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Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

The Arctic–boreal zone (ABZ) is experiencing amplified warming, actively changing biogeochemical cycling of vegetation and soils. The land-to-atmosphere fluxes of CO2 in the ABZ have the potential to increase in magnitude and feedback to the climate causing additional large-scale warming. The ability to model and predict this vulnerability is critical to preparation for a warming world, but Earth system models have biases that may hinder understanding of the rapidly changing ABZ carbon fluxes. Here we investigate circumpolar carbon cycling represented by the Community Land Model 5 (CLM5.0) with a focus on seasonal gross primary productivity (GPP) in plant functional types (PFTs). We benchmark model results using data from satellite remote sensing products and eddy covariance towers. We find consistent biases in CLM5.0 relative to observational constraints: (1) the onset of deciduous plant productivity to be late; (2) the offset of productivity to lag and remain abnormally high for all PFTs in fall; (3) a high bias of grass, shrub, and needleleaf evergreen tree productivity; and (4) an underestimation of productivity of deciduous trees. Based on these biases, we focus on model development of alternate phenology, photosynthesis schemes, and carbon allocation parameters at eddy covariance tower sites. Although our improvements are focused on productivity, our final model recommendation results in other component CO2 fluxes, e.g., net ecosystem exchange (NEE) and terrestrial ecosystem respiration (TER), that are more consistent with observations. Results suggest that algorithms developed for lower latitudes and more temperate environments can be inaccurate when extrapolated to the ABZ, and that many land surface models may not accurately represent carbon cycling and its recent rapid changes in high-latitude ecosystems, especially when analyzed by individual PFTs.

The contribution of soil heterotrophic respiration to the boreal–Arctic carbon (CO2) cycle and its potential feedback to climate change remains poorly quantified. We developed a remote-sensing-driven permafrost carbon model at intermediate scale (∼1 km) to investigate how environmental factors affect the magnitude and seasonality of soil heterotrophic respiration in Alaska. The permafrost carbon model simulates snow and soil thermal dynamics and accounts for vertical soil carbon transport and decomposition at depths up to 3 m below the surface. Model outputs include soil temperature profiles and carbon fluxes at 1 km resolution spanning the recent satellite era (2001–2017) across Alaska. Comparisons with eddy covariance tower measurements show that the model captures the seasonality of carbon fluxes, with favorable accuracy in simulating net ecosystem CO2 exchange (NEE) for both tundra (R>0.8, root mean square error (RMSE – 0.34 g C m−2 d−1), and boreal forest (R>0.73; RMSE – 0.51 g C m−2 d−1). Benchmark assessments using two regional in situ data sets indicate that the model captures the complex influence of snow insulation on soil temperature and the temperature sensitivity of cold-season soil heterotrophic respiration. Across Alaska, we find that seasonal snow cover imposes strong controls on the contribution from different soil depths to total soil heterotrophic respiration. Earlier snowmelt in spring promotes deeper soil warming and enhances the contribution of deeper soils to total soil heterotrophic respiration during the later growing season, thereby reducing net ecosystem carbon uptake. Early cold-season soil heterotrophic respiration is closely linked to the number of snow-free days after the land surface freezes (R=-0.48, p), i.e., the delay in snow onset relative to surface freeze onset. Recent trends toward earlier autumn snow onset in northern Alaska promote a longer zero-curtain period and enhanced cold-season respiration. In contrast, southwestern Alaska shows a strong reduction in the number of snow-free days after land surface freeze onset, leading to earlier soil freezing and a large reduction in cold-season soil heterotrophic respiration. Our results also show nonnegligible influences of subgrid variability in surface conditions on the model-simulated CO2 seasonal cycle, especially during the early cold season at 10 km scale. Our results demonstrate the critical role of snow cover affecting the seasonality of soil temperature and respiration and highlight the challenges of incorporating these complex processes into future projections of the boreal–Arctic carbon cycle.

Cold seasons in Arctic ecosystems are increasingly important to the annual carbon balance of these vulnerable ecosystems. Arctic winters are largely harsh and inaccessible leading historic data gaps during that time. Until recently, cold seasons have been assumed to have negligible impacts on the annual carbon balance but as data coverage increases and the Arctic warms, the cold season has been shown to account for over half of annual methane (CH4 ) emissions and can offset summer photosynthetic carbon dioxide (CO2 ) uptake. Freeze-thaw cycle dynamics play a critical role in controlling cold season CO2 and CH4 loss, but the relationship has not been extensively studied. Here, we analyze freeze-thaw processes through in situ CO2 and CH4 fluxes in conjunction with soil cores for physical structure and porewater samples for redox biogeochemistry. We find a movement of water toward freezing fronts in soil cores, leaving air spaces in soils, which allows for rapid infiltration of oxygen-rich snow melt in spring as shown by oxidized iron in porewater. The snow melt period coincides with rising ecosystem respiration and can offset up to 41% of the summer CO2 uptake. Our study highlights this important seasonal process and shows spring greenhouse gas emissions are largely due to production from respiration instead of only bursts of stored gases. Further warming is projected to result in increases of snowpack and deeper thaws, which could increase this ecosystem respiration dominate snow melt period causing larger greenhouse gas losses during spring.

The ongoing disproportionate increases in temperature and precipitation over the Arctic region may greatly alter the latitudinal gradients in greenup and snowmelt timings as well as associated carbon dynamics of tundra ecosystems. Here we use remotely-sensed and ground-based datasets and model results embedding snowmelt timing in phenology at seven tundra flux tower sites in Alaska during 2001–2018, showing that the carbon response to early greenup or delayed snowmelt varies greatly depending upon local climatic limits. Increases in net ecosystem productivity (NEP) due to early greenup were amplified at the higher latitudes where temperature and water strongly colimit vegetation growth, while NEP decreases due to delayed snowmelt were alleviated by a relief of water stress. Given the high likelihood of more frequent delayed snowmelt at higher latitudes, this study highlights the importance of understanding the role of snowmelt timing in vegetation growth and terrestrial carbon cycles across warming Arctic ecosystems., The ongoing disproportionate increases in temperature and precipitation in the Alaska may alter the latitudinal gradients in greenup and snowmelt timings as well as carbon dynamics. With a broad range of datasets and model results, the authors show that the carbon response to early greenup or delayed snowmelt varies greatly depending upon local climatic limits.

Methane (CH$_{4}$) emissions from natural landscapes constitute roughly half of global CH$_{4}$ contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH$_{4}$ flux are ideal for constraining ecosystem-scale CH$_{4}$ emissions due to quasi-continuous and high-temporal-resolution CH$_{4}$ flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH$_{4}$ Version 1.0, the first open-source global dataset of CH$_{4}$ EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH$_{4}$ fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH$_{4}$ representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH$_{4}$ Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH$_{4}$ emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH$_{4}$ fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH$_{4}$ emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20° S to 20° N) the spring onset of elevated CH$_{4}$ emissions starts 3 d earlier, and the CH$_{4}$ emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH$_{4}$ emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH$_{4}$ emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH$_{4}$ emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH$_{4}$ emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH$_{4}$ modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH$_{4}$ peak). FLUXNET-CH$_{4}$ is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH$_{4}$ cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH$_{4}$ data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use.

