Reading tea leaves worldwide: Decoupled drivers of initial litter decomposition mass-loss rate and stabilization.

The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large-scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass-loss rates and stabilization factors of plant-derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy-to-degrade components accumulate during early-stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass-loss rates and stabilization, notably in colder locations. Using TBI improved mass-loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early-stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models.

Carbon uptake in Eurasian boreal forests dominates the high-latitude net ecosystem carbon budget.

Arctic-boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic-boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003-2015) vegetation gross primary productivity (GPP), ecosystem respiration (Reco ), net ecosystem CO2 exchange (NEE; Reco - GPP), and terrestrial methane (CH4 ) emissions for the Arctic-boreal zone using a satellite data-driven process-model for northern ecosystems (TCFM-Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM-Arctic to obtain daily 1-km2 flux estimates and annual carbon budgets for the pan-Arctic-boreal region. Across the domain, the model indicated an overall average NEE sink of -850 Tg CO2 -C year-1 . Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH4 emissions from tundra and boreal wetlands (not accounting for aquatic CH4 ) were estimated at 35 Tg CH4 -C year-1 . Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high-latitude carbon status and also indicates a continued need for integrated site-to-regional assessments to monitor the vulnerability of these ecosystems to climate change.

Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales.

While wetlands are the largest natural source of methane (CH4 ) to the atmosphere, they represent a large source of uncertainty in the global CH4 budget due to the complex biogeochemical controls on CH4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH4 emissions.

Refining the role of phenology in regulating gross ecosystem productivity across European peatlands.

The role of plant phenology as a regulator for gross ecosystem productivity (GEP) in peatlands is empirically not well constrained. This is because proxies to track vegetation development with daily coverage at the ecosystem scale have only recently become available and the lack of such data has hampered the disentangling of biotic and abiotic effects. This study aimed at unraveling the mechanisms that regulate the seasonal variation in GEP across a network of eight European peatlands. Therefore, we described phenology with canopy greenness derived from digital repeat photography and disentangled the effects of radiation, temperature and phenology on GEP with commonality analysis and structural equation modeling. The resulting relational network could not only delineate direct effects but also accounted for possible effect combinations such as interdependencies (mediation) and interactions (moderation). We found that peatland GEP was controlled by the same mechanisms across all sites: phenology constituted a key predictor for the seasonal variation in GEP and further acted as a distinct mediator for temperature and radiation effects on GEP. In particular, the effect of air temperature on GEP was fully mediated through phenology, implying that direct temperature effects representing the thermoregulation of photosynthesis were negligible. The tight coupling between temperature, phenology and GEP applied especially to high latitude and high altitude peatlands and during phenological transition phases. Our study highlights the importance of phenological effects when evaluating the future response of peatland GEP to climate change. Climate change will affect peatland GEP especially through changing temperature patterns during plant phenologically sensitive phases in high latitude and high altitude regions.

Early snowmelt significantly enhances boreal springtime carbon uptake.

We determine the annual timing of spring recovery from space-borne microwave radiometer observations across northern hemisphere boreal evergreen forests for 1979-2014. We find a trend of advanced spring recovery of carbon uptake for this period, with a total average shift of 8.1 d (2.3 d/decade). We use this trend to estimate the corresponding changes in gross primary production (GPP) by applying in situ carbon flux observations. Micrometeorological CO2 measurements at four sites in northern Europe and North America indicate that such an advance in spring recovery would have increased the January-June GPP sum by 29 g⋅C⋅m-2 [8.4 g⋅C⋅m-2 (3.7%)/decade]. We find this sensitivity of the measured springtime GPP to the spring recovery to be in accordance with the corresponding sensitivity derived from simulations with a land ecosystem model coupled to a global circulation model. The model-predicted increase in springtime cumulative GPP was 0.035 Pg/decade [15.5 g⋅C⋅m-2 (6.8%)/decade] for Eurasian forests and 0.017 Pg/decade for forests in North America [9.8 g⋅C⋅m-2 (4.4%)/decade]. This change in the springtime sum of GPP related to the timing of spring snowmelt is quantified here for boreal evergreen forests.

The uncertain climate footprint of wetlands under human pressure.

Significant climate risks are associated with a positive carbon-temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the "cost" of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse-response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange.

Warming of subarctic tundra increases emissions of all three important greenhouse gases - carbon dioxide, methane, and nitrous oxide.

