ALBERT

Description: 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.

Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Geoscientific Model Development 11 (2018): 497-519, doi:10.5194/gmd-11-497-2018.

Description: Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 =  0.76; Nash–Sutcliffe modeling efficiency, MEF  =  0.76) and ecosystem respiration (ER, r2 =  0.78, MEF  =  0.75), with lesser accuracy for latent heat fluxes (LE, r2 =  0.42, MEF  =  0.14) and and net ecosystem CO2 exchange (NEE, r2 =  0.38, MEF  =  0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 〈 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.

Description: This study was supported by the European Research Council Synergy grant ERC-2013-SyG- 610028 IMBALANCE-P.

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

Description: The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high.