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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Laiho, Raija; Lampela, Maija; Minkkinen, Kari; Straková, Petra; +5 Authors

    We estimated fine-root biomass (FRB) and production (FRP) and their depth distribution and plant functional type (PFT) composition in four forested boreal peatland site types that varied in soil nutrient and water-table level regimes, ground vegetation and tree stand characteristics. Two were pine-dominated nutrient-poor sites (dwarf-shrub pine bog, tall-sedge pine fen) and two spruce-dominated nutrient-rich sites (Vaccinium myrtillus spruce swamp, herb-rich hardwood-spruce swamp). Measurements were done in two sites per site type: one undrained site and one site that had been drained for forestry. In each of the eight sites, we established three measurement plots. FRB was estimated by separating and visually identifying roots from soil cores extending down to 50-cm depth. The cores were taken in late August, 2016. FRP was estimated using ingrowth cores covering the same depth, and the separated roots were identified using Fourier transform infrared spectroscopy (FTIR). The ingrowth cores were incubated for two years, starting in November 2015 and ending in November 2017. Tree-stand basal area and stem volume per species, and projection cover of ground vegetation per species were determined in summer 2018. We monitored the soil water-table level and soil temperatures in 5 and 30 cm depths with dataloggers. Soil pH, bulk density, and carbon, nitrogen, phosphorus, potassium, calcium, magnesium, iron, manganese, boron, zinc, and copper concentrations were measured from peat cores extending down to 50-cm depth and taken simultaneously with the FRB cores. FRB, FRP and peat properties are presented for 10-cm depth segments. FRB, FRP and peat properties are presented for 10-cm depth segments. Peat cores were taken with a box-shaped 65 mm x 37 mm peat corer, except in the wet TP site where a 60 mm x 60 mm corer was used.

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    Authors: Mander, Ülo; Krasnova, Alisa; Escuer-Gatius, Jordi; Espenberg, Mikk; +10 Authors

    1 Study site and set-up The studied hemiboreal riparian forest is a 40-year old Filipendula type grey alder (Alnus incana (L.) Moench) forest stand grown on a former agricultural agricultural land. It is situated in the Agali Village (58o17' N; 27o17' E) in eastern Estonia within the Lake Peipsi Lowland (Varep 1964). The area is characterized by a flat relief with an average elevation of 32m a.s.l., formed from the bottom of former periglacial lake systems, it is slightly inclined (1%) towards a tributary of the Kalli River. The soil is Gleyic Luvisol. The thickness of the humus layer was 15-20 cm. The content of total carbon (TC), total nitrogen (TN), nitrate (NO3- -N), ammonia NH4+-N, Ca and Mg per dry matter in 10cm topsoil was 3.8 and 0.33 %, and 2.42, 2.89, 1487 and 283 mg kg-1, respectively, which was correspondingly 6.3, 8.3, 4.4, 3.6, 2.3, and 2.0 times more than those in 20cm deep zone. The long-term average annual precipitation of the region is 650 mm, and the average temperature is 17.0 °C in July and -6.7 °C in January. The duration of the growing season is typically 175-180 days from mid-April to October (Kupper et al. 2011). The mean height of the forest stand is 17.5 m, the mean stem diameter at breast height 15.6 cm and the growing stock 245 m3 ha−1 (based on Uri et al 2014 and Becker et al 2015). In the forest floor, the following herbs dominate: Filipendula ulmaria (L.) Maxim., Aegopodium podagraria L., Cirsium oleraceum (L.) Scop., Geum rivale L., Crepis paludosa (L.) Moench,), shrubs (Rubus idaeus L., Frangula alnus L., Daphne mezereum L.) and young trees (A. incana, Prunus padus (L.)) dominate. In moss-layer Climacium dendroides (Hedw.) F. Weber & D. Mohr, Plagiomnium spp and Rhytidiadelphus triquetrus (Hedw.) Warnst. 2 Soil flux measurements Soil fluxes were measured using 12 automatic dynamic chambers located close to each studied tree and installed in June 2017. The chambers were made from polymethyl methacrylate (Plexiglas) covered with non-transparent plastic film. Each soil chamber (volume of 0.032 m³) covered a 0.16 m² soil surface. To avoid stratification of gas inside the chamber, air with a constant flow rate of 1.8 L min-1 was circulated within a closed loop between the chamber and gas analyzer unit during the measurements by a diaphragm pump. The air sample was taken from the top of the chamber headspace and pumped back by distributing it to each side of the chamber. For the measurements, the soil chambers were closed automatically for 9 minutes each. Flushing time of the whole system with ambient air between measurement periods was 1 minute. Thus, there were approximately 12 measurements per chamber per day. A Picarro G2508 (Picarro Inc., Santa Clara, CA, USA) gas analyzer using cavity ring-down spectroscopy (CRDS) technology was used to monitor N2O gas concentrations in the frequency of approximately 1.17 measurements per second. The chambers were connected to the gas analyzer using a multiplexer. Since the 9 minutes of closing each soil chamber for measurements consisted of two minutes for stabilization the trend in the beginning and about two minutes unstable fluctuations at the end, for soil flux calculations, only 5 minutes of the linear trend of N2O concentration change has been used for soil flux calculations. After the quality checking 105,830 flux values (98.7% of total possible) of soil N2O fluxes could be used during the whole study period. 3 Stem flux measurements The tree stem fluxes were measured manually with frequency 1-2 times per week from September 2017 until December 2018. Twelve representative mature grey alder trees were selected for stem flux measurements and equipped with static closed tree stem chamber systems for stem flux measurements (Machacova et al 2016). Soil fluxes were investigated close to each selected tree. The tree chambers were installed in June 2017 in following order: at the bottom part of the tree stem (approximately 10 cm above the soil) and at 80 and 170 cm above the ground. The rectangular shape stem chambers were made of transparent plastic containers, including removable airtight lids (Lock & Lock Co Ltd, Seoul, Republic of Korea). For chamber preparation see Schindler et al. (2020). Two chambers per profile were set randomly across 180° and interconnected with tubes into one system (total volume of 0.00119 m³) covering 0.0108 m² of stem surface. A pump (model 1410VD, 12 V; Thomas GmbH, Fürstenfeldbruck, Germany) was used to homogenize the gas concentration prior to sampling. Chamber systems remained open between each sampling campaign. During 60 measurement campaigns, four gas samples (each 25 ml) were collected from each chamber system via septum in a 60 min interval: 0/60/120/180 min sequence (sampling time between 12:00 and 16:00) and stored in pre-evacuated (0.3 bar) 12 ml coated gas-tight vials (LabCo International, Ceregidion, UK). The gas samples were analysed in the laboratory at University of Tartu within a week using gas chromatograph (GC-2014; Shimadzu, Kyoto, Japan) equipped with an electron capture detector for detection of N2O and a flame ionization detector for CH4. The gas samples were injected automatically using Loftfield autosampler (Loftfield Analytics, Göttingen, Germany). For gas-chromatographical settings see Soosaar et al. (2011). 4 Soil and stem flux calculation Fluxes were quantified on a linear approach according to change of CH4 and N2O concentrations in the chamber headspace over time, using the equation according to Livingston & Hutchison (1995). Stem fluxes were quantified on a linear approach according to change of N2O concentrations in the chamber headspace over time. A data quality control was applied based on R2 values of linear fit for CO2 measurements. When the R2 value for CO2 efflux was above 0.9, the conditions inside the chamber were applicable, and the calculations for N2O gases were also accepted in spite of their R2 values. To compare the contribution of soil and stems, the stem fluxes were upscaled to hectare of ground area based on average stem diameter, tree height, stem surface area, tree density, and stand basal area estimated for each period. A cylindric shape of tree stem was assumed. To estimate average stem emissions per tree, fitted regression curves for different periods were made between the stem emissions and height of the measurements as previously done by Schindler et al. (2020). 5 Eddy covariance instrumentation Eddy-covariance system was installed on a 21 m height scaffolding tower. Fast 3-D sonic anemometer Gill HS-50 (Gill Instruments Ltd., Lymington, Hampshire, UK) was used to obtain 3 wind components. CO2 fluxes were measured using the Li-Cor 7200 analyser (Li-Cor Inc., Lincoln, NE, USA). Air was sampled synchronously with the 30 m teflon inlet tube and analyzed by a quantum cascade laser absorption spectrometer (QCLAS) (Aerodyne Research Inc., Billerica, MA, USA) for N2O concentrations. The Aerodyne QCLAS was installed in the heated and ventilated cottage near the tower base. A high-capacity free scroll vacuum pump (Agilent, Santa Clara, CA, USA) guaranteed air flow rate 15 L min-1 between the tower and gas analyzer during the measurements. Air was filtered for dust and condense water. All measurements were done at 10Hz and the gas-analyzer reported concentrations per dry air (mixing ratios). 6 Eddy-covariance flux calculation and data quality control The fluxes of N2O were calculated using the EddyPro software (v.6.0-7.0, Li-Cor) as a covariance of the gas mixing ratio with the vertical wind component over 30-minute periods. Despiking of the raw data was performed following Mauder (2013). Anemometer tilt was corrected with the double axis rotation. Linear detrending was chosen over block averaging to minimize the influence of a possible fluctuations of a gas analyser. Time lags were detected using covariance maximisation in a given time window (5±2s was chosen based on the tube length and flow rate). While WPL-correction is typically performed for the closed-path systems, we did not apply it as water correction was already performed by the Aerodyne and the software reported mixing ratios. Both low and high frequency spectral corrections were applied using fully analytic corrections (Moncrieff et al. 1997, 2004). Calculated fluxes were filtered out in case they were coming from the half-hour averaging periods with at least one of the following criteria: more than 1000 spikes, half-hourly averaged mixing ratio out of range (300-350 ppb), quality control (QC) flags higher than 7 (Foken et al, 2004). Footprint area was estimated using Kljun et al (2015) implemented in TOVI software (Li-Cor Inc.). Footprint allocation tool was implemented to flag the non-forested areas within the 90% cumulative footprint and fluxes appointed to these areas were removed from the further analysis. Storage fluxes were estimated using point concentration measurements from the eddy system, assuming the uniform change within the air column under the tower during every 30 min period (calculated in EddyPro software). In the absence of a better estimate or profile measurements, these estimates were used to correct for storage change. Total flux values that were higher than eight times the standard deviation were additionally filtered out (following Wang et al., 2013). Overall, the quality control procedures resulted in 61% data coverage. While friction velocity (u*) threshold is used to filter eddy fluxes of CO2 (Papale et al. 2006), visual inspection of the friction velocity influence on N2O fluxes demonstrated no effect. Thus, we decided not to apply it, taking into account that 1-9 QC flag system already marks the times when the turbulence is not sufficient. To obtain the continuous time-series and to enable the comparison to chamber estimates over hourly time scales, gap-filling of N2O fluxes was performed using marginal distribution sampling method implemented in ReddyProcWeb online tool (https://www.bgc-jena.mpg.de/bgi/index.php/Services/REddyProcWeb) (described in detail in Wutzler et al 2018). MATLAB (ver. 2018a-b, Mathworks Inc., Natick, MA, USA) was used for all the eddy fluxes data analysis. 7 Ancillary measurements Air temperature and relative humidity were measured within the canopy at 10m height using the HC2A-S3 - Standard Meteo Probe / RS24T (Rotronic AG, Bassersdorf, Switzerland) and Campbell CR100 data logger (Campbell Scientific Inc., Logan, UT, USA). Based on these data, dew point depression was calculated to characterise chance of fog formation within the canopy. The incoming solar radiation data were obtained from the SMEAR Estonia station located at 2 km from the study site (Noe et al 201587) using the Delta-T-SPN-1 sunshine pyranometer (Delta-T Devices Ltd., Cambridge, UK). The cloudiness ratio was calculated based on radiation data. Near-ground air temperature, soil temperature (Campbell Scientific Inc.) and soil water content sensors (ML3 ThetaProbe, Delta-T Devices, Burwell, Cambridge, UK) were installed directly on the ground and 0-10 cm soil depth close to the studied tree spots. During six campaigns from August to November 2017 composite topsoil samples were taken with a soil corer from a depth of 0-10 cm for physical and chemical analysis using standard methods (APHA-AWWA-WEF, 2005).

