and 0.62 ± 0.09 mg C m−2 h−1 during the autumn campaign), whilst the surrounding forests represent a small sink (−0.06 ± −2 h−1 during the summer campaign and −0.03 ± −2 h−1 during the autumn campaign). N2O fluxes were near-zero across both ecosystems.We found a weak negative relationship between CH4 emissions and water table depth in the wetland, with emissions decreasing as the water table approached and flooded the soil surface and a positive relationship between CH4 emissions and the presence of Sphagnum mosses. Temperature was also an important driver of CH4 with emissions increasing to a peak at approximately 12 °C. Little could be determined about the drivers of N2O emissions given the small magnitude of the fluxes.A multiple regression modelling approach was used to describe CH4 emissions based on spectral data from PLEIADES PA1 satellite imagery across a 2 km × 2 km landscape. When applied across the whole image domain we calculated a CH4 source of 2.05 ± 0.61 mg C m−2 h−1. This was significantly higher than landscape estimates based on either a simple mean or weighted by forest/wetland proportion (0.99 ± 0.16, 0.93 ± 0.12 mg C m−2 h−1, respectively). Hence we conclude that ignoring the detailed spatial variability in CH4 emissions within a landscape leads to a potentially significant underestimation of landscape-scale fluxes. Given the small magnitude of measured N2O fluxes a similar level of detailed upscaling was not needed; we conclude that N2O fluxes do not currently comprise an important component of the landscape-scale GHG budget at this site.

The carbon dioxide (CO2) exchange of five different peatland systems across Europe with a wide gradient in land use intensity, water table depth, soil fertility and climate was simulated with the process oriented CoupModel. The aim of the study was to find out whether CO2 fluxes, measured at different sites, can be explained by common processes and parameters or to what extend a site specific configuration is needed. The model was calibrated to fit measured CO2 fluxes, soil temperature, snow depth and leaf area index (LAI) and resulting differences in model parameters were analyzed. Finding site independent model parameters would mean that differences in the measured fluxes could be explained solely by model input data: water table, meteorological data, management and soil inventory data. Seasonal variability in the major fluxes was well captured, when a site independent configuration was utilized for most of the parameters. Parameters that differed between sites included the rate of soil organic decomposition, photosynthetic efficiency, and regulation of the mobile carbon (C) pool from senescence to shooting in the next year. The largest difference between sites was the rate coefficient for heterotrophic respiration. Setting it to a common value would lead to underestimation of mean total respiration by a factor of 2.8 up to an overestimation by a factor of 4. Despite testing a wide range of different responses to soil water and temperature, rate coefficients for heterotrophic respiration were consistently the lowest on formerly drained sites and the highest on the managed sites. Substrate decomposability, pH and vegetation characteristics are possible explanations for the differences in decomposition rates. Specific parameter values for the timing of plant shooting and senescence, the photosynthesis response to temperature, litter fall and plant respiration rates, leaf morphology and allocation fractions of new assimilates, were not needed, even though the gradient in site latitude ranged from 48° N (southern Germany) to 68° N (northern Finland) differed largely in their vegetation. This was also true for common parameters defining the moisture and temperature response for decomposition, leading to the conclusion that a site specific interpretation of these processes is not necessary. In contrast, the rate of soil organic decomposition, photosynthetic efficiency, and the regulation of the mobile carbon pool need to be estimated from available information on specific soil conditions, vegetation and management of the ecosystems, to be able to describe CO2 fluxes under different conditions.

This paper aims to assess the spatial variability in the response of CO2 exchange to irradiance across the Arctic tundra during peak season using light response curve (LRC) parameters. This investigation allows us to better understand the future response of Arctic tundra under climatic change. Peak season data were collected during different years (between 1998 and 2010) using the micrometeorological eddy covariance technique from 12 circumpolar Arctic tundra sites, in the range of 64–74° N. The LRCs were generated for 14 days with peak net ecosystem exchange (NEE) using an NEE–irradiance model. Parameters from LRCs represent site-specific traits and characteristics describing the following: (a) NEE at light saturation (Fcsat), (b) dark respiration (Rd), (c) light use efficiency (α), (d) NEE when light is at 1000 μmol m−2 s−1 (Fc1000), (e) potential photosynthesis at light saturation (Psat) and (f) the light compensation point (LCP). Parameterization of LRCs was successful in predicting CO2 flux dynamics across the Arctic tundra. We did not find any trends in LRC parameters across the whole Arctic tundra but there were indications for temperature and latitudinal differences within sub-regions like Russia and Greenland. Together, leaf area index (LAI) and July temperature had a high explanatory power of the variance in assimilation parameters (Fcsat, Fc1000 and Psat, thus illustrating the potential for upscaling CO2 exchange for the whole Arctic tundra. Dark respiration was more variable and less correlated to environmental drivers than were assimilation parameters. This indicates the inherent need to include other parameters such as nutrient availability, substrate quantity and quality in flux monitoring activities.

The northern terrestrial net ecosystem carbon balance (NECB) is contingent on inputs from vegetation gross primary productivity (GPP) to offset the ecosystem respiration (Reco) of carbon dioxide (CO2) and methane (CH4) emissions, but an effective framework to monitor the regional Arctic NECB is lacking. We modified a terrestrial carbon flux (TCF) model developed for satellite remote sensing applications to evaluate wetland CO2 and CH4 fluxes over pan-Arctic eddy covariance (EC) flux tower sites. The TCF model estimates GPP, CO2 and CH4 emissions using in situ or remote sensing and reanalysis-based climate data as inputs. The TCF model simulations using in situ data explained > 70% of the r2 variability in the 8 day cumulative EC measured fluxes. Model simulations using coarser satellite (MODIS) and reanalysis (MERRA) records accounted for approximately 69% and 75% of the respective r2 variability in the tower CO2 and CH4 records, with corresponding RMSE uncertainties of &leq; 1.3 g C m−2 d−1 (CO2) and 18.2 mg C m−2 d−1 (CH4). Although the estimated annual CH4 emissions were small (< 18 g C m−2 yr−1) relative to Reco (> 180 g C m−2 yr−1), they reduced the across-site NECB by 23% and contributed to a global warming potential of approximately 165 ± 128 g CO2eq m−2 yr−1 when considered over a 100 year time span. This model evaluation indicates a strong potential for using the TCF model approach to document landscape-scale variability in CO2 and CH4 fluxes, and to estimate the NECB for northern peatland and tundra ecosystems.

