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Draining peatlands for forestry and agriculture has been a common practice in Nordic countries in the last century. In drained peatland forests, trees act as carbon sink, while well-aerated peat soil is a source of carbon. Traditionally in even aged forestry all the trees are removed in clear-cut harvesting, whereas the continous cover forestry, with partial removal of a stand in selection cuttings, have been suggested to serve as climate wise option for peatlands. A process-based model ‘Landscape De-Nitrification De-Composition’ (LDNDC) was used to simulate fluxes of matter and energy of a drained nutrient-rich peatland forest ecosystem in southern Finland. LDNDC utilizes several sub-models for physiology, biogeochemistry, hydrology and microclimate and it simulates ecosystem water, energy and carbon balances including methane balance along with vegetation structure development. Multiple species can be simulated simultaneously as a mixed forest cohort, and contributions of the ground vegetation can be included. Different management methods of the forestry industry, e.g clear cutting or selection cutting have been simulated successfully. Local meterological data from 2010-2018 was used to drive the model and this data was cycled through several times to start the simulation run from 1969. The amount of carbon storage in the soil was set according to the measurements at nutrient-rich peatlands. Three different simulation runs were made for a clear-cut or a selection cutting taking place in 2016 and a reference forest with no cutting. Pine was simulated as a dominant tree species prior to the management actions along with spruce and birch as a secondary canopy and alpine meadows as ground vegetation. Eddy covariance and chamber measurements from both management and reference sites were used to evaluate model performance. The model captured the net ecosystem exchange, gross primary production, terrestrial ecosystem respiration and methane fluxes well. The model also captured the changes in soil moisture and water-table level caused by the applied forest management methods. Leaf area index (LAI) of the combined vegetation cohort represented the measured LAI quite well along with the growth of the individual species. Successful implementation of the model resulted in extension of simulations until 2100 using different climate drivers to investigate effects of future management scenarios on various ecosystem balances. These model results can be utilized to provide recommendations for peatland forest management, which can ensure reduction in forestry related emissions and improve the possibilities for the peatland forest to act as a sink of carbon.

Studies on physiological response of suppressed trees to selection harvest are scarce. Understanding how trees respond to changes in environmental factors following harvest is needed for continuous cover forestry that aims to optimize both environmental impacts and economical gain. The physiological response of the trees can be understood by measuring stable carbon isotope composition (δ13C) which records the changes in photosynthesis and water use of the tree. The processes that determine the response can be further elaborated by comparing the measured isotopic signal to process-level model simulations.We studied the response of Norway spruce (Picea abies) trees to selection harvesting on a fertile drained peatland forest located in southern Finland. The studied area consisted of a control plot which was left intact and of harvested plot which was thinned in March 2016. We measured intra-annual δ13C from tree-rings covering the period from 2010 to 2020 at the Stable Isotope Laboratory of Luke (SILL) (Lehtonen et al., accepted). The measured δ13C was compared to modelled 13C discrimination (Δ13C) simulated with a vertically resolved ecosystem model describing tree photosynthesis (Launiainen et al., 2015).The δ13C measurements showed that after the harvest Δ13C decreased already on the following growing season. The overall decrease was ca. 3.3 ‰ on average between pre- and post-harvest periods. The decrease was caused by both changes in CO2 assimilation of the spruce trees and differences in meteorological conditions between pre- and post-harvest years. We simulated Δ13C with three different models with increasing number of fractionation processes considered. All three models predicted that as a response to harvest the Δ13C would decrease, however, none of the models could replicate the observed 3.3‰ drop in Δ13C. The most complex Δ13C model that included 13C fractionation in mitochondrial and photorespiration as well as transport of CO2 from stomata to mesophyll was the closest to the measurements.The vertically resolved model allowed us to estimate that the changes in photosynthetically active radiation, relative humidity and needle temperature following the harvest contributed the most to the observed decrease in Δ13C. Further, model sensitivity analysis showed that the modelled Δ13C is the most sensitive to g1 parameter and mesophyll conductance. The g1 parameter is related to calculation of stomatal conductance (Launiainen et al., 2015; Medlyn et al., 2011). By tuning the g1 parameter and mesophyll conductance we were able to bring the modelled Δ13C closer to the observations.ReferencesLauniainen et al., Ecological Modelling, 312, 385-405, 2015.Lehtonen et al., Forest Ecology and Management, accepted.Medlyn et. al., Global Change Biology 17, 2134–2144, 2