Satellite monitoring of plant phenology in tundra and grassland ecosystems using conventional vegetation indices (VIs), such as the normalized difference vegetation index (NDVI), can be biased by effects of snow. Snow-free VIs that take advantage of the shortwave infrared (SWIR) band have been proposed to overcome this problem, viz., the phenology index (PI) and the normalized difference phenology index (NDPI). However, the PI cannot properly capture the presence of sparse vegetation, and the NDPI does not account for the influence of dry vegetation. Here, we propose a novel snow-free VI, designated the normalized difference greenness index (NDGI), that uses reflectance in the green, red, and near-infrared (NIR) bands. The NDGI is a semi-analytical index based on a linear spectral mixture model and the spectral characteristics of vegetation, snow, soil, and dry grass. Its performance at estimating the start and end of the growing season (SOS and EOS) was evaluated using simulation datasets, time-lapse camera data at tundra sites, and flux tower gross primary production (GPP) data at grassland sites. Simulation results demonstrated that the NDGI can exclude the influence of snow on estimates of SOS and EOS. At the tundra sites, the NDGI markedly outperformed the NDVI, PI, NDPI, NIRv (near-infrared reflectance of vegetation), EVI2 (two-band enhanced vegetation index), PPI (plant phenology index), and DVI+ (difference vegetation index plus) for SOS estimation, with a root mean square error (RMSE) of 6.5 days and a Bias of −1.3 days, and for EOS estimation, with an RMSE of 8.3 days and a Bias of 0.11 days. At the grassland sites, the NDGI also outperformed the other VIs at SOS estimation, with an RMSE of 10.3 days and a Bias of −4.9 days. Although its performance was poorer at monitoring EOS than SOS at grassland (GPP) sites, its performance was comparable to that of the PI and superior to that of the other VIs at estimating EOS. These results indicate the potential of the NDGI for operational monitoring of plant phenology in tundra and grassland ecosystems based on satellite observations.

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.

Arctic tundra exhibits large landscape heterogeneity in microtopography, hydrology, and active layer depth. While many carbon flux measurements and experiments are done at or below the mesoscale (≤1 km), modern ecosystem carbon modeling is often done at scales of 0.25°–1.0° latitude, creating a mismatch between processes, process input data, and verification data. Here we arrange the naturally complex terrain into mesoscale landscape types of varying microtopography and moisture status to evaluate how landscape types differ in terms of CO2 and CH4 balances and their combined warming potential, expressed as CO2 equivalents (CO2-eq). Using a continuous 4 year dataset of CO2 and CH4 fluxes obtained from three eddy covariance (EC) towers, we investigate the integrated dynamics of landscape type, vegetation community, moisture regime, and season on net CO2 and CH4 fluxes. EC towers were situated across a moisture gradient including a moist upland tundra, a heterogeneous polygon tundra, and an inundated drained lake basin. We show that seasonal shifts in carbon emissions buffer annual carbon budget differences caused by site variability. Of note, high growing season gross primary productivity leads to higher fall zero-curtain CO2 emissions, reducing both variability in annual budgets and carbon sink strength of more productive sites. Alternatively, fall zero-curtain CH4 emissions are equal across landscape types, indicating site variation has little effect on CH4 emissions during the fall despite large differences during the growing season. We find that the polygon site has the largest mean warming potential (107 ± 8.63 g C–CO2-eq m−2 yr−1) followed by the drained lake basin site (82.12 ± 9.85 g C–CO2-eq m−2 yr−1) and the upland site (77.19 ± 21.8 g C–CO2-eq m−2 yr−1), albeit differences were not significant. The highest temperature sensitivities are also at the polygon site with mixed results between CO2 and CH4 at the other sites. Results show a similar mean annual net warming effect across dominant landscape types but that these landscape types vary significantly in the amounts and timing of CO2 and CH4 fluxes.

Energy, water, and greenhouse gas exchange in the permafrost zone play an important role in the regional and global climate system at multiple temporal and spatial scales. High-latitude warming in recent years has substantially altered ecosystem function, including biosphere–atmosphere interaction, which may amplify or dampen future high-latitude warming through a variety of feedback processes. In this chapter, we have reviewed the current state of energy, water, CO2, and CH4 exchange at the northern high-latitude permafrost zone, with synthesizing observed micrometeorological fluxes. Tundra has a higher summer and winter albedo with a longer snow period than boreal forests, resulting in that tundra less transfers sensible and latent energy to the atmosphere. Growing season length determines the spatial variability of the annual gross primary productivity and net growing season CO2 sink. In contrast, interannual variabilities of the annual CO2 budget at boreal forests are determined by ecosystem respiration, indicating an importance of ecosystem respiration in the boreal forests. The CO2 fertilization effect could be an important determinant of the long-term greenhouse gas budget at sites with a near neutral CO2 budget. In terms of annual greenhouse gas budget, CH4 emission is more important than CO2 budget for both boreal forest and Arctic wet tundra. Based on this synthesis, finally, we discuss future possible directions of study to reach a better understanding of changing high-latitude ecosystems, by synthesizing tower flux measurements in Alaska and Siberia and combining these in situ measurements with remote sensing data.

Author(s): Wang, Y; Yuan, F; Yuan, F; Gu, B; Hahn, MS; Torn, MS; Ricciuto, DM; Kumar, J; He, L; Zona, D; Lipson, DA; Wagner, R; Oechel, WC; Wullschleger, SD; Thornton, PE; Xu, X | Abstract: Spatial heterogeneities in soil hydrology have been confirmed as a key control on CO2 and CH4 fluxes in the Arctic tundra ecosystem. In this study, we applied a mechanistic ecosystem model, CLM-Microbe, to examine the microtopographic impacts on CO2 and CH4 fluxes across seven landscape types in Utqiaġvik, Alaska: trough, low-centered polygon (LCP) center, LCP transition, LCP rim, high-centered polygon (HCP) center, HCP transition, and HCP rim. We first validated the CLM-Microbe model against static-chamber measured CO2 and CH4 fluxes in 2013 for three landscape types: trough, LCP center, and LCP rim. Model application showed that low-elevation and thus wetter landscape types (i.e., trough, transitions, and LCP center) had larger CH4 emissions rates with greater seasonal variations than high-elevation and drier landscape types (rims and HCP center). Sensitivity analysis indicated that substrate availability for methanogenesis (acetate, CO2n+nH2) is the most important factor determining CH4 emission, and vegetation physiological properties largely affect the net ecosystem carbon exchange and ecosystem respiration in Arctic tundra ecosystems. Modeled CH4 emissions for different microtopographic features were upscaled to the eddy covariance (EC) domain with an area-weighted approach before validation against EC-measured CH4 fluxes. The model underestimated the EC-measured CH4 flux by 20% and 25% at daily and hourly time steps, suggesting the importance of the time step in reporting CH4 flux. The strong microtopographic impacts on CO2 and CH4 fluxes call for a model-data integration framework for better understanding and predicting carbon flux in the highly heterogeneous Arctic landscape.