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    Authors: Voigt, Carolina; Chevrier-Dion, Charles; Marquis, Charlotte; Nesic, Zoran; +7 Authors

    This dataset includes two data tables of methane (CH4) fluxes measured in Arctic uplands. Dataset 1 contains CH4 fluxes measured at high temporal resolution (hourly fluxes) collected over two snow-free seasons (June–August; 2019, 2021) at Trail Valley Creek, an Arctic tundra site in the Western Canadian Arctic. Fluxes were measured with automated chambers installed in replication of six at three individual landcover vegetation units (Lichen, Shrub, Tussock) within dwarf-shrub dominated tundra. Site meteorological data are provided with the flux data at hourly resolution. Dataset 2 includes campaign-based, manual chamber measurements at sites displaying net CH4 uptake. These manual measurements were conducted during the growing season at typical, well-drained upland sites, which included, besides Trail Valley Creek, three additional sites in the Canadian and European Arctic (Havikpak Creek, Scotty Creek, Kilpisjärvi). Besides CH4 flux observations, dataset 2 contains measured greenhouse gas concentration profiles of CH4, carbon dioxide (CO2) and nitrous oxide (N2O) at 2 cm, 5 cm, 10 cm, and 20 cm soil depths, as well as site meteorological data. While wetlands are known CH4 emitters, drier arctic and boreal uplands may act as sinks of atmospheric CH4. The scope of the study and this dataset is to improve the spatial and temporal coverage of low CH4 emitting and sites displaying net CH4 uptake across the Arctic. Both datasets are meant as supplement to the published study, where further, detailed information on site conditions and methodology can be found.