Wide-spread harvesting of forests growing on drained peatlands is foreseen to take place in Finland in the near future. A hot question is if continuous cover forestry utilizing partial cuttings could be used to mitigate carbon dioxide (CO2) emissions and the consequent climatic impact compared to traditional clear-cutting and even-aged forest management. To assess the impact of clear-cutting vs. partial cutting, we first measured CO2 exchange with the eddy covariance (EC) method for six years in a mature, nutrient-rich peatland forest in southern Finland. Part of the forest was then partially cut (74% of the stem volume), and part of it was clear-cut, and CO2 exchange of both areas was measured for another six years. Tree growth was recorded before and after the cuttings to separate the contributions of tree stand and forest floor to CO2 exchange. Before the cuttings, the site had an annual CO2 exchange close to zero, but both cutting methods turned it into a CO2 source. However, the first-year emissions from the partial cutting area (800 g CO2 in-2 yr iota) were markedly lower than the emissions after clear -cutting (3100 g CO2 M-2 yr iota) The partial cutting area remained a CO2 source during the first three years but turned into a CO2 sink after that, while the clear-cut area acted as a large, although diminishing, CO2 source for the whole measurement period. The total six-year CO2 balances before and after partial cutting did not differ significantly, while the emissions after clear-cutting were on average 2240 g CO2 m2 yr iota larger than before it. Combining the EC data with the tree growth measurements showed that the forest floor was losing C both before and after harvestings. In conclusion, partial cutting resulted in clearly smaller CO2 emissions than clear-cutting at least in the short term.

While the eddy covariance (EC) technique is a well-established method for measuring water fluxes (i.e., evaporation or ’evapotranspiration’, ET), the measurement is susceptible to many uncertainties. One such issue is the potential underestimation of ET when relative humidity (RH) is high (>70%), due to low-pass filtering with some EC systems. Yet, this underestimation for different types of EC systems (e.g. open-path or closed-path sensors) has not been characterized for synthesis datasets such as the widely used FLUXNET2015 dataset. Here, we assess the RH-associated underestimation of latent heat fluxes (LE, or ET) from different EC systems for 163 sites in the FLUXNET2015 dataset. We found that the LE underestimation is most apparent during hours when RH is higher than 70%, predominantly observed at sites using closed-path EC systems, but the extent of the LE underesti- mation is highly site-specific. We then propose a machine learning based method to correct for this underestimation, and compare it to two energy balance closure based LE correction approaches (Bowen ratio correction, BRC, and attributing all errors to LE). Our correction increases LE by 189% for closed-path sites at high RH (>90%), while BRC increases LE by around 30% for all RH conditions. Additionally, we assess the influence of these corrections on ET-based transpiration (T) estimates using two different ET partitioning methods. Results show opposite responses (increasing vs. slightly decreasing T-to-ET ratios, T/ET) between the two methods when comparing T based on corrected and uncorrected LE. Overall, our results demonstrate the existence of a high RH bias in water fluxes in the FLUXNET2015 dataset and suggest that this bias is a pronounced source of uncertainty in ET measurements to be considered when estimating ecosystem T/ET and WUE.

Context Spatial patterns of CH4 fluxes can be modeled with remotely sensed data representing land cover, soil moisture and topography. Spatially extensive CH4 flux measurements conducted with portable analyzers have not been previously upscaled with remote sensing. Objectives How well can the CH4 fluxes be predicted with plot-based vegetation measures and remote sensing? How does the predictive skill of the model change when using different combinations of predictor variables? Methods We measured CH4 fluxes in 279 plots in a 12.4 km2 peatland-forest-mosaic landscape in Pallas area, northern Finland in July 2019. We compared 20 different CH4 flux maps produced with vegetation field data and remote sensing data including Sentinel-1, Sentinel-2 and digital terrain model (DTM). Results The landscape acted as a net source of CH4 (253–502 µg m−2 h−1) and the proportion of source areas varied considerably between maps (12–50%). The amount of explained variance was high in CH4 regressions (59–76%, nRMSE 8–10%). Regressions including remote sensing predictors had better performance than regressions with plot-based vegetation predictors. The most important remote sensing predictors included VH-polarized Sentinel-1 features together with topographic wetness index and other DTM features. Spatial patterns were most accurately predicted when the landscape was divided into sinks and sources with remote sensing-based classifications, and the fluxes were modeled for sinks and sources separately. Conclusions CH4 fluxes can be predicted accurately with multi-source remote sensing in northern boreal peatland landscapes. High spatial resolution remote sensing-based maps constrain uncertainties related to CH4 fluxes and their spatial patterns.

