The flux measurements were conducted at the Qvidja farm in southern Finland (60.29550∘ N, 22.39281∘ E; elevation 5 m) from May 2018 to May 2020 (Fig. ). The site belongs to the hemiboreal climate zone. From 1981 to 2010, the mean annual air temperature and precipitation at the Kaarina Yltöinen weather station, located 13 km northeast of Qvidja, were 5.4 ∘C and 679 mm, respectively . The experimental field in Qvidja has mineral soil (clay loam), and it covers 16.25 ha. It was cultivated as forage grassland during the study years. From 2008 to 2016, the field was managed intensively with conventional practices, and it was in annual crop rotation. In 2017, the field management practices were converted towards more sustainable and environmentally friendly farming by increasing the use of organic fertilizers and perennials, restricting the use of pesticides and increasing plant species biodiversity. The current grass and clover mixture was sown as an undergrown species with broad bean in spring 2017. The predominant species were timothy (Phleum pratense), meadow fescue (Festuca pratensis) and white clover (Trifolium repens).

Grass was harvested for silage for the first time on 12 June 2018. As the grass cover was fairly sparse later in the summer due to drought, oversowing was done on 3 September 2018 to restore the drought-induced damage. The seed mixture included 35 % of timothy, 30 % of rye grasses (Lolium spp.), 20 % of common meadow grass (Poa pratensis) and 15 % of red fescue (Festuca rubra). Timothy, meadow fescue and clover remained as the predominant species in 2019 and early 2020. On 21 August 2018, the grass was cut at approximately 15 cm, but the yield was left in the field. The second harvest of 2018 occurred on 23 September. In 2019, the grass was harvested on 11 June and 20 August. In June 2018, a conventional cutting height of 6 cm was used, whereas in the other harvests the grass was cut at 15 cm.

In 2018, the field was fertilized twice, on 16 July and 24 August, with 2800 and 1800 kg ha-1 of NK-molasses, respectively (Table ). NK-molasses is a byproduct of the sugar industry. It contained 67 % of organic matter (OM) and 4.4 % of nitrogen and had the C:N ratio of 9. According to the product information, the molasses included 205 g kg-1 of organic carbon. In addition, it contained potassium and small proportions of sulfur, magnesium, calcium and sodium.

In May 2019, the field was fertilized with a mixture of side products from industries of starch potato processing, biowaste processing and ethanol production out of sawdust. This fertilization mixture contained 70 % (of dry weight) of OM, 1.3 % of nitrogen, 0.2 % of phosphorus, 3 % of potassium and 0.4 % of sulfur, as well as small amounts of calcium, magnesium, zinc, copper and manganese. Approximately 4600 kg ha-1 was applied to the field on 8 May (Table ). On 26 June after the first harvest, 220 kg ha-1 of mineral fertilizers was applied. This fertilizer contained 23 % of nitrogen, 10 % of phosphorus and 8 % of potassium.

The CO2 and H2O fluxes were measured with the micrometeorological EC method. The flux measurements started on 3 May 2018, and here we analysed data collected from 4 May 2018 to 3 May 2020. From this point on, the periods of 4 May 2018–3 May 2019 and 4 May 2019–3 May 2020 are referred to as the first and second EC measurement years, respectively.

The EC instrumentation consisted of an enclosed infrared gas analyser (LI-7200, LI-COR Biosciences, NE, USA), which detects the CO2 and H2O mixing ratios, and a three-dimensional sonic anemometer (uSonic-3 Scientific, METEK GmbH, Elmshorn, Germany) to measure wind speed and air temperature. The data were recorded at 10 Hz frequency. The measurement height was 2.3 m. The flow rate was about 12 L min-1, and the length of the 4 mm stainless-steel inlet tube with 2 µm Swagelok sinter was 0.8 m. The CO2 measurements were regularly checked with zero and span gases, and the LI-7200 was recalibrated when necessary. The H2O measurements were compared with the data obtained from a dedicated humidity sensor; no recalibration was necessary.

The micrometeorological sign convention is used throughout the paper, with a negative value indicating the flux from the atmosphere to the ecosystem (net uptake) and a positive value indicating the flux from the ecosystem to the atmosphere (net emission).

