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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.

Accurate estimates of net ecosystem CO2 exchange (NEE) would improve the understanding of natural carbon sources and sinks and their role in the regulation of global atmospheric carbon. In this work, we use and compare the random forest (RF) and the gradient boosting (GB) machine learning (ML) methods for predicting year-round 6 h NEE over 1996–2018 in a pine-dominated boreal forest in southern Finland and analyze the predictability of NEE. Additionally, aggregation to weekly NEE values was applied to get information about longer term behavior of the method. The meteorological ERA5 reanalysis variables were used as predictors. Spatial and temporal neighborhood (predictor lagging) was used to provide the models more data to learn from, which was found to improve considerably the accuracy of both ML approaches compared to using only the nearest grid cell and time step. Both ML methods can explain temporal variability of NEE in the observational site of this study with meteorological predictors, but the GB method was more accurate. Only minor signs of overfitting could be detected for the GB algorithm when redundant variables were included. The accuracy of the approaches, measured mainly using cross-validated R2 score between the model result and the observed NEE, was high, reaching a best estimate value of 0.92 for GB and 0.88 for RF. In addition to the standard RF approach, we recommend using GB for modeling the CO2 fluxes of the ecosystems due to its potential for better performance.

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.

The role of precipitation (P) variability with respect to evapotranspiration (ET) and its two components, transpiration (T) and evaporation (E), from savannas continues to draw significant research interest given its relevance to a number of ecohydrological applications. Our study reports on 6 years of measured ET and estimated T and E from a grazed savanna grassland at Welgegund, South Africa. Annual P varied significantly with respect to amount (508 to 672 mm yr−1), with dry years characterized by infrequent early-season rainfall. T was determined using annual water-use efficiency and gross primary production estimates derived from eddy-covariance measurements of latent heat flux and net ecosystem CO2 exchange rates. The computed annual T for the 4 wet years with frequent early wet-season rainfall was nearly constant, 326±19 mm yr−1 (T/ET=0.51), but was lower and more variable between the 2 dry years (255 and 154 mm yr−1, respectively). Annual T and T/ET were linearly related to the early wet-season storm frequency. The constancy of annual T during wet years is explained by the moderate water stress of C4 grasses as well as trees' ability to use water from deeper layers. During extreme drought, grasses respond to water availability with a dieback–regrowth pattern, reducing leaf area and transpiration and, thus, increasing the proportion of transpiration contributed by trees. The works suggest that the early-season P distribution explains the interannual variability in T, which should be considered when managing grazing and fodder production in these grasslands.

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.

Better monitoring, reporting, and verification (MRV) of the amount, additionality, and persistence of the sequestered soil carbon is needed to understand the best carbon farming practices for different soils and climate conditions, as well as their actual climate benefits or cost efficiency in mitigating greenhouse gas emissions. This paper presents our Field Observatory Network (FiON) of researchers, farmers, companies, and other stakeholders developing carbon farming practices. FiON has established a unified methodology towards monitoring and forecasting agricultural carbon sequestration by combining offline and near-real-time field measurements, weather data, satellite imagery, modeling, and computing networks. FiON's first phase consists of two intensive research sites and 20 voluntary pilot farms testing carbon farming practices in Finland. To disseminate the data, FiON built a web-based dashboard called the Field Observatory (v1.0, https://www.fieldobservatory.org/, last access: 3 February 2022). The Field Observatory is designed as an online service for near-real-time model–data synthesis, forecasting, and decision support for the farmers who are able to monitor the effects of carbon farming practices. The most advanced features of the Field Observatory are visible on the Qvidja site, which acts as a prototype for the most recent implementations. Overall, FiON aims to create new knowledge on agricultural soil carbon sequestration and effects of carbon farming practices as well as provide an MRV tool for decision support.

Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO2) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO2 fluxes and to better estimate the terrestrial ABZ CO2 budget. ABCflux is openly and freely available online (Virkkala et al., 2021b, https://doi.org/10.3334/ORNLDAAC/1934).