Boreal upland forests are generally considered methane (CH4) sinks due to high methane consumption rates. However, some studies have shown a boreal upland forest soil turning from a CH4 sink to a source after long-term abundant precipitation but the factors affecting this change remain largely unknown. In a simulated rainfall experiment, we investigated soil moisture effects on CH4 flux. We also evaluated the influence of simultaneous soil temperature increase, organic litter addition and root exclusion on CH4 flux.The study was conducted in a northern boreal upland forest soil (Kenttärova forest in Kittilä, Finland) in summer 2018. Split-plot design was used in the experiment with soil moisture being the main treatment variable and soil warming (T), organic litter addition (A) and organic litter and root exclusion (E) subtreatment variables. The design included two main plots: irrigation (I) and control (C), within which each subtreatment was replicated three times. In addition to the T, A and E manipulations, plots without additional manipulations (O) were included for the assessment of the effect of only soil moisture increase (n=4). CH4 flux was measured at least once a week using chambers. Soil moisture and temperature were also continuously measured.Contrary to our expectation, the soil remained a CH4 sink after experimental rainfall increase but irrigation and control sites differed significantly in their CH4 fluxes, indicating a strong decreasing effect of soil moisture on soil CH4 sink. All treatments had lowest CH4 uptake rates in August, possibly as a result of high soil moisture. The IA treatment had the lowest uptake rates possibly due to a reduction in gas diffusion. The IE treatment had contrasting results to all other treatments and showed a positive relationship between uptake rate and soil moisture, but the causes remained unsolved and the results were highly uncertain. T treatment had no effect on uptake likely due to a failure to create soil temperature differences and thus the interactions were not reliably analyzed. Our results suggest that the CH4 flux response to soil moisture may have been more related to changes in CH4 consumption than production. Based on these results, future irrigation experiments should especially assess the combined effect of organic litter addition and soil moisture on soil CH4 sink over multiple years. Improvements in the manipulation methods, experimental design and sensors will also be needed.

Boreal upland forests are generally considered methane (CH4) sinks due to the predominance of CH4 oxidizing bacteria over the methanogenic archaea. However, boreal upland forests can temporarily act as CH4 sources during wet seasons or years. From a landscape perspective and in annual terms, this source can be significant as weather conditions may cause flooding, which can last a considerable proportion of the active season and because often, the forest coverage within a typical boreal catchment is much higher than that of wetlands. Processes and conditions which change mineral soils from acting as a weak sink to a strong source are not well understood. We measured soil CH4 fluxes from 20 different points from regularly irrigated and control plots during two growing seasons. We also estimated potential CH4 production and oxidation rates in different soil layers and performed a laboratory experiment, where soil microcosms were subjected to different moisture levels and glucose addition simulating the fresh labile carbon (C) source from root exudates. The aim was to find the key controlling factors and conditions for boreal upland soil CH4 production. Probably due to long dry periods in both summers, we did not find occasions of CH4 production following the excess irrigation, with one exception in July 2019 with emission of 18 200 µg CH4 m−2 h−1. Otherwise, the soil was always a CH4 sink (median CH4 uptake rate of 260–290 and 150–170 µg CH4 m−2 h−1, in control and irrigated plots, respectively). The median soil CH4 uptake rates at the irrigated plot were 88 % and 50 % lower than at the control plot in 2018 and 2019, respectively. Potential CH4 production rates were highest in the organic layer (0.2–0.6 nmol CH4 g−1 d−1), but some production was also observed in the leaching layer, whereas in other soil layers, the rates were negligible. Potential CH4 oxidation rates varied mainly within 10–40 nmol CH4 g−1 d−1, except in deep soil and the organic layer in 2019, where potential oxidation rates were almost zero. The laboratory experiment revealed that high soil moisture alone does not turn upland forest soil into a CH4 source. However, a simple C source, e.g., substrates coming from root exudates with high moisture, switched the soil into a CH4 source. Our unique study provides new insights into the processes and controlling factors on CH4 production and oxidation, and the resulting net efflux that should be incorporated in process models describing global CH4 cycling.