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    Authors: Spilling, Kristian; Piiparinen, Jonna; Achterberg, Eric Pieter; Arístegui, Javier; +9 Authors

    The data is from a mesocosm experiment set up outside Lima, Peru to study the influence of upwelling of oxygen minimum zone (OMZ) water. The mesocosm bags were 2 m in diameter and extended from the surface down to 19 m depth, where the last 2 m was a conical sediment trap. Eight mesocosm bags were used and they were moored at 12.0555°S; 77.2348°W just north of Isla San Lorenzo where the water depth is ~30 m. The experiment was started 25 February 2017 by closing the mesocosm bags and were run for 50 days. Two treatments were used (water with different OMZ signature), each with four replicates. Water (100 m3) from the OMZ was collected from two locations and depths. The first was collected from 12.028323°S; 77.223603°W from 30 m depth, and the second one from 12.044333°S; 77.377583°W from 70 m depth. The original aim was to collect severe and moderate OMZ signature water (differing in e.g. nitrate concentrations) from the first and second site, respectively. This assumption was based on long-term monitoring data, however, the chemical properties (e.g. nitrate concentration) was more similar in these water masses than anticipated, rather reflecting low and very low OMZ signatures from site 1 and 2 respectively. To have a baseline of measured variables, the mesocosms where closed and environmental and biological variables were determined over 10 days. After this period, the OMZ water was added to the mesocosms in two steps on day 11 and 12 after the enclosure of the mesocosms. As the mesocosms contain a specific volume (~54 m3), the process of adding the OMZ water started with first removing water from the mesocosms. The water removed (~20 m3) was pumped out from 11-12 m depth. A similar volume of OMZ water, from both collection sites, was then pumped into four replicate mesocosms each. The OMZ water was pumped into the mesocosms moving the input hose between 14-17 m depth. The water collected at 30 m depth was pumped into mesocosms M1, M4, M5 and M8 having a low OMZ signature and water from 70 m depth into mesocosms M2, M3, M6 and M7 having a very low OMZ signature. Due a halocline at 12 m depth (see below), the added OMZ water was not immediately mixed throughout the mesocosm bag. Sampling took place every second day over a period of 50 days, and all variables were taken with an integrated water sampler (HydroBios, IWS) pre-programed to fill from 0 – 10 m depth and all samples consisted of this integrated samples from the upper 10 m. The samples were stored dark in cool boxes and brought back to the laboratory and processed right away. Sampling took place in the morning, and the samples were usually back in the laboratory around noon. Measured variables included inorganic nutrients, dissolved organic nutrients, extracellular enzyme activity: leucine aminopeptidase (LAP) and alkaline phosphatase, and the phytoplankton and bacterial community composition.

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    Authors: Laine-Petäjäkangas, Anna Maria; Korrensalo, Aino; Kokkonen, Nicola A K; Tuittila, Eeva-Stiina;

    We measured the following vascular plant functional traits: plant height (cm), leaf size (LS, cm2), specific leaf area (SLA, cm2 g-1), leaf dry matter content (LDMC, mg g-1) and leaf moisture content (g g-1) from the most common species in each research unit. We measured the following Sphagnum traits: capitulum density (number of shoots cm-2), fascicle density (number cm-1), surface density (mg cm-3), capitulum dry mass (mg) and capitulum moisture content (cap_wc, g g-1). In addition, rate of net photosynthesis was measured at four light levels. The data was collected from Lakkasuo mire complex located in Southern Finland (61° 47' N; 24° 18' E). The study includes three sites called rich fen, poor fen, and bog. At each site two experimental units were established in 2000/2001: an undrained control unit and a Water level drawdown (WLD) unit that was surrounded by a 30 cm-deep ditches after a control year. Photosynthesis measurements were carried out during summer 2016, while other traits were sampled during August 2016. We measured vascular plant vegetative height (cm), leaf area (LA, cm2 leaf-1) with a leaf area scanner (LI-3000, LI-COR Inc.), leaf fresh mass and leaf dry mass after the sample was dried at 40 °C for at least 48h (mg leaf-1). Leaf dry matter content (LDMC mg g-1) was calculated from fresh and dry mass, while specific leaf area (SLA, cm2 g-1) was calculated from LA and dry mass. Leaf traits were measured from five replicate plants as an average of a sample of ten fully grown healthy leaves from each plant. Sphagnum moss traits were measured from five replicates of single-species samples. Each sample consisted of two parts: a volume-specific sample collected with a core (diameter 7 cm, area 38.5 cm2, height 3 cm) to maintain the natural density of the stand and an additional sample of ca. 10 individuals, with stems more than 5 cm at length. Before collecting the core in the field, the number of shoots was counted from a 4 × 4 cm square for capitulum density (cap_dens, number of shoots cm-2). The volume-specific sample was cleaned of litter and unwanted species before drying at 40 °C for at least 48h to determine the surface density (surf_dens, mg cm-3). The additional sample of ten moss individuals was divided into capitula and stems (4 cm below capitula). We counted the number of fascicles on the 4 cm stem segments (fasc_dens, number cm-1). The capitula were thoroughly moistened and placed on top of tissue paper for 2 minutes to drain, before weighing them for water-filled fresh mass (cap_fw, mg). The samples were dried at 60 °C for at least 48h to measure the capitulum dry masses (cap_dw, mg). The moisture contents of capitula (cap_mc, g g-1) were then calculated as the ratio of water-filled to dry mass. Height growth (mm growing season-1) was measured in the field with the modified cranked wire method (Clymo 1970) as a difference in height between the beginning (mid-May) and end (mid-October) of the growing season 2017. For both vascular plants and mosses, we measured net photosynthesis rate, with a fully controlled, flow-through gas-exchange fluorescence measurement systems (GFS-3000, Walz, Germany; LI6400, LI-COR, USA). For mosses the living apical parts (~0.5 to 1 cm) were harvested right before the measurement and placed on a custom-made cuvette. For vascular plants, leaves, or in the case of shrubs, segments of branches were enclosed within the cuvette without disturbing the connection to the rooting system. Net photosynthesis rate (A, µmol m-2 g-1 s-1) was measured at 1500, 250, 35, and 0 µmol m-2 s-1 photosynthetic photon flux density (PPFD). The cuvette conditions were kept constant (temperature 20°C, CO2 concentration 400 ppm, flow rate 500, impeller in level 5). Relative humidity (Rh) of incoming air was set to 40% for vascular plants and 60% for mosses; for mosses this setting retained the cuvette Rh at around 80%. The setting enabled mosses to remain moist to ensure photosynthesis but protected the device from excess moisture. The data was collected to find out the impact of long-term WLD on functional traits of vascular plants and mosses, and how this impact is modulated by nutrient status (rich fen, poor fen, bog). We first assess (i) how peatland species differ in their traits and their intraspecific trait variability, to quantify (ii) how WLD impacts community level traits at different peatland sites.