Recent warming in the Arctic, which has been amplified during the winter1–3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)4. However, the amount of CO2 released in winter is not known and has not been well represented by ecosystem models or empirically based estimates5,6. Here we synthesize regional in situ observations of CO2 flux from Arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1,662 TgC per year from the permafrost region during the winter season (October–April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (−1,032 TgC per year). Extending model predictions to warmer conditions up to 2100 indicates that winter CO2 emissions will increase 17% under a moderate mitigation scenario—Representative Concentration Pathway 4.5—and 41% under business-as-usual emissions scenario—Representative Concentration Pathway 8.5. Our results provide a baseline for winter CO2 emissions from northern terrestrial regions and indicate that enhanced soil CO2 loss due to winter warming may offset growing season carbon uptake under future climatic conditions. Winter warming in the Arctic will increase the CO2 flux from soils. A pan-Arctic analysis shows a current loss of 1,662 TgC per year over the winter, exceeding estimated carbon uptake in the growing season; projections suggest a 17% increase under RCP 4.5 and a 41% increase under RCP 8.5 by 2100.

The springtime transition to regional-scale onset of photosynthesis and net ecosystem carbon uptake in boreal and tundra ecosystems are linked to the soil freeze-thaw state. We present evidence from diagnostic and inversion models constrained by satellite fluorescence and airborne CO2 from 2012 to 2014 indicating the timing and magnitude of spring carbon uptake in Alaska correlates with landscape thaw and ecoregion. Landscape thaw in boreal forests typically occurs in late April (DOY 111 ± 7) with a 29 ± 6 day lag until photosynthetic onset. North Slope tundra thaws 3 weeks later (DOY 133 ± 5) but experiences only a 20 ± 5 day lag until photosynthetic onset. These time lag differences reflect efficient cold season adaptation in tundra shrub and the longer dehardening period for boreal evergreens. Despite the short transition from thaw to photosynthetic onset in tundra, synchrony of tundra respiration with snow melt and landscape thaw delays the transition from net carbon loss (at photosynthetic onset) to net uptake by 13 ± 7 days, thus reducing the tundra net carbon uptake period. Two global CO2 inversions using a CASA-GFED model prior estimate earlier northern high latitude net carbon uptake compared to our regional inversion, which we attribute to (i) early photosynthetic-onset model prior bias, (ii) inverse method (scaling factor + optimization window), and (iii) sparsity of available Alaskan CO2 observations. Another global inversion with zero prior estimates the same timing for net carbon uptake as the regional model but smaller seasonal amplitude. The analysis of Alaskan eddy covariance observations confirms regional scale findings for tundra, but indicates that photosynthesis and net carbon uptake occur up to 1 month earlier in evergreens than captured by models or CO2 inversions, with better correlation to above-freezing air temperature than date of primary thaw. Further collection and analysis of boreal evergreen species over multiple years and at additional subarctic flux towers are critically needed.

A central challenge to understanding how climate anomalies, such as drought and heatwaves, impact the terrestrial carbon cycle, is quantification and scaling of spatial and temporal variation in ecosystem gross primary productivity (GPP). Existing empirical and model-based satellite broadband spectra-based products have been shown to miss critical variation in GPP. Here, we evaluate the potential of high spectral resolution (10 nm) shortwave (400-2,500 nm) imagery to better detect spatial and temporal variations in GPP across a range of ecosystems, including forests, grassland-savannas, wetlands, and shrublands in a water-stressed region. Estimates of GPP from eddy covariance observations were compared against airborne hyperspectral imagery, collected across California during the 2013-2014 HyspIRI airborne preparatory campaign. Observations from 19 flux towers across 23 flight campaigns (102 total image-flux tower pairs) showed GPP to be strongly correlated to a suite of spectral wavelengths and band ratios associated with foliar physiology and chemistry. A partial least squares regression (PLSR) modeling approach was then used to predict GPP with higher validation accuracy (adjusted R2 = 0.71) and low bias (0.04) compared to existing broadband approaches (e.g., adjusted R2 = 0.68 and bias = -5.71 with the Sims et al. model). Significant wavelengths contributing to the PLSR include those previously shown to coincide with Rubisco (wavelengths 1,680, 1,740, and 2,290 nm) and Vcmax (wavelengths 1,680, 1,722, 1,732, 1,760, and 2,300 nm). These results provide strong evidence that advances in satellite spectral resolution offer significant promise for improved satellite-based monitoring of GPP variability across a diverse range of terrestrial ecosystems.

Global-scale studies suggest that dryland ecosystems dominate an increasing trend in the magnitude and interannual variability of the land CO2 sink. However, such analyses are poorly constrained by measured CO2 exchange in drylands. Here we address this observation gap with eddy covariance data from 25 sites in the water-limited Southwest region of North America with observed ranges in annual precipitation of 100-1000 mm, annual temperatures of 2-25°C, and records of 3-10 years (150 site-years in total). Annual fluxes were integrated using site-specific ecohydrologic years to group precipitation with resulting ecosystem exchanges. We found a wide range of carbon sink/source function, with mean annual net ecosystem production (NEP) varying from -350 to +330 gCm-2 across sites with diverse vegetation types, contrasting with the more constant sink typically measured in mesic ecosystems. In this region, only forest-dominated sites were consistent carbon sinks. Interannual variability of NEP, gross ecosystem production (GEP), and ecosystem respiration (Reco ) was larger than for mesic regions, and half the sites switched between functioning as C sinks/C sources in wet/dry years. The sites demonstrated coherent responses of GEP and NEP to anomalies in annual evapotranspiration (ET), used here as a proxy for annually available water after hydrologic losses. Notably, GEP and Reco were negatively related to temperature, both interannually within site and spatially across sites, in contrast to positive temperature effects commonly reported for mesic ecosystems. Models based on MODIS satellite observations matched the cross-site spatial pattern in mean annual GEP but consistently underestimated mean annual ET by ~50%. Importantly, the MODIS-based models captured only 20-30% of interannual variation magnitude. These results suggest the contribution of this dryland region to variability of regional to global CO2 exchange may be up to 3-5 times larger than current estimates.

The maximum exergy dissipation theory provides a theoretical basis for using surface temperature to measure the status and development of ecosystems, which could provide an early warning of rapid evaluation of ecosystem degradation. In the present study, we used the radiation balance of ecosystems to demonstrate this hypothesis theoretically. Further, we used empirical data to verify whether ecosystems gain more radiation, while lowering their surface temperatures, as they develop naturally. We analyzed 12 chronosequences from the FLUXNET database using meteorological data and heat fluxes. We included age, disturbance, and successional chronosequences across six climate zones. Net radiation (R n) and the ratio of net radiation to global radiation (R n/R g) were used to measure the energy gain of the ecosystems. The maximum daily air temperature above the canopy (T max) and thermal response number (TRN) were used to analyze the surface temperature trends with ecosystem natural development. The general trends of T max, TRN, R n, and R n /R g demonstrated that ecosystems become cooler and more stable, yet gain more energy, throughout their natural development. Among the four indicators, TRN showed the most consistent trends and highest sensitivity to ecosystem growth, succession, and recovery. Moreover, TRN was not significantly influenced by precipitation or wind. We propose that TRN can be used to rapidly evaluate or warn of ecosystem disturbance, senescence, and degradation without prior knowledge of species composition, nutrient status, and complex ecosystem processes.