A soil moisture estimation method was developed for Sentinel-1 synthetic aperture radar (SAR) ground range detected high resolution (GRDH) data to analyze moisture conditions in a gently undulating and heterogeneous subarctic area containing forests, wetlands, and open orographic tundra. In order to preserve the original 10-m pixel spacing, PIMSAR (pixel-based multitemporal nonlocal averaging) nonlocal mean filtering was applied. It was guided by multitemporal statistics of SAR images in the area. The gradient boosted trees (GBT) machine learning method was used for the soil moisture algorithm development. Discrete and continuous in situ soil moisture values were used for training and validation of the algorithm. For surface soil moisture, the root mean square error (RMSE) of the method was 6.5% and 8.8% for morning and evening images, respectively. The corresponding maximum errors were 34.1% and 33.8%. The pixelwise sensitivity to the training set and method choice was estimated as the variance of the soil moisture values derived using the algorithms for the three best methods with respect to the criteria: the smallest maximum error, the smallest RMSE value, and the highest coefficient of determination (R-2) value. It was, on average, 6.3% with a standard deviation of 5.7%. Our approach successfully produced instantaneous high-resolution soil moisture estimates on daily basis for the subarctic landscape and can further be applied to various hydrological, biogeochemical, and management purposes.

Continuous cover forestry (CCF) has been promoted as an environmentally sustainable option for drained peatlands. The CCF management has been challenged due to potentially lower tree growth compared to tradi-tional even-aged management, especially with suppressed trees that are released during a selection harvesting under CCF management. Our objective was to quantify the time lag of stem diameter growth response of suppressed Norway spruce trees (Picea abies Karst.) after a selection harvesting compared to that of dominant trees. We also tested if the carbon assimilation of the trees increased immediately after selection harvesting. We used radial increment cores from suppressed Norway spruce trees to estimate the impact of selection harvesting on the diameter growth and intrinsic water use efficiency (iWUE). We measured carbon isotope composition (delta 13C) of wood, to quantify how the reduced competition between trees altered iWUE and its components, the photosynthetic rate (A) and sto-matal conductance (g). The study was conducted in the Lettosuo experimental site on fertile forestry drained peatland area in southern Finland. Approximately 70 % of the initial stand area (18.5 ha) was harvested according to CCF principles by applying selection harvesting, and the rest of the area was divided to intact control area and to clear-cut area. In the study site, by selection harvest, trees were removed from multiple age classes, but especially mature trees individually or in a small groups were taken away to maintain uneven-aged structure of the forest. All the target trees grew in the similar competitive position before selection harvesting. Our results show that there was a delay with the diameter growth of the suppressed trees to selection har-vesting, whereas the most significant growth-enhancing effect occurred three-four years after selection har-vesting. In contrast to the delay in the increment, the photosynthetic rate relative to stomatal conductance increased immediately after selection harvesting, as shown by the instant 2.5 parts per thousand increase in delta 13C to a post-harvest level. Our results show that carbon uptake increased immediately for suppressed Norway spruce trees after selection harvesting, but the harvest did not induce a clear increase in stem diameter growth during the first years after the harvest.

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.