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    Authors: Elovaara, Samu; Eronen-Rasimus, Eeva; Asmala, Eero; Tamelander, Tobias; +1 Authors

    The data were collected from an experiment using phytoplankton cultures (Apocalathium malmogiense and Rhodomonas marina). The aim of the experiment was to study carbon cycling among phytoplankton and bacteria, and the effects on the dissolved organic matter (DOM) pool. Measured variables include phytoplankton and bacterial abundance, primary production, bacterial production and respiration, 14C-transfer from phytoplankton to DOM and bacteria, concentrations of particulate and dissolved organic carbon, nitrate, phosphate and chlorophyll a, and optical characteristics of dissolved organic matter. The experiment was conducted at Tvärminne Zoological Station, Hanko, Finland with non-axenic unialgal phytoplankton cultures and bacteria originating from the Baltic Sea. The experiment was conducted between Dec. 2017 and Apr. 2018. The experiment consisted of two parts, the DOM release experiment (part 1) and the DOM consumption experiment (part 2). Separate triplicate batch cultures of both phytoplankton species were grown for each experiment. In the DOM release experiment the cultures were grown for over 4 months and three day-long incubations (key point incubations, KPI's) were initiated on three occasions; the first KPI at early exponential growth phase and the second and third KPI's when the phytoplankton had grown more abundant. During each KPI and aliquot of the culture was inoculated with freshly collected sea water bacteria, and bacterial community composition was measured. This aliquot was then divided into two further aliquots; one was incubated with radioisotopes for productivity (primary and bacterial production) and 14C-flow analyses (production line) and one filtered through 0.8 µm for analysis of DOM optical properties. During the KPI's measurements were taken at 0, 4, 8 and 12 h. Nutrient concentrations (measured from non-filtered and 0.8 µm filtered samples) and concentration of dissolved organic carbon were measured only at 0 and 12 h. Concentrations of particulate organic carbon and nitrogen and chlorophyll a were measured only once for each KPI at the beginning of the incubation. In the DOM consumption experiments the cultures were grown to high abundance, after which the phytoplankton and most of the bacteria were filtered out. The filtrate was then inoculated with freshly collected sea water bacteria, after which it was incubated for 7 days. Bacterial abundance, production, respiration, and community composition, and concentration and optical properties of DOM were measured daily. The experimental design is explained in figure 1 of the associated publication.

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    Authors: Laine-Petäjäkangas, Anna Maria; Lindholm, Tapio; Nilsson, Mats; Kutznetsov, Oleg; +2 Authors

    We estimated plant community composition as the projection cover of each vascular plant and moss species. We measured the following vascular plant functional traits: plant height, leaf size (LS), specific leaf area (SLA) and leaf carbon (C) and nitrogen (N) contents from the most common species in each site. We measured the following Sphagnum traits: stand density (number of shoots cm-2), capitulum width (cap_width, mm) and dry weight (cap_dw, mg), fascicle density (number cm-1), capitulum dry matter content (CDMC, mg g-1), capitulum water content (cap_wc, g g-1) and capitulum C and N contents and C:N ratio. The data was collected from 47 northern peatlands located in land uplift regions in Finland, Sweden and Russia: Sävar on the west coast of Bothnian Bay (63o50'N, 20o40'E, Sweden), Siikajoki (64°45' N, 24°43', Finland) and Hailuoto island (65°07' N, 24°71' E, Finland) on the east coast of Bothnian Bay, and Belomorsk-Virma (63°90' N, 36°50' E, Russia) on the coast of the White Sea. The data was collected from the different areas as follows: Siikajoki sites were sampled in August 2016, Sävar sites at the end of June 2017, Hailuoto sites during July 2017 and Belomorsk sites at the end of August 2017. We determined the plant community composition by visually estimating the projection cover of each species separately for field (vascular plants) and moss layer using the scale 0.1%, 0.25%, 0.5%, 1%, 2%, 3%, etc. There were fifteen 50 x 50 cm plots in each peatland at Siikajoki and Belomorsk-Virma, and 10 at Sävar and Hailuoto. The sample plots were located five meters apart along a transect starting from the generally treeless peatland margin and heading towards the peatland center. Plant traits were measured as follows: To measure SLA (i.e., the one-sided area of a fresh leaf divided by its oven-dry mass, cm2 g-1), the freshly picked leaf or a sample of 3 leaves in case of shrubs with small leaves was pressed flat between a board and a glass and a standardized photo was taken. The leaf size (LS, cm2) was analysed from the photos with ImageJ. The leaf samples were stored in paper bags and dried at 60°C for a minimum of 48h. The dried samples were weighed, and SLA calculated. The SLA samples were used for carbon (C) and nitrogen (N) content analysis. Leaves from each species from each site were pooled into one sample, which was milled (Retsch MM301 mill) and analyzed for C and N concentrations and for C:N ration on a CHNS–O Elemental analyzer (EA1110) (University of Oulu). Sphagnum moss samples for trait measurements were collected with a corer (7 cm diameter, area 38 cm2, height at least 8 cm) to maintain the natural density of the stand. Stand density was measured as the number of mosses in the sample. From ten individuals we measured the width of the capitula and counted the number of fascicles from a five cm segment below capitulum. We separated the ten moss individuals into capitulum and stem (5 cm below capitula) wetted them and allowed to dry on top of tissue paper for 2 min before weighing them for water filled fresh weight. Samples were placed on paper bags and dried at 60 °C for at least 48h after which the dry mass of capitula and stems were measured. CDMC and cap_wc were calculated from the fresh and dry weight. We used the capitula samples for analyses of C and N concentrations and for C:N ratio, and treated them similarly to vascular plant samples. The data was collected to find out how functional diversity and trait composition of vascular plant and Sphagnum moss communities develops during peatland succession across land uplift regions.

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    Authors: Zweifel, Roman; Etzold, Sophia; Haeni, Matthias; Feichtinger, Linda; +6 Authors

    Within the setup of a long‐term irrigation experiment in a Scots pine (Pinus sylvestris) forest at Pfynwald in the inner-Alpine Swiss Rhone valley, ecophysiological data were recorded from permanently irrigated trees, from trees cut off the irrigation after 11 years, and non-treated control trees. The data sets include continuous stem radius changes (automated point dendrometer at breast height), tree stem sap flow (Granier-type sap flow sensors at breast height), air temperature and humidity, vapour pressure deficit, net solar radiation, precipitation (tipping bucket), and volumetric soil water content (TDR and HS-sensors). The meteorological data were measured 2 m above the canopy in about 13 m height on top of a scaffold. The soil water sensors covered soil depth of up to 80 cm. Data resolution is 1 hour or higher and covers the years 2011-2017. Data as used and published in Zweifel, et al. (2020), Determinants of legacy effects in pine trees ‐ implications from an irrigation‐stop experiment. New Phytol. doi:10.1111/nph.16582

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    Authors: Spilling, Kristian;

    In an enclosure experiment, we employed two levels of inorganic NP ratios (10 and 5) for three distinct plankton communities collected along the coast of central Chile (33ºS). Each combination of community and NP level was replicated three times. The experiment lasted 12 days, and the data set include inorganic nutrients (NO3, PO4, DSi), particular organic carbon (POC), nitrogen (PON) and phosphorus (POP), Chlorophyll a, a range of fluorescence based measurements such as photochemical efficiency (Fv/Fm) and community data. The primary effect of the NP treatment was related to different concentrations of NO3, which directly influenced the biomass of phytoplankton. Additionally, low inorganic NP ratio reduced the seston NP and Chl a-C ratios, and there were some effects on the plankton community composition, e.g. benefitting Synechococcus spp in some communities.

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    Authors: Barboza, Francisco Rafael; Kotta, Jonne; Weinberger, Florian; Jormalainen, Veijo; +14 Authors

    Data on morphological and biochemical traits of the bladderwrack Fucus vesiculosus were obtained from individuals simultaneously collected in September 2011 in 20 stations along the Baltic Sea and 4 stations in the North Sea. The individuals included in the analysis were collected at 0.5-1.0 m depth. Frond length, frond width, stipe width and number of fronds were directly determined in the field. All collected individuals were transported to the laboratory in cooler boxes at temperatures below 5 °C, then frozen at -20 °C within 12 h, and shipped to the GEOMAR-Helmholtz Centre for Ocean Research Kiel (Germany) on dry ice. Measurements of chlorophyll a and fucoxanthin in surface and tissue extracts, mannitol, phlorotannins and carbon:nitrogen ratio were performed in the laboratory (see further methodological details in the related article). The relative palatability of the algal material collected in all 24 stations was determined in palatability assays, using reconstituted algal pellets and the pan-Baltic grazer Idotea balthica. In addition to the trait information, environmental data on sea surface salinity, sea surface summer temperature, photosynthetically active radiation (PAR), wave exposure and total nitrogen have been obtained from the Swedish Meteorological and Hydrological Institute (SMHI) or local monitoring services.