The seasonal dynamic of gross primary productivity (GPP) has influences on the annual GPP (AGPP) of the terrestrial ecosystem. However, the spatiotemporal variation of the seasonal dynamic of GPP and its effects on spatial and temporal variations of AGPP are still poorly addressed. In this study, we developed a parameter, αGPP, defined as the ratio of mean daily GPP (GPPmean) to the maximum daily GPP (GPPmax) during the growing season, to analyze the seasonal dynamic of GPP based on Weibull function. The αGPP was a comprehensive parameter characterizing the shape, scale, and location of the seasonal dynamic curve of GPP. We calculated αGPP based on the data of GPP for 942 site-years from 115 flux sites in the Northern Hemisphere, and analyzed the spatiotemporal variation and influencing factors of the αGPP. We found that the αGPP of terrestrial ecosystems in the Northern Hemisphere ranged from 0.47 to 0.85, with an average of 0.62 ± 0.06. The αGPP varied significantly both among different climatic zones and different ecosystem types. The αGPP was stable on the interannual scale, while decreased as latitude increased, which was consistent across different ecosystem types. The spatial pattern of the seasonal dynamic of astronomical radiation was the dominating factor of the spatial pattern of αGPP, that was, the spatial pattern of the seasonal dynamic of astronomical radiation determined that of the seasonal dynamic of GPP by controlling that of seasonal dynamics of total radiation and temperature. In addition, we assessed the spatial variation of AGPP preliminarily based on αGPP and other seasonal dynamic parameters of GPP, indicating that the understanding of the spatiotemporal variation of αGPP could provide a new approach for studying the spatial and temporal variations of AGPP and estimating AGPP based on the seasonal dynamic of GPP.

The Arctic is warming at twice the rate of the global mean. This warming could further stimulate methane (CH4) emissions from northern wetlands and enhance the greenhouse impact of this region. Arctic wetlands are extremely heterogeneous in terms of geochemistry, vegetation, microtopography, and hydrology, and therefore CH4 fluxes can differ dramatically within the metre scale. Eddy covariance (EC) is one of the most useful methods for estimating CH4 fluxes in remote areas over long periods of time. However, when the areas sampled by these EC towers (i.e. tower footprints) are by definition very heterogeneous, due to encompassing a variety of environmental conditions and vegetation types, modelling environmental controls of CH4 emissions becomes even more challenging, confounding efforts to reduce uncertainty in baseline CH4 emissions from these landscapes. In this study, we evaluated the effect of footprint variability on CH4 fluxes from two EC towers located in wetlands on the North Slope of Alaska. The local domain of each of these sites contains well developed polygonal tundra as well as a drained thermokarst lake basin. We found that the spatiotemporal variability of the footprint, has a significant influence on the observed CH4 fluxes, contributing between 3% and 33% of the variance, depending on site, time period, and modelling method. Multiple indices were used to define spatial heterogeneity, and their explanatory power varied depending on site and season. Overall, the normalised difference water index had the most consistent explanatory power on CH4 fluxes, though generally only when used in concert with at least one other spatial index. The spatial bias (defined here as the difference between the mean for the 0.36 km2 domain around the tower and the footprint-weighted mean) was between ∣51∣% and ∣18∣% depending on the index. This study highlights the need for footprint modelling to infer the representativeness of the carbon fluxes measured by EC towers in these highly heterogeneous tundra ecosystems, and the need to evaluate spatial variability when upscaling EC site-level data to a larger domain.

Warming in northern high latitudes has changed the energy balance between terrestrial ecosystems and the atmosphere. This study evaluated changes in regional surface energy exchange in Alaska from 2000 to 2011 when substantial declines in spring snow cover due to spring warming and large-scale fire events were observed. Energy fluxes from a network of 20 eddy covariance sites were upscaled using a support vector regression (SVR) model, by combining satellite remote sensing data and global climate data. Based on site-scale analysis, SVR reproduced observed net radiation, sensible heat flux, latent heat flux, and ground heat flux; 8 day root-mean-square errors for these variables were 15, 10, 9, and 3 W m−2, respectively. Based on upscaled fluxes, decreases in spring snow cover induced an increase in surface net radiation, a net heating effect, of 0.56 W m−2 decade−1. This heating effect was comparable to the net cooling effect due to increased fire extent during the study period (up to 0.59 W m−2 decade−1). These land cover effects were larger than the change in the energy forcing associated with CO2 balance for the Alaska region. Spring warming and postfire land cover change increased the regional latent heat flux. The regional sensible heat flux decreased with the postfire land cover change. Our results highlight the importance of positive spring snow albedo feedback to climate and a postfire negative feedback under the expected warming climate in the Arctic.

Regional quantification of arctic CO 2 and CH 4 fluxes remains difficult due to high landscape heterogeneity coupled with a sparse measurement network. Most of the arctic coastal tundra near Barrow, Alaska is part of the thaw lake cycle, which includes current thaw lakes and a 5500-year chronosequence of vegetated thaw lake basins. However, spatial variability in carbon fluxes from these features remains grossly understudied. Here, we present an analysis of whole-ecosystem CO 2 and CH 4 fluxes from 20 thaw lake cycle features during the 2011 growing season. We found that the thaw lake cycle was largely responsible for spatial variation in CO 2 flux, mostly due to its control on gross primary productivity (GPP). Current lakes were significant CO 2 sources that varied little. Vegetated basins showed declining GPP and CO 2 sink with age (R 2 = 67% and 57%, respectively). CH 4 fluxes measured from a subset of 12 vegetated basins showed no relationship with age or CO 2 flux components. Instead, higher CH 4 fluxes were related to greater landscape wetness (R 2 = 57%) and thaw depth (additional R 2 = 28%). Spatial variation in CO 2 and CH 4 fluxes had good satellite remote sensing indicators, and we estimated the region to be a small CO 2 sink of -4.9 ± 2.4 (SE) g C m -2 between 11 June and 25 August, which was countered by a CH 4 source of 2.1 ± 0.2 (SE) g C m -2 . Results from our scaling exercise showed that developing or validating regional estimates based on single tower sites can result in significant bias, on average by a factor 4 for CO 2 flux and 30% for CH 4 flux. Although our results are specific to the Arctic Coastal Plain of Alaska, the degree of landscape-scale variability, large-scale controls on carbon exchange, and implications for regional estimation seen here likely have wide relevance to other arctic landscapes.