Auxiliary meteorological measurements were conducted next to the flux tower. These included soil moisture observations at the depth of 0.1 m (ML3 ThetaProbe sensor, Delta-T Devices Ltd., Cambridge, UK) and soil temperature profiles at the depths of 5, 10 and 30 cm (Pt100 IKES sensors, Nokeval Oy, Nokia, Finland). The soil temperature data were collected with a Vaisala QML201C datalogger (Vaisala Oyj, Vantaa, Finland). Photosynthetically active radiation (PQS PAR sensor, Kipp & Zonen B.V., Delft, the Netherlands), global and reflected solar radiation (CMP3 radiometer, Kipp & Zonen), and air temperature and relative humidity (Humicap HMP155, Vaisala Oyj) were measured at the height of 1.8 m. In addition, precipitation was measured with a weighing rain gauge (Pluvio2, OTT HydroMet GmbH, Kempten, Germany). Meteorological measurements started on 8 May 2018, and the data were recorded as 30 min averages, excluding the precipitation which was recorded as 1 min values. Snow depth was recorded at the weather station of Kaarina Yltöinen.

The leaf area index (LAI) data were obtained from the Sentinel-2 satellite as daily values on the clear-sky days. LAI was calculated from the Sentinel-2 bottom-of-atmosphere products (L2A) using the Google Earth Engine (GEE) and a Python implementation of the Biophysical Processor toolbox available in Sentinel Application Platform (SNAP) software. The cloudy, cloud-shadowed and snowy data were filtered out using the scene classification band available in the L2A products.

The turbulent fluxes were determined as the covariance between the variations in vertical wind component and gas mixing ratio recorded at 10 Hz. They were calculated as 30 min block averages applying standard procedures, including double coordinate rotation and lag determination based on cross-correlation analysis . The systematic flux loss due to the incomplete frequency response of the measurement system was corrected according to the empirical method described by .

The EC data from 5 January to 28 March 2019 were affected by technical issues with an inlet filter, which resulted in an erroneous reading of the internal analyser pressure. For this period, the 10 Hz mixing ratios were recalculated from the recorded absorptance data using the instrument-specific calibration functions. The mean CO2 mixing ratio was set to 410 ppm in these calculations.

The following acceptance criteria were applied to screen the 30 min averaged CO2 flux data: number of spikes in the raw data <150 of 18 000, relative stationarity of CO2 flux <50 %, mean CO2 mixing ratio >380 ppm, variance of CO2 mixing ratio <15 ppm2 between April and September and <5 ppm2 between October and March, and wind direction within 0–30∘ or 140–360∘. Furthermore, the data were discarded during the periods of weak turbulence and when the flux footprint was not sufficiently representative of the target grassland, as estimated with the footprint model of . For these, we applied a friction velocity limit of 0.06 m s-1 and a cumulative footprint limit of 0.7. The further screening applied to H2O fluxes included H2O flux >0, relative stationarity of H2O flux <50 % and variance of H2O mixing ratio <1 (mmol mol-1)2. After applying these filtering criteria, the coverage of CO2 and H2O flux data accepted for further analysis was 44 % and 30 % of all the 30 min periods (i.e. total of 35 088 time steps) during the 2 measurement years, respectively (for CO2, day/night 55 %/33 %, April–September/October–March 48 %/38 %; for H2O, day/night 49 %/11 %, April–September/October–March 41 %/16 %). Most of the accepted CO2 and H2O flux data were collected when the wind direction was in the south-southwest sector (Fig. ).

To calculate CO2 balances and to analyse the components of the net ecosystem exchange between the field and the atmosphere, the measured CO2 flux data (i.e. net ecosystem exchange, NEE) were partitioned to GPP and total ecosystem respiration (Reco) and gap-filled based on this partitioning: 1NEE=GPP+Reco. The gap-filled GPP and Reco were calculated with empirical response functions by first fitting these functions to the flux data. Reco was expressed as a function of temperature : 2Reco=R0eE01T1-1Ta-T0, where R0 is the respiration rate (mg m-2 s-1) at the reference temperature of 283.15 K, T0=227.13 K, T1=56.02 K, E0 is ecosystem sensitivity coefficient that describes the temperature response of soil respiration and Ta is the air temperature.

GPP was modelled as a function of photosynthetically active radiation (PAR, µmol m-2 s-1) as 3GPP=α×PAR×GPmaxα×PAR+GPmax, where α is the apparent quantum yield (mg µmol-1), and GPmax⁡ denotes the asymptotic CO2 uptake rate in optimal light conditions (mg m-2 s-1). Further details on the gap-filling procedure are provided in Appendix . Energy fluxes were gap-filled following the description in Appendix .