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    Authors: Laiho, Raija; Lampela, Maija; Minkkinen, Kari; Straková, Petra; +5 Authors

    We estimated fine-root biomass (FRB) and production (FRP) and their depth distribution and plant functional type (PFT) composition in four forested boreal peatland site types that varied in soil nutrient and water-table level regimes, ground vegetation and tree stand characteristics. Two were pine-dominated nutrient-poor sites (dwarf-shrub pine bog, tall-sedge pine fen) and two spruce-dominated nutrient-rich sites (Vaccinium myrtillus spruce swamp, herb-rich hardwood-spruce swamp). Measurements were done in two sites per site type: one undrained site and one site that had been drained for forestry. In each of the eight sites, we established three measurement plots. FRB was estimated by separating and visually identifying roots from soil cores extending down to 50-cm depth. The cores were taken in late August, 2016. FRP was estimated using ingrowth cores covering the same depth, and the separated roots were identified using Fourier transform infrared spectroscopy (FTIR). The ingrowth cores were incubated for two years, starting in November 2015 and ending in November 2017. Tree-stand basal area and stem volume per species, and projection cover of ground vegetation per species were determined in summer 2018. We monitored the soil water-table level and soil temperatures in 5 and 30 cm depths with dataloggers. Soil pH, bulk density, and carbon, nitrogen, phosphorus, potassium, calcium, magnesium, iron, manganese, boron, zinc, and copper concentrations were measured from peat cores extending down to 50-cm depth and taken simultaneously with the FRB cores. FRB, FRP and peat properties are presented for 10-cm depth segments. FRB, FRP and peat properties are presented for 10-cm depth segments. Peat cores were taken with a box-shaped 65 mm x 37 mm peat corer, except in the wet TP site where a 60 mm x 60 mm corer was used.

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    Authors: Mander, Ülo; Krasnova, Alisa; Escuer-Gatius, Jordi; Espenberg, Mikk; +10 Authors