a b s t r a c t The eddy-covariance method often underestimates fluxes under stable, low-wind conditions at night when turbulence is not well developed. The most common approach to resolve the problem of nighttime flux underestimation is to identify and remove the deficit periods using friction-velocity (u*) threshold filters (u* Th ). This study modifies an accepted method for u* Th evaluation by incorporating change-point

Arctic terrestrial ecosystems are major global sources of methane (CH4); hence, it is important to understand the seasonal and climatic controls on CH4 emissions from these systems. Here, we report year-round CH4 emissions from Alaskan Arctic tundra eddy flux sites and regional fluxes derived from aircraft data. We find that emissions during the cold season (September to May) account for >= 50% of the annual CH4 flux, with the highest emissions from noninundated upland tundra. A major fraction of cold season emissions occur during the "zero curtain" period, when subsurface soil temperatures are poised near 0 degrees C. The zero curtain may persist longer than the growing season, and CH4 emissions are enhanced when the duration is extended by a deep thawed layer as can occur with thick snow cover. Regional scale fluxes of CH4 derived from aircraft data demonstrate the large spatial extent of late season CH4 emissions. Scaled to the circumpolar Arctic, cold season fluxes from tundra total 12 +/- 5 (95% confidence interval) Tg CH4 y(-1), similar to 25% of global emissions from extratropical wetlands, or similar to 6% of total global wetland methane emissions. The dominance of late-season emissions, sensitivity to soil environmental conditions, and importance of dry tundra are not currently simulated in most global climate models. Because Arctic warming disproportionally impacts the cold season, our results suggest that higher cold-season CH4 emissions will result from observed and predicted increases in snow thickness, active layer depth, and soil temperature, representing important positive feedbacks on climate warming.

Climatic variables not only directly affect the interannual variability (IAV) in net ecosystem exchange of CO 2 (NEE) but also indirectly drive it by changing the physiological parameters. Identifying these direct and indirect paths can reveal the underlying mechanisms of carbon (C) dynamics. In this study, we applied a path analysis using flux data from 65 sites to quantify the direct and indirect climatic effects on IAV in NEE and to evaluate the potential relationships among the climatic variables and physiological parameters that represent physiology and phenology of ecosystems. We found that the maximum photosynthetic rate was the most important factor for the IAV in gross primary productivity (GPP), which was mainly induced by the variation in vapour pressure deficit. For ecosystem respiration (RE), the most important drivers were GPP and the reference respiratory rate. The biome type regulated the direct and indirect paths, with distinctive differences between forests and non-forests, evergreen needleleaf forests and deciduous broadleaf forests, and between grasslands and croplands. Different paths were also found among wet, moist and dry ecosystems. However, the climatic variables can only partly explain the IAV in physiological parameters, suggesting that the latter may also result from other biotic and disturbance factors. In addition, the climatic variables related to NEE were not necessarily the same as those related to GPP and RE, indicating the emerging difficulty encountered when studying the IAV in NEE. Overall, our results highlight the contribution of certain physiological parameters to the IAV in C fluxes and the importance of biome type and multi-year water conditions, which should receive more attention in future experimental and modelling research. Keywords: net ecosystem exchange, interannual variability, climatic variations, physiological parameters, direct and indirect effects, relative importance (Published: 2 August 2016) Citation: Tellus B 2016, 68, 30575, http://dx.doi.org/10.3402/tellusb.v68.30575

The landscape surface of the Barrow Peninsula of Alaska is a mosaic of small ponds, thaw lakes, different aged vegetated drained thaw-lake basins (VDTLBs), and interstitial tundra which have been dynamically formed by both short- and long-term processes. We used a combination of tower- and aircraft-based eddy covariance measurements to characterize the spatial and temporal patterns of CO2, latent, and sensible heat fluxes along with MODIS NDVI, and were able to scale the aircraft-based CO2 fluxes to the 1802 km 2 Barrow Peninsula region. During typical 2006 summer conditions, the midday hourly CO2 flux over the region was � 2.04 � 10 5 kg CO2 h � 1 . The CO2 fluxes among the interstitial tundra, Ancient, and Old VDTLBs, as well as between the Medium and Young VDTLBs were not significantly different. Combined, the interstitial tundra and Old and Ancient VDTLBs represent � 67% of the Barrow Peninsula surface area, accounting for � 59% of the regional flux signal. Although the Medium and Young VDTLBs represent � 11% of the surface area, they account for a large portion, � 35%, of the total regional flux. The remaining � 22% of the surface area are lakes and contributed the remaining � 6% of the total regional flux. Previous studies treated vegetated areas of the region as a single surface type with measurements from a few study sites; doing so could underestimate the regional flux by � 22%. Here, we demonstrate that aircraft-based systems have the ability to cover large spatial scales while measuring the turbulent fluxes across a number of surfaces and combined with ground- and satellite-based measurements provide a valuable tool for both scaling and validation of regional-scale fluxes.

Arctic regions hold considerable reservoirs of soil organic carbon. However, most of this carbon is in a potential labile state, and expected changes in temperature and water availability could strongly affect the carbon balance of tundra ecosystems. Plant community composition and soil carbon are closely tied to microtopography and position relative to the water table. We evaluated CO2 fluxes and moss contribution to ecosystem photosynthesis in response to fine-scale topography across a drained lake bed in Barrow, Alaska, during two contrasting growing seasons. CO2 exchange was assessed through static chamber measurements in three vegetation classes distinguished by plant dominance and topographic position within low-centered polygons. Gross primary production (GPP) and ecosystem respiration (ER) were the lowest under high soil moisture conditions in 2006. ER responded more strongly to wet conditions, resulting in a larger summer sink in 2006 than in 2005 (64 vs. 17g CO2 m−2, respectively). Micr...

Northern ecosystems are a major sink for atmospheric CO2 and contain much of the world's soil organic carbon (SOC) that is potentially reactive to near-term climate change. We introduce a simple terrestrial carbon flux (TCF) model driven by satellite remote sensing inputs from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) to estimate surface (

Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board the National Aeronautics and Space Administration's (NASA) Terra satellite to scale up AmeriFlux NEE measurements to the continental scale. We first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a modified regression tree approach. The predictive model was trained and validated using eddy flux NEE data over the periods 2000-2004 and 2005-2006, respectively. We found that the model predicted NEE well (r = 0.73, p < 0.001). We then applied the model to the continental scale and estimated NEE for each 1 km x 1 km cell across the conterminous U.S. for each 8-day interval in 2005 using spatially explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE as determined from measurements and the literature. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets over large areas.