Drained peatlands are a challenge to the climate change mitigation, due to acting as sources of carbon and greenhouse gases to the atmosphere. However, different management practices could be used to reduce these emissions. In this thesis, the objective was to quantify the changes in water table level (WTL), evapotranspiration (ET) and greenhouse gas (GHG) fluxes for the first few years following clearcutting and partial harvesting a nutrient-rich peatland forest. The experimental forest was divided to partial harvest, clear-cut and control subsites, where WTL was monitored and direct flux measurements were made with the eddy covariance (EC), and manual and automatic soil chamber methods. Before clearcutting, the subsite was a small CO2 and CH4 sink, but N2O emissions were small. After clearcutting, WTL rose by 24 cm due to a 45% decrease in ET. The loss of photosynthesising biomass and addition of respiring logging residues turned the clear-cut subsite from CO2 sink into a large CO2 source for the next few years. Forest floor N2O fluxes increased significantly, possibly due to residues releasing reactive nitrogen, hence promoting N2O production. Also, soil compression and WTL rise might have enhanced N2O production through increased denitrification. The soil turned from CH4 sink into a small source as a result of thinning of oxic peat layer, which decreased CH4 oxidation. The partially harvested subsite was a small CO2 source before the partial harvest, meaning more carbon was lost through peat decomposition than was taken up by growing trees. Forest floor was a small CH4 sink and N2O source. After partial harvest, WTL rose by 12 cm and ET decreased by 17% compared to the control site. Also, CO2 emissions increased. However, compared to the clear-cut site, CO2 emissions were significantly smaller at the partial harvest site. No considerable changes in CH4 and N2O fluxes were observed after partial harvest. The difference in CO2 emissions between the harvest treatments can be explained with remaining tree stand, which kept ET higher, WTL lower and acted as CO2 sink. Also, the amount of decomposing logging residues was smaller after partial harvesting than after clearcutting. Kuivatut turvemaat ovat haaste ilmastonmuutoksen kannalta, koska ne toimivat hiilen ja kasvihuonekaasujen lähteinä, mutta erilaisilla käsittelytavoilla voidaan mahdollisesti hillitä näitä päästöjä. Tässä väitöskirjassa tavoitteena oli määrittää muutokset runsasravinteisen suometsän pohjaveden korkeudessa (WTL), haihdunnassa (ET) sekä kasvihuonekaasuvoissa (KHK-voissa) ensimmäisinä vuosina avohakkuun sekä osittaishakkuun jälkeen. Tutkimusmetsä jaettiin kolmeen koealaan: osittaishakkuu, avohakkuu ja kontrolli. Koealoilla mitattiin WTL:ää, ET:tä ja KHK-voita pyörrekovarianssi, automaatti- ja manuaalikammiomenetelmillä. Ennen avohakkuuta koeala oli pieni hiilidioksidin (CO2) ja metaanin (CH4) nielu ja pieni typpioksiduulin (N2O) lähde. Avohakkuun jälkeen ET laski 45%, joka johti 24 cm vedenpinnan nousuun. Yhteyttävän biomassan häviäminen ja hajoavien hakkuutähteiden lisääminen muutti avohakatun alan suureksi CO2-lähteeksi. Metsänpohjan N2O-vuot kasvoivat merkitsevästi todennäköisesti hakkutähteiden vapauttaman reaktiivisen typen vuoksi. Samaan aikaan maan tiivistyminen ja WTL:n nousu tehostivat denitrifikaatiota ja siten N2O:n tuottoa. Maaperä muuttui CH4-nielusta lähteeksi hapellisen turvekerroksen ohennuttua, joka pienensi CH4:n hapettumista. Osittaishakattava ala oli pieni CO2-lähde ennen hakkuuta, eli turpeen hajoamisesta muodostuvat CO2-päästöt olivat suuremmat kuin mitä puusto sitoi. Metsänpohja oli pieni CH4:n nielu ja N2O:n lähde. Osittaishakkuun jälkeen ET pieneni 17% ja WTL nousi 12 cm verrattuna kontrollialaan. CO2-päästöt kasvoivat verrattuna hakkuuta edeltävään tilaan, mutta merkittävästi vähemmän kuin avohakkuun jälkeen. CH4- ja N2O-voissa ei havaittu merkitsevästi muutoksia. Erot avohakkuun ja osittaishakkuun välillä selittyvät jäljelle jääneellä puustolla, joka piti haihdunnan korkeammalla, WTL:n matalammalla sekä sitoi CO2:a. Myös hakkuutähteiden määrä oli merkittävästi pienempi osittaishakkuun jäljiltä.