    1 Study site and set-up The studied hemiboreal riparian forest is a 40-year old Filipendula type grey alder (Alnus incana (L.) Moench) forest stand grown on a former agricultural agricultural land. It is situated in the Agali Village (58o17' N; 27o17' E) in eastern Estonia within the Lake Peipsi Lowland (Varep 1964). The area is characterized by a flat relief with an average elevation of 32m a.s.l., formed from the bottom of former periglacial lake systems, it is slightly inclined (1%) towards a tributary of the Kalli River. The soil is Gleyic Luvisol. The thickness of the humus layer was 15-20 cm. The content of total carbon (TC), total nitrogen (TN), nitrate (NO3- -N), ammonia NH4+-N, Ca and Mg per dry matter in 10cm topsoil was 3.8 and 0.33 %, and 2.42, 2.89, 1487 and 283 mg kg-1, respectively, which was correspondingly 6.3, 8.3, 4.4, 3.6, 2.3, and 2.0 times more than those in 20cm deep zone. The long-term average annual precipitation of the region is 650 mm, and the average temperature is 17.0 °C in July and -6.7 °C in January. The duration of the growing season is typically 175-180 days from mid-April to October (Kupper et al. 2011). The mean height of the forest stand is 17.5 m, the mean stem diameter at breast height 15.6 cm and the growing stock 245 m3 ha−1 (based on Uri et al 2014 and Becker et al 2015). In the forest floor, the following herbs dominate: Filipendula ulmaria (L.) Maxim., Aegopodium podagraria L., Cirsium oleraceum (L.) Scop., Geum rivale L., Crepis paludosa (L.) Moench,), shrubs (Rubus idaeus L., Frangula alnus L., Daphne mezereum L.) and young trees (A. incana, Prunus padus (L.)) dominate. In moss-layer Climacium dendroides (Hedw.) F. Weber & D. Mohr, Plagiomnium spp and Rhytidiadelphus triquetrus (Hedw.) Warnst. 2 Soil flux measurements Soil fluxes were measured using 12 automatic dynamic chambers located close to each studied tree and installed in June 2017. The chambers were made from polymethyl methacrylate (Plexiglas) covered with non-transparent plastic film. Each soil chamber (volume of 0.032 m³) covered a 0.16 m² soil surface. To avoid stratification of gas inside the chamber, air with a constant flow rate of 1.8 L min-1 was circulated within a closed loop between the chamber and gas analyzer unit during the measurements by a diaphragm pump. The air sample was taken from the top of the chamber headspace and pumped back by distributing it to each side of the chamber. For the measurements, the soil chambers were closed automatically for 9 minutes each. Flushing time of the whole system with ambient air between measurement periods was 1 minute. Thus, there were approximately 12 measurements per chamber per day. A Picarro G2508 (Picarro Inc., Santa Clara, CA, USA) gas analyzer using cavity ring-down spectroscopy (CRDS) technology was used to monitor N2O gas concentrations in the frequency of approximately 1.17 measurements per second. The chambers were connected to the gas analyzer using a multiplexer. Since the 9 minutes of closing each soil chamber for measurements consisted of two minutes for stabilization the trend in the beginning and about two minutes unstable fluctuations at the end, for soil flux calculations, only 5 minutes of the linear trend of N2O concentration change has been used for soil flux calculations. After the quality checking 105,830 flux values (98.7% of total possible) of soil N2O fluxes could be used during the whole study period. 3 Stem flux measurements The tree stem fluxes were measured manually with frequency 1-2 times per week from September 2017 until December 2018. Twelve representative mature grey alder trees were selected for stem flux measurements and equipped with static closed tree stem chamber systems for stem flux measurements (Machacova et al 2016). Soil fluxes were investigated close to each selected tree. The tree chambers were installed in June 2017 in following order: at the bottom part of the tree stem (approximately 10 cm above the soil) and at 80 and 170 cm above the ground. The rectangular shape stem chambers were made of transparent plastic containers, including removable airtight lids (Lock & Lock Co Ltd, Seoul, Republic of Korea). For chamber preparation see Schindler et al. (2020). Two chambers per profile were set randomly across 180° and interconnected with tubes into one system (total volume of 0.00119 m³) covering 0.0108 m² of stem surface. A pump (model 1410VD, 12 V; Thomas GmbH, Fürstenfeldbruck, Germany) was used to homogenize the gas concentration prior to sampling. Chamber systems remained open between each sampling campaign. During 60 measurement campaigns, four gas samples (each 25 ml) were collected from each chamber system via septum in a 60 min interval: 0/60/120/180 min sequence (sampling time between 12:00 and 16:00) and stored in pre-evacuated (0.3 bar) 12 ml coated gas-tight vials (LabCo International, Ceregidion, UK). The gas samples were analysed in the laboratory at University of Tartu within a week using gas chromatograph (GC-2014; Shimadzu, Kyoto, Japan) equipped with an electron capture detector for detection of N2O and a flame ionization detector for CH4. The gas samples were injected automatically using Loftfield autosampler (Loftfield Analytics, Göttingen, Germany). For gas-chromatographical settings see Soosaar et al. (2011). 4 Soil and stem flux calculation Fluxes were quantified on a linear approach according to change of CH4 and N2O concentrations in the chamber headspace over time, using the equation according to Livingston & Hutchison (1995). Stem fluxes were quantified on a linear approach according to change of N2O concentrations in the chamber headspace over time. A data quality control was applied based on R2 values of linear fit for CO2 measurements. When the R2 value for CO2 efflux was above 0.9, the conditions inside the chamber were applicable, and the calculations for N2O gases were also accepted in spite of their R2 values. To compare the contribution of soil and stems, the stem fluxes were upscaled to hectare of ground area based on average stem diameter, tree height, stem surface area, tree density, and stand basal area estimated for each period. A cylindric shape of tree stem was assumed. To estimate average stem emissions per tree, fitted regression curves for different periods were made between the stem emissions and height of the measurements as previously done by Schindler et al. (2020). 5 Eddy covariance instrumentation Eddy-covariance system was installed on a 21 m height scaffolding tower. Fast 3-D sonic anemometer Gill HS-50 (Gill Instruments Ltd., Lymington, Hampshire, UK) was used to obtain 3 wind components. CO2 fluxes were measured using the Li-Cor 7200 analyser (Li-Cor Inc., Lincoln, NE, USA). Air was sampled synchronously with the 30 m teflon inlet tube and analyzed by a quantum cascade laser absorption spectrometer (QCLAS) (Aerodyne Research Inc., Billerica, MA, USA) for N2O concentrations. The Aerodyne QCLAS was installed in the heated and ventilated cottage near the tower base. A high-capacity free scroll vacuum pump (Agilent, Santa Clara, CA, USA) guaranteed air flow rate 15 L min-1 between the tower and gas analyzer during the measurements. Air was filtered for dust and condense water. All measurements were done at 10Hz and the gas-analyzer reported concentrations per dry air (mixing ratios). 6 Eddy-covariance flux calculation and data quality control The fluxes of N2O were calculated using the EddyPro software (v.6.0-7.0, Li-Cor) as a covariance of the gas mixing ratio with the vertical wind component over 30-minute periods. Despiking of the raw data was performed following Mauder (2013). Anemometer tilt was corrected with the double axis rotation. Linear detrending was chosen over block averaging to minimize the influence of a possible fluctuations of a gas analyser. Time lags were detected using covariance maximisation in a given time window (5±2s was chosen based on the tube length and flow rate). While WPL-correction is typically performed for the closed-path systems, we did not apply it as water correction was already performed by the Aerodyne and the software reported mixing ratios. Both low and high frequency spectral corrections were applied using fully analytic corrections (Moncrieff et al. 1997, 2004). Calculated fluxes were filtered out in case they were coming from the half-hour averaging periods with at least one of the following criteria: more than 1000 spikes, half-hourly averaged mixing ratio out of range (300-350 ppb), quality control (QC) flags higher than 7 (Foken et al, 2004). Footprint area was estimated using Kljun et al (2015) implemented in TOVI software (Li-Cor Inc.). Footprint allocation tool was implemented to flag the non-forested areas within the 90% cumulative footprint and fluxes appointed to these areas were removed from the further analysis. Storage fluxes were estimated using point concentration measurements from the eddy system, assuming the uniform change within the air column under the tower during every 30 min period (calculated in EddyPro software). In the absence of a better estimate or profile measurements, these estimates were used to correct for storage change. Total flux values that were higher than eight times the standard deviation were additionally filtered out (following Wang et al., 2013). Overall, the quality control procedures resulted in 61% data coverage. While friction velocity (u*) threshold is used to filter eddy fluxes of CO2 (Papale et al. 2006), visual inspection of the friction velocity influence on N2O fluxes demonstrated no effect. Thus, we decided not to apply it, taking into account that 1-9 QC flag system already marks the times when the turbulence is not sufficient. To obtain the continuous time-series and to enable the comparison to chamber estimates over hourly time scales, gap-filling of N2O fluxes was performed using marginal distribution sampling method implemented in ReddyProcWeb online tool (https://www.bgc-jena.mpg.de/bgi/index.php/Services/REddyProcWeb) (described in detail in Wutzler et al 2018). MATLAB (ver. 2018a-b, Mathworks Inc., Natick, MA, USA) was used for all the eddy fluxes data analysis. 7 Ancillary measurements Air temperature and relative humidity were measured within the canopy at 10m height using the HC2A-S3 - Standard Meteo Probe / RS24T (Rotronic AG, Bassersdorf, Switzerland) and Campbell CR100 data logger (Campbell Scientific Inc., Logan, UT, USA). Based on these data, dew point depression was calculated to characterise chance of fog formation within the canopy. The incoming solar radiation data were obtained from the SMEAR Estonia station located at 2 km from the study site (Noe et al 201587) using the Delta-T-SPN-1 sunshine pyranometer (Delta-T Devices Ltd., Cambridge, UK). The cloudiness ratio was calculated based on radiation data. Near-ground air temperature, soil temperature (Campbell Scientific Inc.) and soil water content sensors (ML3 ThetaProbe, Delta-T Devices, Burwell, Cambridge, UK) were installed directly on the ground and 0-10 cm soil depth close to the studied tree spots. During six campaigns from August to November 2017 composite topsoil samples were taken with a soil corer from a depth of 0-10 cm for physical and chemical analysis using standard methods (APHA-AWWA-WEF, 2005).

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    Authors: Voigt, Carolina; Chevrier-Dion, Charles; Marquis, Charlotte; Nesic, Zoran; +7 Authors

    This dataset includes two data tables of methane (CH4) fluxes measured in Arctic uplands. Dataset 1 contains CH4 fluxes measured at high temporal resolution (hourly fluxes) collected over two snow-free seasons (June–August; 2019, 2021) at Trail Valley Creek, an Arctic tundra site in the Western Canadian Arctic. Fluxes were measured with automated chambers installed in replication of six at three individual landcover vegetation units (Lichen, Shrub, Tussock) within dwarf-shrub dominated tundra. Site meteorological data are provided with the flux data at hourly resolution. Dataset 2 includes campaign-based, manual chamber measurements at sites displaying net CH4 uptake. These manual measurements were conducted during the growing season at typical, well-drained upland sites, which included, besides Trail Valley Creek, three additional sites in the Canadian and European Arctic (Havikpak Creek, Scotty Creek, Kilpisjärvi). Besides CH4 flux observations, dataset 2 contains measured greenhouse gas concentration profiles of CH4, carbon dioxide (CO2) and nitrous oxide (N2O) at 2 cm, 5 cm, 10 cm, and 20 cm soil depths, as well as site meteorological data. While wetlands are known CH4 emitters, drier arctic and boreal uplands may act as sinks of atmospheric CH4. The scope of the study and this dataset is to improve the spatial and temporal coverage of low CH4 emitting and sites displaying net CH4 uptake across the Arctic. Both datasets are meant as supplement to the published study, where further, detailed information on site conditions and methodology can be found.

