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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

Global-scale studies suggest that dryland ecosystems dominate an increasing trend in the magnitude and interannual variability of the land CO

Wetlands are the single largest global natural methane (CH4) source, and emissions between 50°N and 70°N latitude contribute 10–30 % to this source. Predictive capability of northern wetland CH4 emissions is still low due to limited site measurements, strong spatial and temporal variability in emissions, and complex hydrological and biogeochemical dynamics. To explore this issue, we compare wetland CH4 emission predictions from the Community Land Model 4.5 (CLM4.5-BGC) with site to regional scale observations. A comparison of the CH4 fluxes with eddy flux data highlighted needed changes to the model’s estimate of aerenchyma area, which we implemented and tested. The model modification substantially reduced biases in CH4 emissions when compared with CarbonTracker CH4 predictions. CLM4.5 CH4 emission predictions agree well with growing season (May–September) CarbonTracker Alaskan regional-level CH4 predictions and site-level observations. However, CLM4.5 underestimated CH4 emissions in the cold season (October–April). The monthly CH4 mole fraction enhancements due to wetland emissions are also assessed using the WRF-STILT Lagrangian transport model coupled with daily emission priors from CLM4.5 and compared with aircraft CH4 mole fraction measurements from the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) campaign. Both the tower and aircraft analyses confirm the underestimate of cold season CH4 emissions by CLM4.5. The greatest uncertainties in predicting the seasonal CH4 cycle are from the wetland extent, cold season CH4 production and CH4 transport processes. We recommend more cold-season experimental studies in high latitude systems, which could improve understanding and parameterization of ecosystem structure and function during this period. Predicted CH4 emissions remain uncertain, but we show here that benchmarking against observations across spatial scales can inform model structural and parameter improvements.

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.

Improving year-round data coverage for CO2 and CH4 fluxes in the Arctic is critical for refining the global C budget but continuous measurements are very sparse due to the remote location limiting instrument maintenance, to low power availability, and to extreme weather conditions. The need for tailoring instrumentation, site set up, and maintenance at different sites can add uncertainty to estimates of annual C budgets from different ecosystems. In this study, we investigated the influence of different sensor combinations on fluxes of sensible heat, CO2, latent heat (LE), and CH4, and assessed the differences in annual CO2 and CH4 fluxes estimated with different instrumentation at the same sites. Using data from four sites across the North Slope of Alaska, we found that annual CO2 fluxes estimated with heated (7.5 +/- 1.4 gC m(-2) yr(-1)) and non-heated (7.9 +/- 1.3 gC m(-2) yr(-1)) anemometers were within uncertainty bounds. Similarly, despite elevated noise in 30-min flux data, we found that summer CO2 fluxes from open (-17.0 +/- 1.1 gC m(-2) yr(-1)) and close-path (-14.2 +/- 1.7 gC m(-2) yr(-1)) gas analyzers were not significantly different. Annual CH4 fluxes were also within uncertainty bounds when comparing both open (4.5 +/- 0.31 gC m(-2) yr(-1)) and closed-path (4.9 +/- 0.27 gC m(-2) yr(-1)) gas analyzers as well as heated (3.7 +/- 0.26 gC m(-2) yr(-1)) and non-heated (3.7 +/- 0.28 gC m(-2) yr(-1)) anemometers. A continuously heated anemometer increased data coverage (64%) relative to non-heated anemometers (47-52%). However, sensible heat fluxes were over-estimated by 12%, on average, with the heated anemometer, contributing to the overestimation of CO2, CH4, and LE fluxes (mean biases of 0.03 mu mol m(-2) s(-1), 0.05 mgC m(-2) h(-1), and 3.77 W m(-2), respectively). To circumvent this potential bias and reduce power consumption, we implemented an intermittent heating strategy whereby activation only occurred when ice or snow blockage of the transducers, was detected. This resulted in comparable coverage (50%) during winter to the continuously heated anemometer (46%), while avoiding flux over-estimation. Closed and open-path analyzers showed good agreement, but data coverage was generally greater when using closed-path, especially during winter. Winter data coverage of 26-32% was obtained with closed-path devices, vs 10-14% for the open-path devices with unheated anemometers or up to 46% and 35% using closed and open-path analyzers, respectively with heated anemometers. Accurate estimation of LE remains difficult in the Arctic due to strong attenuation in closed-path systems, even when intake tubes are heated, and due to poor data coverage from open-path sensors in such a harsh environment

The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties (EFPs). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity (GPP) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFPs and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site-years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R-2 = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements of eddy covariance fluxes and plant traits in time and space is shown to be highly relevant to better understand the importance of intra-and interspecific trait variation on ecosystem functioning.