A significant proportion of the global carbon emissions to the atmosphere originate from agriculture. Therefore, continuous long-term monitoring of CO2 fluxes is essential to understand the carbon dynamics and balances of different agricultural sites. Here we present results from a new eddy covariance flux measurement site located in southern Finland. We measured CO2 and H2O fluxes at this agricultural grassland site for 2 years, from May 2018 to May 2020. In particular the first summer experienced prolonged dry periods, which affected the CO2 fluxes, and substantially larger fluxes were observed in the second summer. During the dry summer, leaf area index (LAI) was notably lower than in the second summer. Water use efficiency increased with LAI in a similar manner in both years, but photosynthetic capacity per leaf area was lower during the dry summer. The annual carbon balance was calculated based on the CO2 fluxes and management measures, which included input of carbon as organic fertilizers and output as yield. The carbon balance of the field was −57 ± 10 and −86 ± 12 g C m−2 yr−1 in the first and second study years, respectively.

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.

The most common forest management method in Fennoscandia is rotation forestry, including clear-cutting and forest regeneration. In clear-cutting, stem wood is removed and the logging residues are either removed or left on site. Clear-cutting changes the microclimate and vegetation structure at the site, both of which affect the site's carbon balance. Peat soils with poor aeration and high carbon densities are especially prone to such changes, and significant changes in greenhouse gas exchange can be expected. We measured carbon dioxide (CO2) and energy fluxes with the eddy covariance method for 2 years (April 2016–March 2018) after clear-cutting a drained peatland forest. We observed a significant rise (23 cm) in the water table level and a large CO2 source (first year: 3086±148 g CO2 m−2 yr−1; second year: 2072±124 g CO2 m−2 yr−1). These large CO2 emissions resulted from the very low gross primary production (GPP) following the removal of photosynthesizing trees and the decline of ground vegetation, unable to compensate for the decomposition of logging residues and peat. During the second summer (June–August) after the clear-cutting, GPP had already increased by 96 % and total ecosystem respiration decreased by 14 % from the previous summer. The mean daytime ratio of sensible to latent heat flux decreased after harvesting from 2.6 in May 2016 to 1.0 in August 2016, and in 2017 it varied mostly within 0.6–1.0. In April–September, the mean daytime sensible heat flux was 33 % lower and latent heat flux 40 % higher in 2017, probably due to the recovery of ground vegetation that increased evapotranspiration and albedo of the site. In addition to CO2 and energy fluxes, we measured methane (CH4) and nitrous oxide (N2O) fluxes with manual chambers. After the clear-cutting, the site turned from a small CH4 sink into a small source and from N2O neutral to a significant N2O source. Compared to the large CO2 emissions, the 100-year global warming potential (GWP100) of the CH4 emissions was negligible. Also, the GWP100 due to increased N2O emissions was less than 10 % of that of the CO2 emission change.

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.

In this study, we introduce new observations of sea–air fluxes of carbon dioxide using the eddy covariance method. The measurements took place at the Utö Atmospheric and Marine Research Station on the island of Utö in the Baltic Sea in July–October 2017. The flux measurement system is based on a closed-path infrared gas analyzer (LI-7000, LI-COR) requiring only occasional maintenance, making the station capable of continuous monitoring. However, such infrared gas analyzers are prone to significant water vapor interference in a marine environment, where CO2 fluxes are small.Two LI-7000 analyzers were run in parallel to test the effect of a sample air drier which dampens water vapor fluctuations and a virtual impactor, included to remove liquid sea spray, both of which were attached to the sample air tubing of one of the analyzers. The systems showed closely similar (R2 = 0.99) sea–air CO2 fluxes when the latent heat flux was low, which proved that neither the drier nor the virtual impactor perturbed the CO2 flux measurement. However, the undried measurement had a positive bias that increased with increasing latent heat flux, suggesting water vapor interference.For both systems, cospectral densities between vertical wind speed and CO2 molar fraction were distributed within the expected frequency range, with a moderate attenuation of high-frequency fluctuations. While the setup equipped with a drier and a virtual impactor generated a slightly higher flux loss, we opt for this alternative for its reduced water vapor cross-sensitivity and better protection against sea spray. The integral turbulence characteristics were found to agree with the universal stability dependence observed over land. Nonstationary conditions caused unphysical results, which resulted in a high percentage (65 %) of discarded measurements. After removing the nonstationary cases, the direction of the sea–air CO2 fluxes was in good accordance with independently measured CO2 partial pressure difference between the sea and the atmosphere. Atmospheric CO2 concentration changes larger than 2 ppm during a 30 min averaging period were found to be associated with the nonstationarity of CO2 fluxes.