To study the differences in photosynthetic capacity of the grass field between the two growing seasons, daily GP1200 values were calculated with the estimated α and GPmax⁡ values; i.e. GPP was normalized to PAR = 1200 µmol m-2 s-1.

In this study, the system boundaries include the main components of the carbon balance of the field ecosystem studied. The carbon balance was calculated by adding up the 30 min NEE fluxes, the imported carbon in the form of organic fertilizers and the carbon removed as harvested biomass: 4Cbalance=CH+CF+∑i=1nNEEi, where CH is the amount of carbon in harvested biomass, CF is the amount of carbon in imported fertilization and n is the total number of time steps in the period for which the balance was calculated. Thus, the carbon balance indicates the net ecosystem carbon balance as defined by without the contribution of carbon monoxide, methane, volatile organic and particulate compounds, or leaching. This balance is commonly called the net biome production . Biomass was converted to carbon by multiplying the dry weight by 0.42 . The following sign convention was used: the carbon imported into the ecosystem corresponds to a negative flux, and the carbon removed from the system corresponds to a positive flux.

The CO2 balance between the field and the atmosphere, which is calculated based on the EC measurements, includes multiple potential error sources. Uncertainties are associated, for example, with the stochastic nature of turbulence and incomplete sampling of large eddies, the performance of instruments and the flux variation caused by the limited area of the target ecosystem . The most relevant random error sources, i.e. the statistical measurement error (Emeas) and the error caused by gap-filling (Egap) , were included in the uncertainty estimate: 5Emeas=∑i=1n(NEEmeas,i-NEEmod,i)2, where NEEmeas is the filtered 30 min flux, NEEmod is the corresponding modelled NEE (Eqs. –) and n is the number of measured data. 6Egap=∑i=1N(EGPP,i2+EReco,i2), where EGPP and EReco are the errors of modelled GPP and Reco, respectively. N is the number of gaps in the data.

The standard error propagation principle was used in estimating the total uncertainty (Etot) of the annual carbon balance: 7Etot=Emeas2+Egap2.

The ecosystem WUE was defined as the ratio of GPP to ET, i.e. H2O flux: 8WUE=GPPET, where daily means of GPP and ET were used. The ET data corresponding to a latent heat flux lower than 30 W m-2 were discarded . Furthermore, days with precipitation were eliminated in order to obtain a signal that is dominated by transpiration.

Soil carbon content was determined from 1 m deep core samples taken within the flux source area. The samples were taken in October 2018 using a hydraulic corer installed on a tractor. The diameter of the sample cylinder was 151 mm. Subsamples were taken along the 1 m core at 16 points, and soil organic carbon (SOC, kg m-2) content in each subsample was analysed using a VarioMax CN analyser (Elementar Analysensysteme GmbH, Germany).

The annual mean air temperature at the study site was 7.6 and 7.7 ∘C in the first and second measurement years, respectively. Both years were warm compared to the long-term (1981–2010) average of 5.4 ∘C measured at a nearby weather station . The annual precipitation sum was lower in the first year (473 mm) and higher in the second year (855 mm) than the long-time average (679 mm).

The thermal growing season, defined here as the period when the daily mean temperature permanently exceeded 5 ∘C, started on 14 April in 2018, i.e. before the EC measurements started. In 2019 and 2020, the thermal growing season began on 16 and 18 April, respectively. The thermal growing season ended on 17 November and 26 October in 2018 and 2019, respectively. Thus, the thermal growing season length was 218 d in 2018 and 194 d in 2019. Meteorological conditions during the main growing season between May and September varied substantially between the 2 years. The mean air temperature during these periods was 16.7 and 14.5 ∘C in 2018 and 2019, respectively. During the same period, the mean daily PAR was about 12 % higher in 2018 than in 2019 (460 vs. 410 µmol m-2 s-1), while the precipitation sum was 32 % lower (212 vs. 312 mm).

During winter 2018–2019, permanent snow cover was recorded from 17 December 2018 to 26 March 2019. In the following winter (2019–2020), there were only two short snow-cover periods: 5–8 February and 30–31 March 2020. The maximum snow depth in the first winter was 33 cm, whereas in the second winter it was 3 cm. The mean wintertime (November–March) air temperature was -0.2 ∘C in 2018–2019 and 2.2 ∘C in 2019–2020.