Rapidly rising temperatures in the Arctic might cause a greater release of greenhouse gases (GHGs) to the atmosphere. To study the effect of warming on GHG dynamics, we deployed open-top chambers in a subarctic tundra site in Northeast European Russia. We determined carbon dioxide (CO2 ), methane (CH4 ), and nitrous oxide (N2 O) fluxes as well as the concentration of those gases, inorganic nitrogen (N) and dissolved organic carbon (DOC) along the soil profile. Studied tundra surfaces ranged from mineral to organic soils and from vegetated to unvegetated areas. As a result of air warming, the seasonal GHG budget of the vegetated tundra surfaces shifted from a GHG sink of -300 to -198 g CO2 -eq m-2 to a source of 105 to 144 g CO2 -eq m-2 . At bare peat surfaces, we observed increased release of all three GHGs. While the positive warming response was dominated by CO2 , we provide here the first in situ evidence of increasing N2 O emissions from tundra soils with warming. Warming promoted N2 O release not only from bare peat, previously identified as a strong N2 O source, but also from the abundant, vegetated peat surfaces that do not emit N2 O under present climate. At these surfaces, elevated temperatures had an adverse effect on plant growth, resulting in lower plant N uptake and, consequently, better N availability for soil microbes. Although the warming was limited to the soil surface and did not alter thaw depth, it increased concentrations of DOC, CO2, and CH4 in the soil down to the permafrost table. This can be attributed to downward DOC leaching, fueling microbial activity at depth. Taken together, our results emphasize the tight linkages between plant and soil processes, and different soil layers, which need to be taken into account when predicting the climate change feedback of the Arctic.

Do the energy fluxes and surface conductance of boreal coniferous forests in Europe scale with leaf area?

Earth observing systems are now routinely used to infer leaf area index (LAI) given its significance in spatial aggregation of land surface fluxes. Whether LAI is an appropriate scaling parameter for daytime growing season energy budget, surface conductance (Gs ), water- and light-use efficiency and surface-atmosphere coupling of European boreal coniferous forests was explored using eddy-covariance (EC) energy and CO2 fluxes. The observed scaling relations were then explained using a biophysical multilayer soil-vegetation-atmosphere transfer model as well as by a bulk Gs representation. The LAI variations significantly alter radiation regime, within-canopy microclimate, sink/source distributions of CO2 , H2 O and heat, and forest floor fluxes. The contribution of forest floor to ecosystem-scale energy exchange is shown to decrease asymptotically with increased LAI, as expected. Compared with other energy budget components, dry-canopy evapotranspiration (ET) was reasonably 'conservative' over the studied LAI range 0.5-7.0 m2 m-2 . Both ET and Gs experienced a minimum in the LAI range 1-2 m2 m-2 caused by opposing nonproportional response of stomatally controlled transpiration and 'free' forest floor evaporation to changes in canopy density. The young forests had strongest coupling with the atmosphere while stomatal control of energy partitioning was strongest in relatively sparse (LAI ~2 m2 m-2 ) pine stands growing on mineral soils. The data analysis and model results suggest that LAI may be an effective scaling parameter for net radiation and its partitioning but only in sparse stands (LAI <3 m2 m-2 ). This finding emphasizes the significance of stand-replacing disturbances on the controls of surface energy exchange. In denser forests, any LAI dependency varies with physiological traits such as light-saturated water-use efficiency. The results suggest that incorporating species traits and site conditions are necessary when LAI is used in upscaling energy exchanges of boreal coniferous forests.

Latent heat exchange in the boreal and arctic biomes.

In this study latent heat flux (λE) measurements made at 65 boreal and arctic eddy-covariance (EC) sites were analyses by using the Penman-Monteith equation. Sites were stratified into nine different ecosystem types: harvested and burnt forest areas, pine forests, spruce or fir forests, Douglas-fir forests, broadleaf deciduous forests, larch forests, wetlands, tundra and natural grasslands. The Penman-Monteith equation was calibrated with variable surface resistances against half-hourly eddy-covariance data and clear differences between ecosystem types were observed. Based on the modeled behavior of surface and aerodynamic resistances, surface resistance tightly control λE in most mature forests, while it had less importance in ecosystems having shorter vegetation like young or recently harvested forests, grasslands, wetlands and tundra. The parameters of the Penman-Monteith equation were clearly different for winter and summer conditions, indicating that phenological effects on surface resistance are important. We also compared the simulated λE of different ecosystem types under meteorological conditions at one site. Values of λE varied between 15% and 38% of the net radiation in the simulations with mean ecosystem parameters. In general, the simulations suggest that λE is higher from forested ecosystems than from grasslands, wetlands or tundra-type ecosystems. Forests showed usually a tighter stomatal control of λE as indicated by a pronounced sensitivity of surface resistance to atmospheric vapor pressure deficit. Nevertheless, the surface resistance of forests was lower than for open vegetation types including wetlands. Tundra and wetlands had higher surface resistances, which were less sensitive to vapor pressure deficits. The results indicate that the variation in surface resistance within and between different vegetation types might play a significant role in energy exchange between terrestrial ecosystems and atmosphere. These results suggest the need to take into account vegetation type and phenology in energy exchange modeling.