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

Studies of global hydrologic cycles, carbon cycles and climate change are greatly facilitated when. global estimates of evapotranspiration (E) are available. We have developed an air-relative-humidity-based two-source (ARTS) E model that simulates the surface energy balance, soil water balance, and environmental constraints on E. It uses remotely sensed leaf area index (L-ai) and surface meteorological data to estimate E by: 1) introducing a simple biophysical model for canopy conductance (G(c)), defined as a constant maximum stomatal conductance g(smax) of 12.2 mm s(-1) multiplied by air relative humidity (R-h) and L-ai (G(c) = g(srnax) x R-h X L-ai); 2) calculating canopy transpiration with the G(c)-based Penman-Monteith (PM) E model; 3) calculating soil evaporation from an air-relative-humidity-based model of evapotranspiration (Yan & Shugart, 2010); 4) calculating total E (E-0) as the sum of the canopy transpiration and soil evaporation, assuming the absence of soil water stress; and 5) correcting E-0 for soil water stress using a soil water balance model. This physiological ARTS E model requires no calibration. Evaluation against eddy covariance measurements at 19 flux sites, representing a wide variety of climate and vegetation types, indicates that daily estimated E had a root mean square error = 0.77 mm d(-1). bias = -0.14 mm d(-1), and coefficient of determination, R-2 = 0.69. Global, monthly, 0.5 degrees-gridded ARTS E simulations from 1984 to 1998, which were forced using Advanced Very High Resolution Radiometer Lai data, Climate Research Unit climate data, and surface radiation budget data, predicted a mean annual land E of 58.4 x 10(3) km(3). This falls within the range (58 x 10(3)-85 x 10(3) km(3)) estimated by the Second Global Soil Wetness Project (GSWP-2: Dirmeyer et al., 2006). The ARTS E spatial pattern agrees well with that of the global E estimated by GSWP-2. The global annual ARTS E increased by 15.5 mm per decade from 1984 to 1998, comparable to an increase of 9.9 mm per decade from the model tree ensemble approach (Jung et al., 2010). These comparisons confirm the effectivity of the ARTS E model to simulate the spatial. pattern and climate response of global E. This model is the first of its kind among remote-sensing-based PM E models to provide global land E estimation with consideration of the soil water balance. (C) 2012 Elsevier Inc. All rights reserved.

The severity and incidence of climatic extremes, including drought, have increased as a result of climate warming. Analyses of observational and reanalysis data suggest that the strength of the western North American carbon sink declined by 30–298 Tg carbon per year during the drought at the turn of the century. Fossil fuel emissions aside, temperate North America is a net sink of carbon dioxide at present1,2,3. Year-to-year variations in this carbon sink are linked to variations in hydroclimate that affect net ecosystem productivity3,4. The severity and incidence of climatic extremes, including drought, have increased as a result of climate warming5,6,7,8. Here, we examine the effect of the turn of the century drought in western North America on carbon uptake in the region, using reanalysis data, remote sensing observations and data from global monitoring networks. We show that the area-integrated strength of the western North American carbon sink declined by 30–298 Tg C yr−1 during the 2000–2004 drought. We further document a pronounced drying of the terrestrial biosphere during this period, together with a reduction in river discharge and a loss of cropland productivity. We compare our findings with previous palaeoclimate reconstructions7 and show that the last drought of this magnitude occurred more than 800 years ago. Based on projected changes in precipitation and drought severity, we estimate that the present mid-latitude carbon sink of 177–623 Tg C yr−1 in western North America could disappear by the end of the century.

Arid environments represent 30% of the global terrestrial surface, but are largely under-represented in studies of ecosystem carbon flux. Less than 2% of all FLUXNET eddy covariance sites exist in a hot desert climate. Long-term datasets of these regions are vital for capturing the seasonal and interannual variability that occur due to episodic precipitation events and climate change, which drive fluctuations in soil moisture and temperature patterns. The objectives of this study were to determine the meteorological variables that drive carbon flux on diel, seasonal, and annual scales and to determine how precipitation events control annual net ecosystem exchange (NEE). Patterns of NEE from 2002 to 2008 were investigated, providing a record with multiple replicates of seasons and conditions. Precipitation was extremely variable (55–339 mm) during the study period, and reduced precipitation in later years (2004–2008) appears to have resulted in annual moderate to large carbon sources (62–258 g C m−2 yr−1) in contrast to the previously reported sink (2002–2003). Variations in photosynthetically active radiation were found to principally drive variations in carbon uptake during the wet growing season while increased soil temperatures at a 5 cm depth stimulated carbon loss during the dry dormant season. Monthly NEE was primarily driven by soil moisture at a 5 cm depth, and years with a higher magnitude of precipitation events showed a longer growing season with annual net carbon uptake, whereas years with lower magnitude had drier soils and displayed short growing seasons with annual net carbon loss. Increased precipitation frequency was associated with increased annual NEE, which may be a function of increased microbial respiration to more small precipitation events. Annual precipitation frequency and magnitude were found to have effects on the interannual variability of NEE for up to 2 years.