Soil moisture content at the depth of 10 cm varied between 0.16 and 0.55 m3 m-3 during the study period. On several occasions, the daily mean soil moisture dropped to about 0.2 m3 m-3. During the growing seasons, such low values indicate substantial drought, while in the winter, rapid data drops were likely related to soil freezing. The average soil moisture during the growing season in 2019 was higher than in 2018 (0.30 vs. 0.26 m3 m-3). As a result of the higher precipitation in 2019, soil moisture occasionally increased up to 0.4 m3 m-3, i.e. close to the saturated values observed in winter.

At the beginning of the measurements, the net CO2 fluxes were negative (Fig. ), and the air temperature was already well above 10 ∘C (Fig. ). Net uptake was observed until the first harvest around mid-June 2018. This harvest and the following management events during that growing season induced large short-term variations in the CO2 fluxes. Similarly, in the second study year, large impacts on CO2 fluxes were observed after the management events. During the growing season, the mean NEE was -0.13 and -0.21 mg CO2 m-2 s-1 in 2018 and 2019, respectively. During the wintertime, no significant CO2 uptake occurred, and the positive fluxes were small compared to the nocturnal fluxes in summer. The mean measured NEE between December 2018 and February 2019 was 0.03 mg CO2 m-2 s-1, and during the same period in 2019–2020 it was 0.04 mg CO2 m-2 s-1.

Seasonal patterns were also observed in the H2O fluxes (Fig. ). In the spring, the ecosystem ET started to increase, reaching the highest levels between June and August, after which it gradually decreased to wintertime values, i.e. close to zero. The mean growing season H2O flux was 34.7 mg H2O m-2 s-1 in 2018 and 35.5 mg H2O m-2 s-1 in 2019. The wintertime (December–February) mean H2O flux was 3.6 and 3.7 mg H2O m-2 in 2018–2019 and 2019–2020, respectively.

The experimental field was harvested and fertilized twice during each of the studied growing seasons (Table ). The effect of management was investigated by comparing the mean fluxes 5 d before and after the harvest dates (Table ). The harvest in June 2018 changed the mean CO2 flux from a net sink of -0.28 mg CO2 m-2 s-1 to a source of 0.03 mg CO2 m-2 s-1, i.e. increased the net efflux by 0.31 mg CO2 m-2 s-1. The first harvest of 2019 increased NEE by 0.47 mg CO2 m-2 s-1, but as the pre-harvest mean NEE was -0.50 mg CO2 m-2 s-1, the field remained as a net sink. As a result of the second harvest on 23 September 2018, the mean sink decreased from -0.10 to -0.02 mg CO2 m-2 s-1, while the harvest on 20 August 2019 caused the sink to change from -0.25 to -0.02 mg CO2 m-2 s-1. Thus, after all the harvests with a cutting height of 15 cm, the mean sink rate was diminished to -0.02 or -0.03 mg CO2 m-2 s-1.

In the first growing season, the first and second fertilization events with organic substances increased NEE by 0.27 and 0.08 mg CO2 m-2 s-1, respectively, i.e. diminished the CO2 sink (Fig. , Table ). During the 5 d after the harvest in May 2019, the field acted as a CO2 source. A similar trend was not observed in June 2019, as mineral fertilizer was used, and thus no organic substances were added to the soil. Each of the fertilization events were followed by rain within the next 5 d. However, the mean soil moisture at the depth of 10 cm either remained the same or decreased slightly (Fig. , Table ). Furthermore, the mean air temperature increased after the fertilizations in July 2018 and May 2019, potentially affecting CO2 fluxes. After the fertilization events with organic substances in July 2018, August 2018 and May 2019, the mean PAR was 7 %, 29 % and 12 % lower, respectively, than the 5 d mean before the fertilization, complicating the interpretation of fertilization impacts on the CO2 fluxes. The effect of management on H2O fluxes could not be disentangled from the present data (Fig. b).