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    Authors: Spilling, Kristian; Piiparinen, Jonna; Achterberg, Eric Pieter; Arístegui, Javier; +9 Authors

    The data is from a mesocosm experiment set up outside Lima, Peru to study the influence of upwelling of oxygen minimum zone (OMZ) water. The mesocosm bags were 2 m in diameter and extended from the surface down to 19 m depth, where the last 2 m was a conical sediment trap. Eight mesocosm bags were used and they were moored at 12.0555°S; 77.2348°W just north of Isla San Lorenzo where the water depth is ~30 m. The experiment was started 25 February 2017 by closing the mesocosm bags and were run for 50 days. Two treatments were used (water with different OMZ signature), each with four replicates. Water (100 m3) from the OMZ was collected from two locations and depths. The first was collected from 12.028323°S; 77.223603°W from 30 m depth, and the second one from 12.044333°S; 77.377583°W from 70 m depth. The original aim was to collect severe and moderate OMZ signature water (differing in e.g. nitrate concentrations) from the first and second site, respectively. This assumption was based on long-term monitoring data, however, the chemical properties (e.g. nitrate concentration) was more similar in these water masses than anticipated, rather reflecting low and very low OMZ signatures from site 1 and 2 respectively. To have a baseline of measured variables, the mesocosms where closed and environmental and biological variables were determined over 10 days. After this period, the OMZ water was added to the mesocosms in two steps on day 11 and 12 after the enclosure of the mesocosms. As the mesocosms contain a specific volume (~54 m3), the process of adding the OMZ water started with first removing water from the mesocosms. The water removed (~20 m3) was pumped out from 11-12 m depth. A similar volume of OMZ water, from both collection sites, was then pumped into four replicate mesocosms each. The OMZ water was pumped into the mesocosms moving the input hose between 14-17 m depth. The water collected at 30 m depth was pumped into mesocosms M1, M4, M5 and M8 having a low OMZ signature and water from 70 m depth into mesocosms M2, M3, M6 and M7 having a very low OMZ signature. Due a halocline at 12 m depth (see below), the added OMZ water was not immediately mixed throughout the mesocosm bag. Sampling took place every second day over a period of 50 days, and all variables were taken with an integrated water sampler (HydroBios, IWS) pre-programed to fill from 0 – 10 m depth and all samples consisted of this integrated samples from the upper 10 m. The samples were stored dark in cool boxes and brought back to the laboratory and processed right away. Sampling took place in the morning, and the samples were usually back in the laboratory around noon. Measured variables included inorganic nutrients, dissolved organic nutrients, extracellular enzyme activity: leucine aminopeptidase (LAP) and alkaline phosphatase, and the phytoplankton and bacterial community composition.

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    Authors: Laine-Petäjäkangas, Anna Maria; Korrensalo, Aino; Kokkonen, Nicola A K; Tuittila, Eeva-Stiina;

    We measured the following vascular plant functional traits: plant height (cm), leaf size (LS, cm2), specific leaf area (SLA, cm2 g-1), leaf dry matter content (LDMC, mg g-1) and leaf moisture content (g g-1) from the most common species in each research unit. We measured the following Sphagnum traits: capitulum density (number of shoots cm-2), fascicle density (number cm-1), surface density (mg cm-3), capitulum dry mass (mg) and capitulum moisture content (cap_wc, g g-1). In addition, rate of net photosynthesis was measured at four light levels. The data was collected from Lakkasuo mire complex located in Southern Finland (61° 47' N; 24° 18' E). The study includes three sites called rich fen, poor fen, and bog. At each site two experimental units were established in 2000/2001: an undrained control unit and a Water level drawdown (WLD) unit that was surrounded by a 30 cm-deep ditches after a control year. Photosynthesis measurements were carried out during summer 2016, while other traits were sampled during August 2016. We measured vascular plant vegetative height (cm), leaf area (LA, cm2 leaf-1) with a leaf area scanner (LI-3000, LI-COR Inc.), leaf fresh mass and leaf dry mass after the sample was dried at 40 °C for at least 48h (mg leaf-1). Leaf dry matter content (LDMC mg g-1) was calculated from fresh and dry mass, while specific leaf area (SLA, cm2 g-1) was calculated from LA and dry mass. Leaf traits were measured from five replicate plants as an average of a sample of ten fully grown healthy leaves from each plant. Sphagnum moss traits were measured from five replicates of single-species samples. Each sample consisted of two parts: a volume-specific sample collected with a core (diameter 7 cm, area 38.5 cm2, height 3 cm) to maintain the natural density of the stand and an additional sample of ca. 10 individuals, with stems more than 5 cm at length. Before collecting the core in the field, the number of shoots was counted from a 4 × 4 cm square for capitulum density (cap_dens, number of shoots cm-2). The volume-specific sample was cleaned of litter and unwanted species before drying at 40 °C for at least 48h to determine the surface density (surf_dens, mg cm-3). The additional sample of ten moss individuals was divided into capitula and stems (4 cm below capitula). We counted the number of fascicles on the 4 cm stem segments (fasc_dens, number cm-1). The capitula were thoroughly moistened and placed on top of tissue paper for 2 minutes to drain, before weighing them for water-filled fresh mass (cap_fw, mg). The samples were dried at 60 °C for at least 48h to measure the capitulum dry masses (cap_dw, mg). The moisture contents of capitula (cap_mc, g g-1) were then calculated as the ratio of water-filled to dry mass. Height growth (mm growing season-1) was measured in the field with the modified cranked wire method (Clymo 1970) as a difference in height between the beginning (mid-May) and end (mid-October) of the growing season 2017. For both vascular plants and mosses, we measured net photosynthesis rate, with a fully controlled, flow-through gas-exchange fluorescence measurement systems (GFS-3000, Walz, Germany; LI6400, LI-COR, USA). For mosses the living apical parts (~0.5 to 1 cm) were harvested right before the measurement and placed on a custom-made cuvette. For vascular plants, leaves, or in the case of shrubs, segments of branches were enclosed within the cuvette without disturbing the connection to the rooting system. Net photosynthesis rate (A, µmol m-2 g-1 s-1) was measured at 1500, 250, 35, and 0 µmol m-2 s-1 photosynthetic photon flux density (PPFD). The cuvette conditions were kept constant (temperature 20°C, CO2 concentration 400 ppm, flow rate 500, impeller in level 5). Relative humidity (Rh) of incoming air was set to 40% for vascular plants and 60% for mosses; for mosses this setting retained the cuvette Rh at around 80%. The setting enabled mosses to remain moist to ensure photosynthesis but protected the device from excess moisture. The data was collected to find out the impact of long-term WLD on functional traits of vascular plants and mosses, and how this impact is modulated by nutrient status (rich fen, poor fen, bog). We first assess (i) how peatland species differ in their traits and their intraspecific trait variability, to quantify (ii) how WLD impacts community level traits at different peatland sites.