Drained thaw lake basins (DTLB's) are the dominant land form of the Arctic Coastal Plain in northern Alaska. The presence of continuous permafrost prevents drainage and so water tables generally remain close to the soil surface, creating saturated, suboxic soil conditions. However, ice wedge polygons produce microtopographic variation in these landscapes, with raised areas such as polygon rims creating more oxic microenvironments. The peat soils in this ecosystem store large amounts of organic carbon which is vulnerable to loss as arctic regions continue to rapidly warm, and so there is great motivation to understand the controls over microbial activity in these complex landscapes. Here we report the effects of experimental flooding, along with seasonal and spatial variation in soil chemistry and microbial activity in a DTLB. The flooding treatment generally mirrored the effects of natural landscape variation in water-table height due to microtopography. The flooded portion of the basin had lower dissolved oxygen, lower oxidation-reduction potential (ORP) and higher pH, as did lower elevation areas throughout the entire basin. Similarly, soil pore water concentrations of organic carbon and aromatic compounds were higher in flooded and low elevation areas. Dissolved ferric iron (Fe(III)) concentrations were higher in low elevation areas and responded to the flooding treatment in low areas, only. The high concentrations of soluble Fe(III) in soil pore water were explained by the presence of siderophores, which were much more concentrated in low elevation areas. All the aforementioned variables were correlated, showing that Fe(III) is solubilized in response to anoxic conditions. Dissolved carbon dioxide (CO2) and methane (CH4) concentrations were higher in low elevation areas, but showed only subtle and/or seasonally dependent effects of flooding. In anaerobic laboratory incubations, more CH4 was produced by soils from low and flooded areas, whereas anaerobic CO2 production only responded to flooding in high elevation areas. Seasonal changes in the oxidation state of solid phase Fe minerals showed that net Fe reduction occurred, especially in topographically low areas. The effects of Fe reduction were also seen in the topographic patterns of pH, as protons were consumed where this process was prevalent. This suite of results can all be attributed to the effect of water table on oxygen availability: flooded conditions promote anoxia, stimulating dissolution and reduction of Fe(III), and to some extent, methanogenesis. However, two lines of evidence indicated the inhibition of methanogenesis by alternative e- acceptors such as Fe(III) and humic substances: (1) ratios of CO2:CH4 evolved from anaerobic soil incubations and dissolved in soil pore water were high; (2) CH4 concentrations were negatively correlated with the oxidation state of the soluble Fe pool in both topographically high and low areas. A second set of results could be explained by increased soil temperature in the flooding treatment, which presumably arose from the increased thermal conductivity of the soil surface: higher N mineralization rates and dissolved P concentrations were observed in flooded areas. Overall, these results could have implications for C and nutrient cycling in high Arctic areas where warming and flooding are likely consequences of climate change.

Question Do variations in fire intensity within a stand determine changes in fire intensity and plant demographics in a subsequent fire? Location San Diego (CA, USA); chaparral dominated by Adenostoma fasciculatum (resprouter) and Ceanothus greggii (seeder). Methods In 2003, a wildfire burned a young (16-yr-old) stand containing a set of experimental plots burned in 1987 with various levels of fire intensity. In 2004, all the 1987 plots were sampled for Adenostoma survival and the recruitment of both species. Similar measures were carried out in the adjacent old (75-yr) stand. Fire intensity in 2003 was estimated by a surrogate fire severity measure [minimum diameter of burned branches (branch diameter)]. Results In the young stand, branch diameter in 2003 was similar to the control plots in 1987, but lower than in the old stand. Fire intensity in 1987 did not significantly affect branch diameter in 2003. Survival of Adenostoma in the young stand was very low, much lower than after the 1987 burn and that in the old stand. Fire intensity in 1987 did not affect Adenostoma survival. Recruitment in Adenostoma increased, and in Ceanothus decreased, with increased fire intensity in 1987. Conclusions We demonstrate that there is a carry-over effect of fire intensity across a whole fire cycle on plant recruitment of the two dominant species. The 2003 fire partially reversed the relative effects on recruitment caused by elevated fire intensity in 1987. Arguably, this effect was driven by the contrasted relationships of the two species to fire intensity. Adenostoma survival in the young stand was much lower in 2003 than in 1987, despite similar branch diameter, and was also lower than in the old stand, despite higher branch diameter in this case. The causes of such mortality are unknown.