The LAI derived from Sentinel-2 images (Fig. d) varied greatly between the years. The higher LAI in 2019 indicated that there was more photosynthesizing green biomass before the first and second harvests compared to 2018. The effect of larger leaf area was also observed in the differences in the photosynthetic capacity (GP1200) of the grassland between the study years (Fig. a). The years differed significantly (p<0.05) in terms of GP1200 at all levels of LAI (>1). Larger LAI values were observed throughout 2019, indicating that grass was growing better than in 2018. Furthermore, the grassland was photosynthesizing more efficiently with the same leaf area in 2019 than in the previous year (Fig. a).

The ecosystem WUE estimate showed different seasonal variation during the studied growing seasons (Fig. ). Generally, WUE was higher in 2019 than in 2018 throughout the growing season. WUE increased before the first harvest around mid-June in both years, indicating more efficient CO2 uptake in terms of water use than during the spring. The 5 d mean WUE before the first harvest was 2.8 and 3.0 g CO2 (kg H2O)-1 in 2018 and 2019, respectively. Due to the harvest, it dropped to 0.9 g CO2 (kg H2O)-1 in 2018 and to 2.6 g CO2 (kg H2O)-1 in 2019. During the latter growing season, WUE increased steadily towards 4 g CO2 (kg H2O)-1 until the second harvest in August, whereas in 2018 it remained predominantly below 2 g CO2 (kg H2O)-1 during the same period. At the end of August and early September, WUE was at the same level in both years.

The LAI derived from the Sentinel-2 data was compared to the daily WUE values (Fig. b) to further cast light on the relationship between vegetation status and WUE. While WUE was on average lower in 2018 than 2019, the difference at a given LAI was not significant (p>0.05). However, in both years the daily WUE increased in a similarly linear manner in relation to LAI.

The carbon balance of the studied grass field was -57 ± 10 g C m-2 yr-1 in the first year, and the balance of the second year was -86 ± 12 g C m-2 yr-1, i.e. the field acted as a net carbon sink in both years (Table ). The magnitude of all components of the carbon balance were smaller in the first year than in the second one, GPP by 29 %, Reco by 23 % and management by 96 %. The components in the mean annual CO2 fluxes between the field and the atmosphere also indicated major differences between the growing seasons (Table ). In 2019, the magnitude of the growing season NEE was 78 %, GPP 49 % and Reco 42 % higher than in 2018.

The average soil carbon storage in the 1 m layer was 16.59 ± 2.25 kg m-2 (average ± standard deviation), with the highest SOC found in the top 30 cm layer (Fig. ). To estimate the increase in soil carbon storage, it was assumed that the magnitude of the net carbon balance represented the amount of carbon accumulated in the soil. Furthermore, to evaluate whether the field had the potential to fulfil the “4 per 1000” initiative, the annual net carbon balance was compared to the average soil carbon content. Thus, the estimated increase in soil carbon storage was 0.3 % and 0.5 % in the first and second years, respectively. On average, the annual carbon input to the soil accounted for 0.4 % of the SOC.

There is an urgent need to find evidence-based climate-friendly practices in agriculture in the boreal region, where the growing season is short and varieties differ from those cultivated in the temperate region. The carbon fluxes we measured on the agricultural grassland at the Qvidja farm in southern Finland clearly indicated that this site was a sink of atmospheric carbon. The annual NEE was -62 g C m-2 yr-1 in the first study year (4 May 2018–3 May 2019) and -216 g C m-2 yr-1 in the second year (4 May 2019–3 May 2020). The GPP showed notable variation between the study years as the annual GPP was -1121 and -1583 g C m-2 yr-1 in the first and second years, respectively. reported a range of -2107 to -1410 g C m-2 yr-1 for the GPP of European managed grasslands. Our results fall below or in the lower end of this range. The annual Reco in Qvidja also varied between the study years (1053 and 1362 g C m-2 yr-1). The annual Reco in the European grasslands is reported to vary between 494 and 1623 g C m-2 yr-1 . Our observations are thus also within this range.