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    Authors: Elovaara, Samu; Eronen-Rasimus, Eeva; Asmala, Eero; Tamelander, Tobias; +1 Authors

    The data were collected from an experiment using phytoplankton cultures (Apocalathium malmogiense and Rhodomonas marina). The aim of the experiment was to study carbon cycling among phytoplankton and bacteria, and the effects on the dissolved organic matter (DOM) pool. Measured variables include phytoplankton and bacterial abundance, primary production, bacterial production and respiration, 14C-transfer from phytoplankton to DOM and bacteria, concentrations of particulate and dissolved organic carbon, nitrate, phosphate and chlorophyll a, and optical characteristics of dissolved organic matter. The experiment was conducted at Tvärminne Zoological Station, Hanko, Finland with non-axenic unialgal phytoplankton cultures and bacteria originating from the Baltic Sea. The experiment was conducted between Dec. 2017 and Apr. 2018. The experiment consisted of two parts, the DOM release experiment (part 1) and the DOM consumption experiment (part 2). Separate triplicate batch cultures of both phytoplankton species were grown for each experiment. In the DOM release experiment the cultures were grown for over 4 months and three day-long incubations (key point incubations, KPI's) were initiated on three occasions; the first KPI at early exponential growth phase and the second and third KPI's when the phytoplankton had grown more abundant. During each KPI and aliquot of the culture was inoculated with freshly collected sea water bacteria, and bacterial community composition was measured. This aliquot was then divided into two further aliquots; one was incubated with radioisotopes for productivity (primary and bacterial production) and 14C-flow analyses (production line) and one filtered through 0.8 µm for analysis of DOM optical properties. During the KPI's measurements were taken at 0, 4, 8 and 12 h. Nutrient concentrations (measured from non-filtered and 0.8 µm filtered samples) and concentration of dissolved organic carbon were measured only at 0 and 12 h. Concentrations of particulate organic carbon and nitrogen and chlorophyll a were measured only once for each KPI at the beginning of the incubation. In the DOM consumption experiments the cultures were grown to high abundance, after which the phytoplankton and most of the bacteria were filtered out. The filtrate was then inoculated with freshly collected sea water bacteria, after which it was incubated for 7 days. Bacterial abundance, production, respiration, and community composition, and concentration and optical properties of DOM were measured daily. The experimental design is explained in figure 1 of the associated publication.

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    Authors: Laine-Petäjäkangas, Anna Maria; Lindholm, Tapio; Nilsson, Mats; Kutznetsov, Oleg; +2 Authors

    We estimated plant community composition as the projection cover of each vascular plant and moss species. We measured the following vascular plant functional traits: plant height, leaf size (LS), specific leaf area (SLA) and leaf carbon (C) and nitrogen (N) contents from the most common species in each site. We measured the following Sphagnum traits: stand density (number of shoots cm-2), capitulum width (cap_width, mm) and dry weight (cap_dw, mg), fascicle density (number cm-1), capitulum dry matter content (CDMC, mg g-1), capitulum water content (cap_wc, g g-1) and capitulum C and N contents and C:N ratio. The data was collected from 47 northern peatlands located in land uplift regions in Finland, Sweden and Russia: Sävar on the west coast of Bothnian Bay (63o50'N, 20o40'E, Sweden), Siikajoki (64°45' N, 24°43', Finland) and Hailuoto island (65°07' N, 24°71' E, Finland) on the east coast of Bothnian Bay, and Belomorsk-Virma (63°90' N, 36°50' E, Russia) on the coast of the White Sea. The data was collected from the different areas as follows: Siikajoki sites were sampled in August 2016, Sävar sites at the end of June 2017, Hailuoto sites during July 2017 and Belomorsk sites at the end of August 2017. We determined the plant community composition by visually estimating the projection cover of each species separately for field (vascular plants) and moss layer using the scale 0.1%, 0.25%, 0.5%, 1%, 2%, 3%, etc. There were fifteen 50 x 50 cm plots in each peatland at Siikajoki and Belomorsk-Virma, and 10 at Sävar and Hailuoto. The sample plots were located five meters apart along a transect starting from the generally treeless peatland margin and heading towards the peatland center. Plant traits were measured as follows: To measure SLA (i.e., the one-sided area of a fresh leaf divided by its oven-dry mass, cm2 g-1), the freshly picked leaf or a sample of 3 leaves in case of shrubs with small leaves was pressed flat between a board and a glass and a standardized photo was taken. The leaf size (LS, cm2) was analysed from the photos with ImageJ. The leaf samples were stored in paper bags and dried at 60°C for a minimum of 48h. The dried samples were weighed, and SLA calculated. The SLA samples were used for carbon (C) and nitrogen (N) content analysis. Leaves from each species from each site were pooled into one sample, which was milled (Retsch MM301 mill) and analyzed for C and N concentrations and for C:N ration on a CHNS–O Elemental analyzer (EA1110) (University of Oulu). Sphagnum moss samples for trait measurements were collected with a corer (7 cm diameter, area 38 cm2, height at least 8 cm) to maintain the natural density of the stand. Stand density was measured as the number of mosses in the sample. From ten individuals we measured the width of the capitula and counted the number of fascicles from a five cm segment below capitulum. We separated the ten moss individuals into capitulum and stem (5 cm below capitula) wetted them and allowed to dry on top of tissue paper for 2 min before weighing them for water filled fresh weight. Samples were placed on paper bags and dried at 60 °C for at least 48h after which the dry mass of capitula and stems were measured. CDMC and cap_wc were calculated from the fresh and dry weight. We used the capitula samples for analyses of C and N concentrations and for C:N ratio, and treated them similarly to vascular plant samples. The data was collected to find out how functional diversity and trait composition of vascular plant and Sphagnum moss communities develops during peatland succession across land uplift regions.

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    Authors: Zweifel, Roman; Etzold, Sophia; Haeni, Matthias; Feichtinger, Linda; +6 Authors

    Within the setup of a long‐term irrigation experiment in a Scots pine (Pinus sylvestris) forest at Pfynwald in the inner-Alpine Swiss Rhone valley, ecophysiological data were recorded from permanently irrigated trees, from trees cut off the irrigation after 11 years, and non-treated control trees. The data sets include continuous stem radius changes (automated point dendrometer at breast height), tree stem sap flow (Granier-type sap flow sensors at breast height), air temperature and humidity, vapour pressure deficit, net solar radiation, precipitation (tipping bucket), and volumetric soil water content (TDR and HS-sensors). The meteorological data were measured 2 m above the canopy in about 13 m height on top of a scaffold. The soil water sensors covered soil depth of up to 80 cm. Data resolution is 1 hour or higher and covers the years 2011-2017. Data as used and published in Zweifel, et al. (2020), Determinants of legacy effects in pine trees ‐ implications from an irrigation‐stop experiment. New Phytol. doi:10.1111/nph.16582

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    Authors: Spilling, Kristian;

    In an enclosure experiment, we employed two levels of inorganic NP ratios (10 and 5) for three distinct plankton communities collected along the coast of central Chile (33ºS). Each combination of community and NP level was replicated three times. The experiment lasted 12 days, and the data set include inorganic nutrients (NO3, PO4, DSi), particular organic carbon (POC), nitrogen (PON) and phosphorus (POP), Chlorophyll a, a range of fluorescence based measurements such as photochemical efficiency (Fv/Fm) and community data. The primary effect of the NP treatment was related to different concentrations of NO3, which directly influenced the biomass of phytoplankton. Additionally, low inorganic NP ratio reduced the seston NP and Chl a-C ratios, and there were some effects on the plankton community composition, e.g. benefitting Synechococcus spp in some communities.

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    Authors: Barboza, Francisco Rafael; Kotta, Jonne; Weinberger, Florian; Jormalainen, Veijo; +14 Authors