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.

In recent years, monitoring of the status of ecosystems using low-cost web (IP) or time lapse cameras has received wide interest. With broad spatial coverage and high temporal resolution, networked cameras can provide information about snow cover and vegetation status, serve as ground truths to Earth observations and be useful for gap-filling of cloudy areas in Earth observation time series. Networked cameras can also play an important role in supplementing laborious phenological field surveys and citizen science projects, which also suffer from observer-dependent observation bias. We established a network of digital surveillance cameras for automated monitoring of phenological activity of vegetation and snow cover in the boreal ecosystems of Finland. Cameras were mounted at 14 sites, each site having 1–3 cameras. Here, we document the network, basic camera information and access to images in the permanent data repository (http://www.zenodo.org/communities/phenology_camera/). Individual DOI-referenced image time series consist of half-hourly images collected between 2014 and 2016 (https://doi.org/10.5281/zenodo.1066862). Additionally, we present an example of a colour index time series derived from images from two contrasting sites.

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.

Digital repeat photography has become a widely used tool for assessing the annual course of vegetation phenology of different ecosystems. By using the green chromatic coordinate (GCC) as a greenness measure, we examined the feasibility of digital repeat photography for assessing the vegetation phenology in two contrasting high-latitude ecosystems. Ecosystem–atmosphere CO2 fluxes and various meteorological variables were continuously measured at both sites. While the seasonal changes in GCC were more obvious for the ecosystem that is dominated by annual plants (open wetland), clear seasonal patterns were also observed for the evergreen ecosystem (coniferous forest). Daily and seasonal time periods with sufficient solar radiation were determined based on images of a grey reference plate. The variability in cloudiness had only a minor effect on GCC, and GCC did not depend on the sun angle and direction either. The daily GCC of wetland correlated well with the daily photosynthetic capacity estimated from the CO2 flux measurements. At the forest site, the correlation was high in 2015 but there were discernible deviations during the course of the summer of 2014. The year-to-year differences were most likely generated by meteorological conditions, with higher temperatures coinciding with higher GCCs. In addition to depicting the seasonal course of ecosystem functioning, GCC was shown to respond to environmental changes on a timescale of days. Overall, monitoring of phenological variations with digital images provides a powerful tool for linking gross primary production and phenology.

The Meteorological Synthesizing Centre-West (MSC-W) of the European Monitoring and Evaluation Programme (EMEP) has been performing model calculations in support of the Convention on Long Range Transboundary Air Pollution (CLRTAP) for more than 30 years. The EMEP MSC-W chemical transport model is still one of the key tools within European air pollution policy assessments. Traditionally, the model has covered all of Europe with a resolution of about 50 km × 50 km, and extending vertically from ground level to the tropopause (100 hPa). The model has changed extensively over the last ten years, however, with flexible processing of chemical schemes, meteorological inputs, and with nesting capability: the code is now applied on scales ranging from local (ca. 5 km grid size) to global (with 1 degree resolution). The model is used to simulate photo-oxidants and both inorganic and organic aerosols. In 2008 the EMEP model was released for the first time as public domain code, along with all required input data for model runs for one year. The second release of the EMEP MSC-W model became available in mid 2011, and a new release is targeted for summer 2012. This publication is intended to document this third release of the EMEP MSC-W model. The model formulations are given, along with details of input data-sets which are used, and a brief background on some of the choices made in the formulation is presented. The model code itself is available at www.emep.int, along with the data required to run for a full year over Europe.