To answer our first research question, we concluded that the carbon balance was negative in both study years (-57 ± 10 and -86 ± 12 g C m-2 yr-1), and thus the field acted as a net carbon sink during the study period. In comparison, the Finnish agricultural fields measured so far were generally carbon sources when ecosystem–atmosphere CO2 fluxes, harvests and the carbon supplied to the system as fertilizers were considered . reported a slightly more negative annual NEE (2-year average NEE -259 g C m-2 yr-1) for a grassland site on mineral soil than we observed in Qvidja. However, by considering the total carbon balance of the system by taking into account the carbon fluxes related to biomass removal as grass yield, it was concluded that their site acted as a net carbon source. Mineral fertilizers were used during their study, and thereby no carbon was imported to the field to compensate for the biomass removal from the system as harvests. Similar management-related carbon flux patterns were observed by , who reported a more negative NEE (average -405 g C m-2 yr-1) for an agricultural grassland in Canada than the NEE in Qvidja; however, the 2-year mean annual carbon balance was positive when biomass removal was taken into account, i.e. the Canadian field was a net source of carbon. It is noteworthy that the yield in Qvidja was substantially smaller than at the other two study sites , at which the total balance became positive when the management activities, i.e. harvests and fertilization, were taken into account. The total carbon balance of the field depends greatly both on the amount of organic matter imported to the system as fertilizers and on the harvest yields, which are affected, for instance, by the applied cutting height.

Analysis of the weather variables in Qvidja indicated that temperature and moisture conditions were associated with the differences in CO2 flux dynamics and carbon balance between the study years. The growing season was warmer and drier in 2018 than 2019, with 13 % lower mean soil moisture, 32 % lower precipitation, 2.2 ∘C higher mean air temperature and 12 % higher mean radiation during the growing season, and substantially smaller fluxes were observed in the first year. This is in accordance with , who observed a positive correlation between the uptake of atmospheric CO2 (GPP) and both soil moisture and air temperature on another Finnish agricultural grassland. According to their conclusions, moderate temperature with high soil moisture enhanced CO2 uptake. Furthermore, and concluded that rather wet summer conditions favoured photosynthetic activity in grasslands. These findings would support the conclusion that low soil moisture and high temperatures were the main factors limiting CO2 uptake at our study site in the summer 2018. However, this question remains partly open, as weather conditions, grass age and grass leaf area all showed different dynamics between the study years. In Finland, it is typical to grow grasslands for 3–4 years before grass renewal. In Qvidja, the grass was not renewed between the study years, which may have led to the larger fluxes observed in the second year when the grass root system, for instance, was likely to be more developed, enhancing water and nutrient availability and thus reducing the effect of drought stress. Furthermore, the leaf area was larger, and other capabilities, such as microbial symbioses e.g., of the more developed grass may have increased carbon uptake. The lower leaf area during the first year was most probably also due to the dry summer, as shortage of water is a growth-limiting factor. Besides the leaf area, the photosynthetic potential per leaf area was lower in the first year, indicating either drought stress or shortage of nutrients, as temperature, a widely limiting factor in northern latitudes, was high enough during both summers not to restrict photosynthesis. In any case, a more specific analysis of the driving and inhibiting environmental factors will require a longer measurement period.

Our second research question concerned the drought-related restrictions of photosynthesis. It has been widely recognized that in dry conditions plants are able to reduce transpiration by stomatal regulation . However, grasses seem to limit stomatal functions only in severe, prolonged drought conditions , and thus occasional or seasonal drought events may not be observed in the ecosystem WUE of grasslands. In our study, WUE values were predominantly lower in 2018 than in 2019. This was most probably explained by the differences in LAI, as the relationship between WUE and LAI was similar during both growing seasons (Fig. b). Furthermore, the drier conditions with high temperatures in the summer 2018 may have resulted in a decoupling of assimilation and transpiration and in temperature-induced downregulation of GPP , as ET was similar in both years (Table ). Therefore, the clearly lower leaf-area-based photosynthetic capacity (GP1200) in 2018 compared to 2019 probably indicates drought-related stress on photosynthetic processes despite the similar leaf-area-based WUE (Fig. ). It is noteworthy that the WUE analysis was performed by means of the total ecosystem ET rather than plant transpiration, which would have enabled a more direct determination of the actual plant WUE and thus a simpler interpretation of plant processes and their relation to LAI. Nevertheless, days with even slight precipitation were eliminated from the analysis, and therefore we can assume that during the growing season most of the water flux arises from transpiration. In general, WUE at our study site varied mainly between 0 and 4 g C (kg H2O)-1. This is consistent with the WUEs observed on northern grasslands (0–7 g C (kg H2O)-1) .