Methods are developed and evaluated to retrieve surface soil temperature information for the advanced microwave scanning radiometer on earth observing system for seven boreal forest and Arctic tundra biophysical monitoring sites across Alaska and Northern Canada. A multiple-band iterative radiative transfer process-based method producing dynamic vegetation and snow cover correction quantities and an empirical multiple regression method using several frequencies are employed. The seasonal pattern of microwave emission and relative accuracy of the soil temperature retrievals are influenced strongly by landscape properties, including the presence of open water, vegetation type and seasonal phenology, snow cover, and freeze-thaw transitions. The retrieval of soil temperature is similar for the two methods with an overall root-mean-square error of 3.1-3.9 K during summer thawed conditions, with a larger error occurring in winter during periods of dynamic snow cover and freeze-thaw state. These results indicate that at high latitudes, the influence of the atmosphere may be less important than that of surface conditions in determining the relative accuracy of the estimated soil temperature. Impacts of surface conditions on surface emissivity, observed brightness temperature, and estimated soil temperature are discussed.

Some form of the light use efficiency (LUE) model is used in most models of ecosystem carbon exchange based on remote sensing. The strong relationship between the normalized difference vegetation index (NDVI) and light absorbed by green vegetation make models based on LUE attractive in the remote sensing context. However, estimation of LUE has proven problematic since it varies with vegetation type and environmental conditions. Here we propose that LUE may in fact be correlated with vegetation greenness (measured either as NDVI at constant solar elevation angle, or a red edge chlorophyll index), making separate estimates of LUE unnecessary, at least for some vegetation types. To test this, we installed an automated tram system for measurement of spectral reflectance in the footprint of an eddy covariance flux system in the Southern California chaparral. This allowed us to match the spatial and temporal scales of the reflectance and flux measurements and thus to make direct comparisons over time scales ranging from minutes to years. The 3-year period of this study included both “normal” precipitation years and an extreme drought in 2002. In this sparse chaparral vegetation, diurnal and seasonal changes in solar angle resulted in large variation in NDVI independent of the actual quantity of green vegetation. In fact, one would come to entirely different conclusions about seasonal changes in vegetation greenness depending on whether NDVI at noon or NDVI at constant solar elevation angle were used. Although chaparral vegetation is generally considered “evergreen”, we found that the majority of the shrubs were actually semi-deciduous, leading to large seasonal changes in NDVI at constant solar elevation angle. LUE was correlated with both greenness indices at the seasonal timescale across all years. In contrast, the relationship between LUE and PRI was inconsistent. PRI was well correlated with LUE during the “normal” years but this relationship changed dramatically during the extreme drought. Contrary to expectations, none of the spectral reflectance indices showed consistent relationships with CO2 flux or LUE over the diurnal time-course, possibly because of confounding effects of sun angle and stand structure on reflectance. These results suggest that greenness indices can be used to directly estimate CO2 exchange at weekly timescales in this chaparral ecosystem, even in the face of changes in LUE. Greenness indices are unlikely to be as good predictors of CO2 exchange in dense evergreen vegetation as they were in the sparse, semi-deciduous chaparral. However, since relatively few ecosystems are entirely evergreen at large spatial scales or over long time spans due to disturbance, these relationships need to be examined across a wider range of vegetation types.

Estimates of net ecosystem exchange (NEE) of CO2 have been measured on a variety of ecosystems world wide including grasslands, savannahs, boreal, pine, deciduous, Mediterranean and tropical rain forests as well as arctic tundra. While there have been numerous comparisons between net primary productivity of arid and semiarid grasslands and shrublands, notably lacking are estimates of NEE with a few exceptions. The objective of this study was to characterize the seasonal and annual carbon flux of a desert shrub ecosystem using the eddy covariance technique to determine the sensitivity of the system to the timing and varying amounts of precipitation. Measurements began in July of 2001, a year with 339mm of rainfall, considerably above the long-term average of 174mm and preceded by 2 years of below average rainfall (50‐62mm). Over the 2 complete years of measurements, precipitation was 147 and 197mm in 2002 and 2003, respectively. In all years, the majority of the precipitation fell between August and September. The site was a sink of � 39gCm � 2 yr � 1 in 2002 with a relatively strong uptake in the early part of the year and reduced uptake after the suboptimal rainfall in September. This contrasts with 2003 when the ecosystem took up � 52gCm � 2 yr � 1 concentrated in the fall after significant rain in August and September. Likely, extremely low rainfall years would result in a carbon loss while a strengthening of the typical winter secondary peak in precipitation (notably absent in the 2 years of measurements) may extend uptake into the spring resulting in more carbon accumulation. The system appears to be buffered against variations in annual rainfall attributed to water storage in the stems and roots.

Operational monitoring of global terrestrial gross primary production (GPP) and net primary production (NPP) is now underway using imagery from the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Evaluation of MODIS GPP and NPP products will require site-level studies across a range of biomes, with close attention to numerous scaling issues that must be addressed to link ground measurements to the satellite-based carbon flux estimates. Here, we report results of a study aimed at evaluating MODIS NPP/GPP products at six sites varying widely in climate, land use, and vegetation physiognomy. Comparisons were made for twenty-five 1km 2 cells at each site, with 8-day averages for GPP and an annual value for NPP. The validation data layers were made with a combination of ground measurements, relatively high resolution satellite data (Landsat Enhanced Thematic Mapper Plus at � 30m resolution), and process-based modeling. There was strong seasonality in the MODIS GPP at all sites, and mean NPP ranged from 80gCm � 2 yr � 1 at an arctic tundra site to 550gCm � 2 yr � 1 at a temperate deciduous forest site. There was not a consistent over- or underprediction of NPP across sites relative to the validation estimates. The closest agreements in NPP and GPP were at the temperate deciduous forest, arctic tundra, and boreal forest sites. There was moderate underestimation in the MODIS products at the agricultural field site, and strong overestimation at the desert grassland and at the dry coniferous forest sites. Analyses of specific inputs to the MODIS NPP/ GPP algorithm ‐ notably the fraction of photosynthetically active radiation absorbed by the vegetation canopy, the maximum light use efficiency (LUE), and the climate data ‐ revealed the causes of the over- and underestimates. Suggestions for algorithm improvement include selectively altering values for maximum LUE (based on observations at eddy covariance flux towers) and parameters regulating autotrophic respiration.

The CO2 flux of a wet sedge tundra ecosystem in the Arctic, at Barrow, Alaska, was measured applying an eddy correlation method. The seasonal change of CO2 uptake by the vegetation and the net CO2 budget through the growing period were examined for the 2000 growing season. Tundra CO2 budget analysis model(TCBM) was applied to examine the vegetation responses to the environmental variables. Photosynthesis of the vegetation was well parameterized as functions of measured solar radiation, Rsd and air temperature, Ta, and ecosystem respiration was determined as a function of soil temperature at 0.01 m depth, Ts. Estimated CO2 flux by TCBM with measured Rsd and Ta was verified by comparison with observed CO2 flux, and then was used for gap-filling of data missing or eliminated data during the quality control. Parameters of TCBM functions were in accordance with previous studies; temperature dependence of the ecosystem respiration Q10 was 2.6, peak levels of photosynthesis-light response curve ranged 0.12-2.43gCO2m-2h-1 with optimum air temperature of 0.5-14.0°C, with high levels in late July, and the initial slope of the curve ranged 0.002-0.067 gCO2 W-1h-1. Daily CO2 flux was almost 0gCO2 m-2d-1 while the snow covered the ground. Then that changed to a source of up to 1.6gCO2m-2d-1 for about a week after snowmelt. After mid June, CO2 flux was a sink until mid September; those levels showed clear seasonal trends with a maximum of −17.8gCO2 m-2d-1 occurring on August 2. The Tundra ecosystem at Barrow accumulated −335gCO2 m-2 during 122 days of growing season in 2000. Photosynthesis and ecosystem respiration calculated by TCBM were −490gCO2 m-2 and 156 gCO2m-2, respectively. The larger photosynthesis and lower respiration were brought about because of the high water level condition, with standing water completely submerging the base of the wet sedge tundra. These conditions provided high photosynthetic activity and less gases-exchange between rhizosphere and atmosphere.