The DO3SE (Deposition of O3 for Stomatal Exchange) model is an established tool for estimating ozone (O3) deposition, stomatal flux and impacts to a variety of vegetation types across Europe. It has been embedded within the EMEP (European Monitoring and Evaluation Programme) photochemical model to provide a policy tool capable of relating the flux-based risk of vegetation damage to O3 precursor emission scenarios for use in policy formulation. A key limitation of regional flux-based risk assessments has been the assumption that soil water deficits are not limiting O3 flux due to the unavailability of evaluated methods for modelling soil water deficits and their influence on stomatal conductance (gsto), and subsequent O3 flux. This paper describes the development and evaluation of a method to estimate soil moisture status and its influence on gsto for a variety of forest tree species. This DO3SE soil moisture module uses the Penman-Monteith energy balance method to drive water cycling through the soil-plant-atmosphere system and empirical data describing gsto relationships with pre-dawn leaf water status to estimate the biological control of transpiration. We trial four different methods to estimate this biological control of the transpiration stream, which vary from simple methods that relate soil water content or potential directly to gsto, to more complex methods that incorporate hydraulic resistance and plant capacitance that control water flow through the plant system. These methods are evaluated against field data describing a variety of soil water variables, gsto and transpiration data for Norway spruce (Picea abies), Scots pine (Pinus sylvestris), birch (Betula pendula), aspen (Populus tremuloides), beech (Fagus sylvatica) and holm oak (Quercus ilex) collected from ten sites across Europe and North America. Modelled estimates of these variables show consistency with observed data when applying the simple empirical methods, with the timing and magnitude of soil drying events being captured well across all sites and reductions in transpiration with the onset of drought being predicted with reasonable accuracy. The more complex methods, which incorporate hydraulic resistance and plant capacitance, perform less well, with predicted drying cycles consistently underestimating the rate and magnitude of water loss from the soil. A sensitivity analysis showed that model performance was strongly dependent upon the local parameterisation of key model drivers such as the maximum gsto, soil texture, root depth and leaf area index. The results suggest that the simple modelling methods that relate gsto directly to soil water content and potential provide adequate estimates of soil moisture and influence on gsto such that they are suitable to be used to assess the potential risk posed by O3 to forest trees across Europe.

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.

This paper addresses the potential role of surface wetness in ozone deposition to plant foliage. We studied Scots pine foliage in field conditions at the SMEARII field measurement station in Finland. We used a combination of data from flux measurement at the shoot (enclosure) and canopy scale (eddy covariance), information from foliage surface wetness sensors, and a broad array of ancillary measurements such as radiation, precipitation, temperature, and relative humidity. Environmental conditions were defined as moist during rain or high relative humidity and during the subsequent twelve hours from such events, circumstances that were frequent at this boreal site. From the measured fluxes we estimated the ozone conductance using it as the expression of the strength of ozone removal surface sink or total deposition. Further, we estimated the stomatal contribution and the remaining deposition was interpreted and analysed as the non-stomatal sink. The combined time series of measurements showed that both shoot and canopy-scale ozone total deposition were enhanced when moist conditions occurred. On average, the estimated stomatal deposition accounted for half of the measured removal at the shoot scale and one third at the canopy scale. However, during dry conditions the estimated stomatal uptake predicted the behaviour of the measured deposition, but during moist conditions there was disagreement. The estimated non-stomatal sink was analysed against several environmental factors and the clearest connection was found with ambient relative humidity. The relationship disappeared under 70% relative humidity, a threshold that coincides with the value at which surface moisture gathers at the foliage surface according to the leaf surface wetness measurements. This suggests the non-stomatal ozone sink on the foliage to be modulated by the surface films. We attempted to extract such potential modulation with the estimated film formation via the theoretical expression of adsorption. Whereas this procedure could predict the behaviour of the non-stomatal sink, it implied a chemical sink that was not accountable as simple ozone decomposition. We discuss the existence of other mechanisms whose relevance in the removal of ozone needs to be clarified, in particular: a significant nocturnal stomatal aperture neglected in the estimations, and a potentially large chemical sink offered by reactive biogenic organic volatile compounds.