The different management practices, such as fertilization and the choice of grass cutting height, were slightly different in the first and second years, which probably had an impact on the carbon balances. In June 2018, a conventional cutting height of 6 cm was used, whereas in the other harvests the grass was cut at 15 cm. The higher cutting height may have enhanced the regrowth of grass, especially in the more favourable weather conditions in 2019, and with a larger leaf area higher CO2 uptake was observed right after the harvest. Only after the 6 cm harvest did the field turn to a net source of CO2. With a low cutting height, it was more likely that the grass was cut below the growing point, particularly in dry conditions, which affects the stand longevity and stress tolerance . As the weather was warm and dry during the harvest events in June in both years, a higher cutting height may have served as a vital management improvement.

The field was mainly fertilized with organic substances, and thus carbon was imported to the system, affecting the net carbon balance. After each of the fertilization events with organic material, the respiration of the field increased, whereas mineral fertilization was not observed to have an immediate effect on CO2 fluxes. Increased respiration was likely to occur due to microbial activity of the organic fertilizers. observed on a Danish agricultural grassland that, although the application of manure increased respiration, the plant uptake of CO2 was notably higher than at the other sites studied. also concluded, based on their 43-year study, that manure fertilization substantially increased soil carbon sequestration of a grassland ecosystem in Northern Ireland. Although the type of the organic fertilizer possibly plays a crucial role, the application of carbon to the system has a direct effect on the carbon balance, but there is also an indirect effect on its components Reco and GPP via soil and plant functions.

Concerning our final research question on the relation of the carbon balance to the international “4 per 1000” carbon sequestration initiative , our results show that the Qvidja field acted as an annual net carbon sink and had the potential to fulfil the goal of this initiative and to contribute to the short-term climate change mitigation. By considering the carbon balance by accounting for the ecosystem–atmosphere CO2 fluxes and the carbon fluxes caused by management activities and comparing that to the measured soil carbon content, the carbon storage of the field increased on average by 0.4 % annually over the studied period. To draw a more reliable conclusion about the carbon sequestration, leaching and other carbon-containing compounds must also be considered in further studies about the carbon balance. Furthermore, the number of soil carbon samples should be increased for a more accurate evaluation of the soil carbon storage of the field, even though the variation among the present samples was small. However, the estimated annual carbon balance of our second study year (-86 g C m-2 yr-1) with improved management practices was within the range of annual carbon sequestration potential (80–120 g C m-2 yr-1) that is evaluated to be attainable with improved management practices . Thus, this study demonstrates the potential for a positive impact of northern agricultural grasslands in terms of climate change mitigation.

Uncertainties in the results are mainly related to the gaps in the measurement data, which required gap-filling of missing measurements with modelled data. The length of a gap increases the related uncertainty, but in our data there were only three longer gaps (4, 8 and 9 d), which all occurred during the first winter, when temperatures were low and only minor fluxes could have been observed. All the other gaps were shorter than 3 d. However, each gap contributed to the uncertainty and were included in the carbon balance calculations. Further uncertainties, which were not included in the error estimates, were involved in the yield measurements and fertilization input estimates, as well as in the fairly scarce sample size of the soil carbon content measurements.

Carbon balance was calculated based on the ecosystem–atmosphere CO2 fluxes and the inputs and outputs of harvest and fertilization. Thus, no other gaseous carbon compounds, such as methane, were considered. reported that the annual methane balances of a Finnish clay soil for 2 years were -0.009 and 0.034 g CH4 m-2 yr-1. Based on this estimate, the possible carbon emission as methane accounts for less than 1 % of our annual carbon balance.

Leaching of dissolved carbon and emissions of volatile organic compounds may have had an effect on the annual carbon balance. Leaching of carbon from the agricultural soils is mainly driven by meteorological and hydrological conditions , but it is also affected by soil properties . Large variations in soil moisture and temperature and precipitation may increase the solubility of SOM. Generally, however, clay soils retain carbon better than other soil types. Furthermore, ploughing increases leaching as mineralization of SOM is enhanced. Depending on precipitation and hydrological and chemical properties of the soil, carbon leaching on grasslands may equal approximately 25 % of the annual carbon balance calculated based on NEE, harvest and fertilization . At our study site, the effect of leaching on the annual carbon balance could be assumed to be fairly small in both summers due to low soil moisture and low precipitation. In winter, the leaching may have caused a temporary contribution to the carbon balance during wet periods and thus reduced the increase in soil carbon storage. For a more accurate carbon balance estimate of this site, however, the contribution of leaching and all carbon-containing gases (e.g. CH4) should be measured and the number of soil carbon storage measurements increased.