Rising air temperatures are believed to be hastening heterotrophic respiration (Rh) in arctic tundra ecosystems, which could lead to substantial losses of soil carbon (C). In order to improve confidence in predicting the likelihood of such loss, the comprehensive ecosystem model ecosys was first tested with carbon dioxide (CO2) fluxes measured over a tundra soil in a growth chamber under various temperatures and soil-water contents (θ). The model was then tested with CO2 and energy fluxes measured over a coastal arctic tundra near Barrow, Alaska, under a range of weather conditions during 1998–1999. A rise in growth chamber temperature from 7 to 15 °C caused large, but commensurate, rises in respiration and CO2 fixation, and so no significant effect on net CO2 exchange was modelled or measured. An increase in growth chamber θ from field capacity to saturation caused substantial reductions in respiration but not in CO2 fixation, and so an increase in net CO2 exchange was modelled and measured. Long daylengths over the coastal tundra at Barrow caused an almost continuous C sink to be modelled and measured during most of July (2–4 g C m−2 d−1), but shortening daylengths and declining air temperatures caused a C source to be modelled and measured by early September (∼1 g C m−2 d−1). At an annual time scale, the coastal tundra was modelled to be a small C sink (4 g C m−2 y−1) during 1998 when average air temperatures were 4 °C above normal, and a larger C sink (16 g C m−2 y−1) during 1999 when air temperatures were close to long-term normals. During 100 years under rising atmospheric CO2 concentration (Ca), air temperature and precipitation driven by the IS92a emissions scenario, modelled Rh rose commensurately with net primary productivity (NPP) under both current and elevated rates of atmospheric nitrogen (N) deposition, so that changes in soil C remained small. However, methane (CH4) emissions were predicted to rise substantially in coastal tundra with IS92a-driven climate change (from ∼20 to ∼40 g C m−2 y−1), causing a substantial increase in the emission of CO2 equivalents. If the rate of temperature increase hypothesized in the IS92a emissions scenario had been raised by 50%, substantial losses of soil C (∼1 kg C m−2) would have been modelled after 100 years, including additional emissions of CH4.

Average daily values of the Priestley-Taylor coefficient (a) were calculated for two eddy covariance (flux) tower sites with contrasting vegetation, soil moisture, and temperature characteristics on the North Slope of Alaska over the 1994 and 1995 growing seasons. Because variations in a have been shown to be associated with changes in vegetation, soil moisture, and meteorological conditions in Arctic ecosystems, we hypothesized that a values would be significantly different between sites. Since variations in the normalized difference vegetation index (NDVI) follow patterns of vegetation community composition and state that are largely controlled by moisture and temperature gradients on the North Slope of Alaska, we hypothesized that temporal variations in a respond to these same conditions and thus co-vary with NDVI. Significant differences in a values were found between the two sites in 1994 under average precipitation conditions. However, in 1995, when precipitation conditions were above average, no significant difference was found. Overall, the variations in a over the two growing seasons showed little relationship to the seasonal progression of the regional NDVI. The only significant relationship was found at the drier, upland study site.

A comprehensive evaluation of energy balance closure is performed across 22 sites and 50 site-years in FLUXNET, a network of eddy covariance sites measuring long-term carbon and energy fluxes in contrasting ecosystems and climates. Energy balance closure was evaluated by statistical regression of turbulent energy fluxes (sensible and latent heat (LE)) against available energy (net radiation, less the energy stored) and by solving for the energy balance ratio, the ratio of turbulent energy fluxes to available energy. These methods indicate a general lack of closure at most sites, with a mean imbalance in the order of 20%. The imbalance was prevalent in all measured vegetation types and in climates ranging from Mediterranean to temperate and arctic. There were no clear differences between sites using open and closed path infrared gas analyzers. At a majority of sites closure improved with turbulent intensity (friction velocity), but lack of total closure was still prevalent under most conditions. The imbalance was greatest during nocturnal periods. The results suggest that estimates of the scalar turbulent fluxes of sensible and LE are underestimated and/or that available energy is overestimated. The implications on interpreting long-term CO2 fluxes at FLUXNET sites depends on whether the imbalance results primarily from general errors associated

Climate change is leading to a disproportionately large warming in the high northern latitudes, but the magnitude and sign of the future carbon balance of the Arctic are highly uncertain. Using 40 terrestrial biosphere models for the Alaskan Arctic from four recent model intercomparison projects – NACP (North American Carbon Program) site and regional syntheses, TRENDY (Trends in net land atmosphere carbon exchanges), and WETCHIMP (Wetland and Wetland CH4 Inter-comparison of Models Project) – we provide a baseline of terrestrial carbon cycle uncertainty, defined as the multi-model standard deviation (σ) for each quantity that follows. Mean annual absolute uncertainty was largest for soil carbon (14.0 ± 9.2 kg C m−2), then gross primary production (GPP) (0.22 ± 0.50 kg C m−2 yr−1), ecosystem respiration (Re) (0.23 ± 0.38 kg C m−2 yr−1), net primary production (NPP) (0.14 ± 0.33 kg C m−2 yr−1), autotrophic respiration (Ra) (0.09 ± 0.20 kg C m−2 yr−1), heterotrophic respiration (Rh) (0.14 ± 0.20 kg C m−2 yr−1), net ecosystem exchange (NEE) (−0.01 ± 0.19 kg C m−2 yr−1), and CH4 flux (2.52 ± 4.02 g CH4 m−2 yr−1). There were no consistent spatial patterns in the larger Alaskan Arctic and boreal regional carbon stocks and fluxes, with some models showing NEE for Alaska as a strong carbon sink, others as a strong carbon source, while still others as carbon neutral. Finally, AmeriFlux data are used at two sites in the Alaskan Arctic to evaluate the regional patterns; observed seasonal NEE was captured within multi-model uncertainty. This assessment of carbon cycle uncertainties may be used as a baseline for the improvement of experimental and modeling activities, as well as a reference for future trajectories in carbon cycling with climate change in the Alaskan Arctic and larger boreal region.