Peatlands and forests cover large areas of the boreal biome and are critical for global climate regulation. They also regulate regional climate through heat and water vapour exchange with the atmosphere. Understanding how land-atmosphere interactions in peatlands differ from forests may therefore be crucial for modelling boreal climate system dynamics and for assessing climate benefits of peatland conservation and restoration. To assess the biophysical impacts of peatlands and forests on peak growing season air temperature and humidity, we analysed surface energy fluxes and albedo from 35 peatlands and 37 evergreen needleleaf forests-the dominant boreal forest type-and simulated air temperature and vapour pressure deficit (VPD) over hypothetical homogeneous peatland and forest landscapes. We ran an evapotranspiration model using land surface parameters derived from energy flux observations and coupled an analytical solution for the surface energy balance to an atmospheric boundary layer (ABL) model. We found that peatlands, compared to forests, are characterized by higher growing season albedo, lower aerodynamic conductance, and higher surface conductance for an equivalent VPD. This combination of peatland surface properties results in a similar to 20% decrease in afternoon ABL height, a cooling (from 1.7 to 2.5 degrees C) in afternoon air temperatures, and a decrease in afternoon VPD (from 0.4 to 0.7 kPa) for peatland landscapes compared to forest landscapes. These biophysical climate impacts of peatlands are most pronounced at lower latitudes (similar to 45 degrees N) and decrease toward the northern limit of the boreal biome (similar to 70 degrees N). Thus, boreal peatlands have the potential to mitigate the effect of regional climate warming during the growing season. The biophysical climate mitigation potential of peatlands needs to be accounted for when projecting the future climate of the boreal biome, when assessing the climate benefits of conserving pristine boreal peatlands, and when restoring peatlands that have experienced peatland drainage and mining.

Agriculture is globally a significant source of carbon emissions to the atmosphere. Main causes for these high emissions are conventional intensive management practices which include such as frequent ploughing, monocropping and high use of agrochemicals. These practices contribute to the loss of biodiversity and soil organic matter, as well as to the CO2 emissions from land use. Recently, it has been recognised that agriculture functioning on the basis of regenerative practices is one of the most potential tools to mitigate climate change.It is well known that topsoil layer and especially humus-rich soils can store more carbon than atmosphere and vegetation together. Therefore, increasing the amount of soil organic matter in the agroecosystems, by applying enhanced management practices such as reduced tillage, high biodiversity and cover cropping, agricultural soils would not only help to mitigate climate change but also to restore soil quality and fertility. To understand the carbon dynamics on different agricultural sites, factors affecting and comprising the carbon balance, and to verify soil carbon and ecosystem models, continuous long-term monitoring of the GHG fluxes is essential at such managed ecosystems. Here we present results from a new eddy covariance (EC) flux study site located in southern Finland.Continuous CO2 flux measurements using the EC method have been conducted at Qvidja farm on mineral (clay) soil forage grassland in Parainen, southern Finland (60.29550°N, 22.39281°E) since the spring 2018. Based on the flux and biomass data, the annual carbon balance was estimated to be negative, i.e. the site acted as an overall sink of carbon even in the dry and hot year 2018. However, the seasonal CO2 fluxes were greatly dependent on weather conditions and management procedures. Results from 2019 show that the growing season accompanied with more mature and dense grass, a bit higher precipitation and lower temperatures, as well as higher cutting height was more favorable for carbon uptake in Qvidja as compared to year 2018.

Mitigation of climate change requires – besides reductions in greenhouse gas emissions – actions to increase carbon sinks and storages in terrestrial ecosystems. Agricultural lands have a high potential for increased carbon sequestration through climate-smart land management and agricultural practices. However, in order to make climate-smart farming an accredited solution for climate policy, carbon markets and product footprints, reliable verification of carbon sequestration is needed. Direct measurement of the changes in soil carbon stock is slow, laborious and expensive and has significant uncertainties due to large background stocks and high spatial variability. An alternative is to infer the soil carbon stock change from measurements of the gaseous carbon fluxes between ecosystems and the atmosphere using the micrometeorological eddy covariance (EC) method.Eddy covariance measures net ecosystem exchange (NEE), which is a small difference between two large components: carbon uptake by photosynthesis and losses due to plant and soil respiration. Therefore, small changes in either of them results in a large change in NEE. This sensitivity is also reflected in uncertainty estimates, which are critical for defining confidence intervals for annual carbon budget estimates and for making statistically valid comparisons of different management practices. In addition, there are inevitable gaps in the data due to instrument failure, power shortages and non-ideal flow conditions. Therefore, in order to calculate daily and annual sums, the collected data must be temporally upscaled or gap-filled, which constitutes a major additional source of uncertainty. This study compares two different gap-filling methods for CO₂ fluxes: (1) an artificial neural network and (2) non-linear regression, which uses temperature and radiation as drivers. Uncertainties associated with both methods are estimated and discussed. The analysis is based on EC flux measurements conducted at two agricultural grassland sites in Finland.