The Arctic Plant Aboveground Biomass Synthesis Dataset.

Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m-2) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic.

A widely-used eddy covariance gap-filling method creates systematic bias in carbon balance estimates.

Climate change mitigation requires, besides reductions in greenhouse gas emissions, actions to increase carbon sinks in terrestrial ecosystems. A key measurement method for quantifying such sinks and calibrating models is the eddy covariance technique, but it requires imputation, or gap-filling, of missing data for determination of annual carbon balances of ecosystems. Previous comparisons of gap-filling methods have concluded that commonly used methods, such as marginal distribution sampling (MDS), do not have a significant impact on the carbon balance estimate. By analyzing an extensive, global data set, we show that MDS causes significant carbon balance errors for northern (latitude [Formula: see text]) sites. MDS systematically overestimates the carbon dioxide (CO[Formula: see text]) emissions of carbon sources and underestimates the CO[Formula: see text] sequestration of carbon sinks. We also reveal reasons for these biases and show how a machine learning method called extreme gradient boosting or a modified implementation of MDS can be used to substantially reduce the northern site bias.

Monitoring the multi-year carbon balance of a subarctic palsa mire with micrometeorological techniques.

This article reports a dataset on 8 years of monitoring carbon fluxes in a subarctic palsa mire based on micrometeorological eddy covariance measurements. The mire is a complex with wet minerotrophic areas and elevated dry palsa as well as intermediate sub-ecosystems. The measurements document primarily the emission originating from the wet parts of the mire dominated by a rather homogenous cover of Eriophorum angustifolium. The CO(2)/CH(4) flux measurements performed during the years 2001-2008 showed that the areas represented in the measurements were a relatively stable sink of carbon with an average annual rate of uptake amounting to on average -46 g C m(-2) y(-1) including an equally stable loss through CH(4) emissions (18-22 g CH(4)-C m(-2) y(-1)). This consistent carbon sink combined with substantial CH(4) emissions is most likely what is to be expected as the permafrost under palsa mires degrades in response to climate warming.

Substantial hysteresis in emergent temperature sensitivity of global wetland CH4 emissions.

Wetland methane (CH4) emissions ([Formula: see text]) are important in global carbon budgets and climate change assessments. Currently, [Formula: see text] projections rely on prescribed static temperature sensitivity that varies among biogeochemical models. Meta-analyses have proposed a consistent [Formula: see text] temperature dependence across spatial scales for use in models; however, site-level studies demonstrate that [Formula: see text] are often controlled by factors beyond temperature. Here, we evaluate the relationship between [Formula: see text] and temperature using observations from the FLUXNET-CH4 database. Measurements collected across the globe show substantial seasonal hysteresis between [Formula: see text] and temperature, suggesting larger [Formula: see text] sensitivity to temperature later in the frost-free season (about 77% of site-years). Results derived from a machine-learning model and several regression models highlight the importance of representing the large spatial and temporal variability within site-years and ecosystem types. Mechanistic advancements in biogeochemical model parameterization and detailed measurements in factors modulating CH4 production are thus needed to improve global CH4 budget assessments.

Modeling acclimation of photosynthesis to temperature in evergreen conifer forests.

• In this study, we used a canopy photosynthesis model which describes changes in photosynthetic capacity with slow temperature-dependent acclimations. • A flux-partitioning algorithm was applied to fit the photosynthesis model to net ecosystem exchange data for 12 evergreen coniferous forests from northern temperate and boreal regions. • The model accounted for much of the variation in photosynthetic production, with modeling efficiencies (mean > 67%) similar to those of more complex models. The parameter describing the rate of acclimation was larger at the northern sites, leading to a slower acclimation of photosynthesis to temperature. The response of the rates of photosynthesis to air temperature in spring was delayed up to several days at the coldest sites. Overall photosynthesis acclimation processes were slower at colder, northern locations than at warmer, more southern, and more maritime sites. • Consequently, slow changes in photosynthetic capacity were essential to explaining variations of photosynthesis for colder boreal forests (i.e. where acclimation of photosynthesis to temperature was slower), whereas the importance of these processes was minor in warmer conifer evergreen forests.