Since the advancement in CH4 gas analyser technology and its applicability to eddy covariance flux measurements, monitoring of CH4 emissions is becoming more widespread. In order to accurately determine the greenhouse gas balance, high quality gap-free data is required. Currently there is still no consensus on CH4 gap-filling methods, and methods applied are still study-dependent and often carried out on low resolution, daily data. In the current study, we applied artificial neural networks to six distinctively different CH4 time series from high latitudes, explain the method and test its functionality. We discuss the applicability of neural networks in CH4 flux studies, the advantages and disadvantages of this method, and what information we were able to extract from such models. Three different approaches were tested by including drivers such as air and soil temperature, barometric air pressure, solar radiation, wind direction (indicator of source location) and in addition the lagged effect of water table depth and precipitation. In keeping with the principle of parsimony, we included up to five of these variables traditionally measured at CH4 flux measurement sites. Fuzzy sets were included representing the seasonal change and time of day. High Pearson correlation coefficients (r) of up to 0.97 achieved in the final analysis are indicative for the high performance of neural networks and their applicability as a gap-filling method for CH4 flux data time series. This novel approach which we show to be appropriate for CH4 fluxes is a step towards standardising CH4 gap-filling protocols.

Drainage for forestry purposes increases the depth of the oxic peat layer and leads to increased growth of shrubs and trees. Concurrently, the production and uptake of the greenhouse gases carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) change: due to the accelerated decomposition of peat in the presence of oxygen, drained peatlands are generally considered to lose peat carbon (C). We measured CO2 exchange with the eddy covariance (EC) method above a drained nutrient-poor peatland forest in southern Finland for 16 months in 2004–2005. The site, classified as a dwarf-shrub pine bog, had been ditched about 35 years earlier. CH4 and N2O fluxes were measured at 2–5-week intervals with the chamber technique. Drainage had resulted in a relatively little change in the water table level, being on average 40 cm below the ground in 2005. The annual net ecosystem exchange was −870 ± 100 g CO2 m−2 yr−1 in the calendar year 2005, indicating net CO2 uptake from the atmosphere. The site was a small sink of CH4 (−0.12 g CH4 m−2 yr−1) and a small source of N2O (0.10 g N2O m−2 yr−1). Photosynthesis was detected throughout the year when the air temperature exceeded −3 °C. As the annual accumulation of C in the above and below ground tree biomass (175 ± 35 g C m−2) was significantly lower than the accumulation observed by the flux measurement (240 ± 30 g C m−2), about 65 g C m−2 yr−1 was likely to have accumulated as organic matter into the peat soil. This is a higher average accumulation rate than previously reported for natural northern peatlands, and the first time C accumulation has been shown by EC measurements to occur in a forestry-drained peatland. Our results suggest that forestry-drainage may significantly increase the CO2 uptake rate of nutrient-poor peatland ecosystems.

The seasonality of the NEE of the northern boreal coniferous forests was investigated by means of inversion modelling using eddy covariance data. Eddy covariance data was used to optimize the biochemical model parameters. Our study sites consisted of three Scots pine (l. Pinus sylvestris) forests and one Norway spruce (l. Picea abies) forest that were located in Finland and Sweden. We obtained temperature and seasonal dependence for the biochemical model parameters: the maximum rate of carboxylation (Vc(max)) and the maximum rate of electron transport (Jmax). Both of the parameters were optimized without assumptions about their mutual magnitude. The values obtained for the biochemical model parameters were similar at all the sites during summer time. To describe seasonality, different temperature fits were made for the spring, summer and autumn periods. During summer, average Jmax across the sites was 54.0 μmol m−2 s−1 (variance 31.2 μmol m−2 s−1) and Vc(max) was 12.0 μmol m−2 s−1 (variance 6.6 μmol m−2 s−1) at 17°C. The sensitivity of the model to LAI and atmospheric soil water stress was also studied. The impact of seasonality on annual GPP was 17% when only summertime parameterization was used throughout the year compared to seasonally changing parameterizations.

We applied a site evaluation approach combining Lagrangian Stochastic footprint modeling with a quality assessment approach for eddy-covariance data to 25 forested sites of the CarboEurope-IP network. The analysis addresses the spatial representativeness of the flux measurements, instrumental effects on data quality, spatial patterns in the data quality, and the performance of the coordinate rotation method. Our findings demonstrate that application of a footprint filter could strengthen the CarboEurope-IP flux database, since only one third of the sites is situated in truly homogeneous terrain. Almost half of the sites experience a significant reduction in eddy-covariance data quality under certain conditions, though these effects are mostly constricted to a small portion of the dataset. Reductions in data quality of the sensible heat flux are mostly induced by characteristics of the surrounding terrain, while the latent heat flux is subject to instrumentation-related problems. The Planar-Fit coordinate rotation proved to be a reliable tool for the majority of the sites using only a single set of rotation angles. Overall, we found a high average data quality for the CarboEurope-IP network, with good representativeness of the measurement data for the specified target land cover types.