Drainage and other management activities in peatlands make especially the fertile sites a source of greenhouse gases into the atmosphere. In addition to typically losing carbon dioxide (CO2) from the old peat, they act as sources of nitrous oxide (N2O) into the atmosphere. In contrary to CO2, N2O fluxes do not necessarily show a distinct seasonal cycle with high emissions in summer and low in winter. Instead, the most intense peaks in N2O fluxes have been earlier attributed to freezing-thawing cycles of peat soil. Emissions of N2O have been reported to vary greatly both in time and space. Due to instrument limitations, the fluxes have been typically measured using manual chamber technique which provides only a snapshot of the potentially highly dynamic fluxes.In this presentation we show multi-year results of N2O fluxes captured by automatic chambers and compare those to temporally sparse manual chamber measurements. Our study site was a nutrient-rich drained peatland ‘Lettosuo’ located in Tammela in southern Finland. The peatland, originally an herb-rich tall sedge pine fen was drained for forestry in 1969. After that, the tree stand was a mixture of Scots pine, Norway spruce and Downy birch. N2O fluxes were measured hourly with six automatic chambers. We will address the temporal and spatial variability in the fluxes and the plausible reasons behind them, including the drought of summer 2018, and give a summary of the exploitability of different methods. Suggestions for an improved chamber configuration and for the optimal sampling frequency for manual chambers will be given based on the results.

Biogeochemical cycling of elements largely occurs in dissolved state, but many elements may also be bound to natural nanoparticles (NNP, 1-100 nm) and fine colloids (100-450 nm). We examined the hypothesis that the size and composition of stream water NNP and colloids vary systematically across Europe. To test this hypothesis, 96 stream water samples were simultaneously collected in 26 forested headwater catchments along two transects across Europe. Three size fractions (~1-20 nm, >20-60 nm, and >60 nm) of NNP and fine colloids were identified with Field Flow Fractionation coupled to inductively coupled plasma mass spectrometry and an organic carbon detector. The results showed that NNP and fine colloids constituted between 2 ± 5% (Si) and 53 ± 21% (Fe; mean ± SD) of total element concentrations, indicating a substantial contribution of particles to element transport in these European streams, especially for P and Fe. The particulate contents of Fe, Al, and organic C were correlated to their total element concentrations, but those of particulate Si, Mn, P, and Ca were not. The fine colloidal fractions >60 nm were dominated by clay minerals across all sites. The resulting element patterns of NNP

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.

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.

We quantified the response of peatland water table level (WTL) and energy fluxes to harvesting of a drained peatland forest. Two alternative harvests (clear-cut and partial harvest) were carried out in a mixed-species ditch-drained peatland forest in southern Finland, where water and energy balance components were monitored for six pre-treatment and three post-treatment growing seasons. To explore the responses caused by harvestings, we applied a mechanistic multi-layer soil-plant-atmosphere transfer model. At the clear-cut site, the mean growing season WTL rose by 0.18 +/- 0.02 m (error estimate based on measurement uncertainty), while net radiation, and sensible and latent heat fluxes decreased after harvest. On the contrary, we observed only minor changes in energy fluxes and mean WTL (0.05 +/- 0.03 m increase) at the partial harvest site, although as much as 70% of the stand basal area was removed and leaf-area index was reduced to half. The small changes were mainly explained by increased water use of spruce undergrowth and field layer vegetation, as well as increased forest floor evaporation. The rapid establishment of field layer vegetation had a significant role in energy balance recovery at the clear-cut site. At partial harvest, chlorophyll fluorescence measurements and model-data comparison suggested the shade-adapted spruce undergrowth was suffering from light stress during the first post-harvest growing season. We conclude that in addition to stand basal area, species composition and stand structure need to be considered when controlling WTL in peatland forests with partial harvesting. Our results have important implications on the operational use of continuous cover forestry on drained peatlands. A continuously maintained tree cover with significant evapotranspiration capacity could enable optimizing WTL from both tree growth and environmental perspectives.