Insect herbivory dampens Subarctic birch forest C sink response to warming.

Climate warming is anticipated to make high latitude ecosystems stronger C sinks through increasing plant production. This effect might, however, be dampened by insect herbivores whose damage to plants at their background, non-outbreak densities may more than double under climate warming. Here, using an open-air warming experiment among Subarctic birch forest field layer vegetation, supplemented with birch plantlets, we show that a 2.3 °C air and 1.2 °C soil temperature increase can advance the growing season by 1-4 days, enhance soil N availability, leaf chlorophyll concentrations and plant growth up to 400%, 160% and 50% respectively, and lead up to 122% greater ecosystem CO2 uptake potential. However, comparable positive effects are also found when insect herbivory is reduced, and the effect of warming on C sink potential is intensified under reduced herbivory. Our results confirm the expected warming-induced increase in high latitude plant growth and CO2 uptake, but also reveal that herbivorous insects may significantly dampen the strengthening of the CO2 sink under climate warming.

Effects of drought and meteorological forcing on carbon and water fluxes in Nordic forests during the dry summer of 2018.

The Nordic region was subjected to severe drought in 2018 with a particularly long-lasting and large soil water deficit in Denmark, Southern Sweden and Estonia. Here, we analyse the impact of the drought on carbon and water fluxes in 11 forest ecosystems of different composition: spruce, pine, mixed and deciduous. We assess the impact of drought on fluxes by estimating the difference (anomaly) between year 2018 and a reference year without drought. Unexpectedly, the evaporation was only slightly reduced during 2018 compared to the reference year at two sites while it increased or was nearly unchanged at all other sites. This occurred under a 40 to 60% reduction in mean surface conductance and the concurrent increase in evaporative demand due to the warm and dry weather. The anomaly in the net ecosystem productivity (NEP) was 93% explained by a multilinear regression with the anomaly in heterotrophic respiration and the relative precipitation deficit as independent variables. Most of the variation (77%) was explained by the heterotrophic component. Six out of 11 forests reduced their annual NEP with more than 50 g C m-2 yr-1 during 2018 as compared to the reference year. The NEP anomaly ranged between -389 and +74 g C m-2 yr-1 with a median value of -59 g C m-2 yr-1. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Importance of vegetation classes in modeling CH4 emissions from boreal and subarctic wetlands in Finland.

Boreal/arctic wetlands are dominated by diverse plant species, which vary in their contribution to CH4 production, oxidation and transport processes. Earlier studies have often lumped the processes all together, which may induce large uncertainties into the results. We present a novel model, which includes three vegetation classes and can be used to simulate CH4 emissions from boreal and arctic treeless wetlands. The model is based on an earlier biogeophysical model, CH4MODwetland. We grouped the vegetation as graminoids, shrubs and Sphagnum and recalibrated the vegetation parameters according to their different CH4 production, oxidation and transport capacities. Then, we used eddy-covariance-based CH4 flux observations from a boreal (Siikaneva) and a subarctic fen (Lompolojänkkä) in Finland to validate the model. The results showed that the recalibrated model could generally simulate the seasonal patterns of the Finnish wetlands with different plant communities. The comparison between the simulated and measured daily CH4 fluxes resulted in a correlation coefficient (R2) of 0.82 with a slope of 1.0 and an intercept of -0.1mgm-2h-1 for the Siikaneva site (n=2249, p<0.001) and an R2 of 0.82 with a slope of 1.0 and an intercept of 0.0mgm-2h-1 for the Lompolojänkkä site (n=1826, p<0.001). Compared with the original model, the recalibrated model in this study significantly improved the model efficiency (EF), from -5.5 to 0.8 at the Siikaneva site and from -0.4 to 0.8 at the Lompolojänkkä site. The simulated annual CH4 emissions ranged from 7 to 24gm-2yr-1, which was consistent with the observations (7-22gm-2yr-1). However, there are some discrepancies between the simulated and observed daily CH4 fluxes for the Siikaneva site (RMSE=50.0%) and the Lompolojänkkä site (RMSE=47.9%). Model sensitivity analysis showed that increasing the proportion of the graminoids would significantly increase the CH4 emission levels. Our study demonstrated that the parameterization of the different vegetation processes was important in estimating long-term wetland CH4 emissions.