1. Eddy covariance was used to measure the net CO2 flux of Alaskan moist-tussock and wet-sedge tundra ecosystems between 1 June and 31 August 1995. The sites were located within 2·5 km of each other and, depending on wind speed and thermal stability, the eddy-covariance measurements integrated surface fluxes over 0·8–26·5 ha (mean 3·8 ha) at the moist-tussock site and 0·1–4·2 ha (mean 0·6) at the wet-sedge site. 2. Both sites were net sinks for atmospheric CO2 during the 92-day measurement period but wet-sedge tundra accumulated 1·5 times more CO2 than moist-tussock tundra. Wet-sedge tundra was a net CO2 sink of −6·4 mol m−2 and moist-tussock tundra was a net sink of −4·6 mol m−2 over the June–August measurement period. 3. Estimates of whole-ecosystem respiration (R) were made using multiple non-linear regression by quantifying the response of measured nocturnal CO2 efflux (Fn) to fluctuations in air temperature and water-table depth (r2 = 0·68). Partial regression analysis revealed that water-table depth explained relatively more of the variance in Fn (45%) than temperature (11%). R was estimated to be 14·9 mol m−2 for moist-tussock tundra and 5·4 mol m−2 for wet-sedge tundra over the 92-day measurement period. The large difference in R was apparently owing to a substantially higher water table in wet-sedge tundra. 4. Estimated rates of gross primary production (GPP), calculated from measured net CO2 flux and estimated R, were 40% lower for wet-sedge tundra over the 92-day measurement period. Rates of GPP integrated over diel (24 h) periods were substantially larger for moist-tussock tundra ecosystems throughout June and July but during the month of August, total diel rates of GPP for moist-tussock and wet-sedge tundra were comparable. 5. Our results demonstrate that R and GPP of moist-tussock and wet-sedge tundra ecosystems can be reliably estimated from eddy-covariance measurements using functional relationships developed from plot-scale studies. Given the large spatial differences in hydrology, the larger sink observed for wet-sedge tundra was probably the result of relatively lower rates of R.

Measurements of net ecosystem CO 2 exchange (NEE) and energy balance were made using chamber-, tower-, and aircraft-based measurement techniques in Alaskan arctic tundra ecosystems during the 1994-1995 growing seasons (June-August). One of our objectives was to quantify the interrelationships between the NEE and the energy balance measurements made from different sampling techniques. Oualitative and quantitative intercomparisons revealed that on average the correspondence between the mass and energy fluxes measured by these sampling methods was good despite potential spatial and temporal mismatches in sampling scale. Quantitative comparisons using least squares linear regression analyses with the tower-based measurements of NEE as the independent variable indicate that the chamber- and aircraft-based NEE measurements were generally lower relative to the tower-based measurements (slope = 0.76-0.86). Similarly, tower-aircraft comparisons of latent (L e ) and sensible (H) heat exchange indicated that the aircraft-based measurements were lower than the tower-based measurements (slope = 0.72-0.80). Qualitative comparisons, however, indicate that the correspondence among the chamber-, tower-, and aircraft-measured fluxes varied both seasonally and interannually, suggesting the lack of a consistent bias between the sampling techniques. The results suggest that differences observed between the chamber, tower, and aircraft flux measurements were primarily due to the failure to account for the spatial distribution of surface types in the tower and aircraft sampling footprint, problems involved in the comparison of temporal and spatial averages, and temporal (e.g., seasonal and interannual) variance in rates of mass and energy flux for a given point. Other potential sources of variance include the underestimation of nocturnal NEE by the tower-based eddy covariance system, and the periodic occurrence of an elevated CO 2 plume in the atmosphere over the Prudhoe Bay oil field. Even with these potential sources of variation, the results reveal that the various methods give comparable estimates of NEE and energy flux within a range of temporal or spatial variability.

Studies and models of trace-gas flux in the Arctic consider temperature and moisture to be the dominant controls over land–atmosphere exchange1,2, with little attention having been paid to the effects of different substrates. Likewise, current Arctic vegetation maps for models of vegetation change recognize one or two tundra types3,4 and do not portray the extensive regions with different soils within the Arctic. Here we show that rapid changes to ecosystem processes (such as photosynthesis and respiration) that are related to changes in climate and land usage will be superimposed upon and modulated by differences in substrate pH. A sharp soil pH boundary along the northern front of the Arctic Foothills in Alaska separates non-acidic (pH > 6.5) ecosystems to the north from predominantly acidic (pH < 5.5) ecosystems to the south. Moist non-acidic tundra has greater heat flux, deeper summer thaw (active layer), is less of a carbon sink, and is a smaller source of methane than moist acidic tundra.

Large carbon dioxide plumes with concentrations up to 45 ppm aboveambient levels were measured about 15 km downwind of the Prudhoe Bay, Alaskamajor oil production facilities, located at 70° N Lat. above the ArcticCircle. The measured emissions were 1.3 × 103 metrictons (C) hour-1 (11.4× 106 metric tons(C) year-1), six times greater than the combustion emissionsassumed by Jaffe and coworkers in J. Atmos. Chem. 20 (1995), 213–227,based on 1989 reported Prudhoe Bay oil facility fuel consumption data, andfour times greater than the total C emissions reported by the oil facilitiesfor the same months as the measurement time periods. Variations in theemissions were estimated by extrapolating the observed emissions at a singlealtitude for all tundra research transect flights conducted downwind of theoil fields. These 30 flights yielded an average emission rate of1.02 × 103 metric tons (C) hour-1 with astandard deviation of 0.33 × 103. These quantity ofemissions are roughly equivalent to the carbon dioxide emissions of7–10 million hectares of arctic tussock tundra (Oechel and Vourlitis,Trends in Ecol. Evolution 9 (1994), 324–329).

The characteristics of micrometeorology and the CO2 flux of the Arctic wet tundra ecosystem were measured during the mid-summer of 1994 at Prudhoe Bay, Alaska. CO2 flux was measured by the eddy correlation technique with a sonic anemometer and an open path IRGA.Over the coastal Arctic tundra, the micrometeorology of the surface boundary layer changed remarkably according to wind direction. Wind from the Polar Sea brought cold and moist air, and southern wind brought warm and dry air with higher water vapor deficit, which resulted different CO2 flux over the wet tundra ecosystem.A simple canopy resistance model was applied in order to analyze the relationship between the CO2 flux and the micrometeorology, in which parameters were determined using measured data. The ecosystem respiration increased with water temperature, and the rate was larger under higher wind speed. The photosynthesis rate decreased with water vapor deficit between leaves and the atmosphere, and its decrement was larger under higher wind speed conditions.The effects of micrometeorology on the CO2 flux were examined using the model, which showed that the level of ecosystem respiration due to high water temperature and that of photosynthetic decrease due to high water vapor deficit were the same orders as the potential of photosynthesis measured over the coastal Arctic tundra at Prudhou Bay, Alaska in mid summer. The magnitude of the ecosystem respiration and the decrement of photosynthesis were large enough to diminish the downward CO2 flux to zero. The CO2 budget over the coastal Arctic wet tundra was much affected by the ecosystem respiration and the contribution of water stress to plant photosynthesis caused by higher temperature and drying.