Drought and heat events, such as the 2018 European drought, interact with the exchange of energy between the land surface and the atmosphere, potentially affecting albedo, sensible and latent heat fluxes, as well as CO 2 exchange. Each of these quantities may aggravate or mitigate the drought, heat, their side effects on productivity, water scarcity and global warming. We used measurements of 56 eddy covariance sites across Europe to examine the response of fluxes to extreme drought prevailing most of the year 2018 and how the response differed across various ecosystem types (forests, grasslands, croplands and peatlands). Each component of the surface radiation and energy balance observed in 2018 was compared to available data per site during a reference period 2004–2017. Based on anomalies in precipitation and reference evapotranspiration, we classified 46 sites as drought affected. These received on average 9% more solar radiation and released 32% more sensible heat to the atmosphere compared to the mean of the reference period. In general, drought decreased net CO 2 uptake by 17.8%, but did not significantly change net evapotranspiration. The response of these fluxes differed characteristically between ecosystems; in particular, the general increase in the evaporative index was strongest in peatlands and weakest in croplands. This article is part of the theme issue ‘Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale’.

The most common forest management method in Fennoscandia is rotation forestry including clearcutting and forest regeneration. In clearcutting, stem wood is removed and the logging residues are either removed or left on site. Clearcutting changes the microclimate and vegetation structure at the site, both of which impact the site's carbon balance. Peat soils with poor aeration and high carbon (C) densities are especially prone to such changes, and significant changes in C stocks and greenhouse gas exchange can be expected. We measured carbon dioxide (CO2) and energy fluxes with the eddy covariance method for two years (April 2016–March 2018) on a peatland drained for forestry. After the clearcutting, we observed a significant rise (23 cm) in the water table level. The site was also a large CO2 source (first year: 3086 ± 120 g CO2 m−2yr−1, second year: 2072 ± 141 g CO2 m−2 yr−1) after the clearcutting. These large CO2 emissions resulted from the collapse of gross primary production (GPP) following the removal of photosynthesizing trees and the decline of ground vegetation. During the second summer (June–August) after the clearcutting, GPP had already increased by 96 % and total ecosystem respiration decreased by 14 % from the previous summer. As a result, net CO2 emissions decreased during the second summer after clearcutting compared to the first one. The Bowen ratios were different in 2016 and 2017, starting at 2.6 in May 2016 and decreasing to less than 1.0 in August 2016, while in 2017 it varied mostly within 0.6–1.0. This was due to a 33 % decrease in the sensible heat flux and a 40 % increase in the latent heat flux from the 2016 values, 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 clearcutting, 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 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.

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 the 1970s and the tree stand is now a mixture of Scots pine, Norway spruce and pubescent birch. Our measurement system consisted of six transparent polycarbonate chambers and stainless steel frames, positioned on a number of different field and moss layer types. Flux rates were calculated with both linear and exponential regression. The use of linear regression systematically underestimated CH4 flux rates by 20–50 % when compared to exponential regression. However, the use of exponential regression with small fluxes (

The response of evapotranspiration (ET) to warming is of critical importance to the water and carbon cycle of the boreal biome, a mosaic of land cover types dominated by forests and peatlands. The effect of warming-induced vapour pressure deficit (VPD) increases on boreal ET remains poorly understood because peatlands are not specifically represented as plant functional types in Earth system models. Here we show that peatland ET increases more than forest ET with increasing VPD using observations from 95 eddy covariance tower sites. At high VPD of more than 2 kPa, peatland ET exceeds forest ET by up to 30%. Future (2091–2100) mid-growing season peatland ET is estimated to exceed forest ET by over 20% in about one-third of the boreal biome for RCP4.5 and about two-thirds for RCP8.5. Peatland-specific ET responses to VPD should therefore be included in Earth system models to avoid biases in water and carbon cycle projections. Climate warming increases evapotranspiration (ET) more in boreal peatlands than in forests. Observations show that peatland ET can exceed forest ET by up to 30%, indicating a stronger warming response in peatlands. Earth system models do not fully account for peatlands and hence may underestimate future boreal ET.