Projected increases in air temperature and precipitation due to climate change in Arctic wetlands could dramatically affect ecosystem functioning. As a consequence, it is important to define the controls on evapotranspiration, which is the major pathway of water loss from these systems. We quantified the multi-year controls on midday arctic coastal wetland evapotranspiration measured with the eddy covariance method at two vegetated drained thaw lake basins near Barrow, Alaska. Variations in near-surface soil moisture and atmospheric vapor pressure deficits were found to have nonlinear effects on midday evapotranspiration rates. Vapor pressure deficits near and above 0.3 kPa appeared to be an important hydrological threshold, allowing latent heat fluxes to persistently exceed sensible heat fluxes. Dry soils increased the bulk surface resistance (water-limited). Wet soils favored ground heat flux and therefore limited the energy available to sensible and latent heat fluxes (energy-limited). Thus, midday evapotranspiration was suppressed on both dry and wet soils through different mechanisms. We also found that wet soils (ponding excluded) combined with large atmospheric demands resulted in an increased bulk surface resistance and therefore suppressing the evapotranspiration to below its potential rate (Priestley-Taylor α < 1.26). This is likely caused by the limited ability of mosses to transfer moisture during large atmospheric demands. Ultimately, in addition to net radiation, the various controlling factors on midday evapotranspiration (near-surface soil moisture, atmospheric vapor pressure, and the limited ability of mosses that are saturated at depth to transfer water during high atmospheric vapor demands) resulted in an average evapotranspiration rate of up to 75 % of the potential evapotranspiration rate. The multiple limitations on midday evapotranspiration rates have the potential to moderate interannual variation of total evapotranspiration and dampen excessive water loss during a warmer climate. Combined with the prevailing maritime winds and the projected increase in precipitation, these dampening mechanisms will likely prevent extensive future soil drying and hence maintain the presence of coastal wetlands.

Partial pressure of CO2 in equilibrium with sample water (pCO2) for the coastal water in the Chukchi Sea was continuously observed in summer, 2008. Average daily CO2 flux calculated from the pCO2 and gas transfer coefficients ranged from −0.144 to −0.0701 g C m−2 day−1 depending on which gas transfer coefficient was used. The pCO2 before the landfast ice sheets melted appeared to be highly biologically controlled based on the following information: (1) the diurnal pattern of pCO2 was strongly correlated with Photosynthetic Photon Flux Density (PPFD); (2) high chlorophyll density was observed during periods of peak uptake; and (3) the day-to-day variation in the pCO2 strongly correlated with the presence or absence of near-shore ice sheets. The lowest pCO2 of 35 ppm together with the highest PPFD of 1362 μmol E m−2 s−1 were observed in the afternoon on June 28 in the presence of sea ice. The very low pCO2 observed in late June was likely caused by high photosynthetic rates related to high phytoplankton densities typically observed from spring to early summer near the ice edge, and by water low in salinity and CO2 released by melting sea ice early in the season.

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...

The ecosystem fluxes of mass and energy were quantified for a riparian cottonwood (Populus fremontii S. Watson) stand, and the daily and seasonal courses of evapotranspiration, CO2 flux, and canopy conductance were described, using eddy covariance. The ecosystem-level evapotranspiration results are consistent with those of other riparian studies; high vapor pressure deficit and increased groundwater depth resulted in reduced canopy conductance, and the annual cumulative evapotranspiration of 1095 mm was more than double the magnitude of precipitation. In addition, the cottonwood forest was a strong sink of CO2, absorbing 310 g C m−2 from the atmosphere in the first 365 days of the study. On weekly to annual time scales, hydrology was strongly linked with the net atmosphere–ecosystem exchange of CO2, with ecosystem productivity greatest when groundwater depth was ∼2 m below the ground surface. Increases in groundwater depth beyond the depth of 2 m corresponded with decreased CO2 uptake and evapotranspiration. Saturated soils caused by flooding and shallow groundwater depths also resulted in reduced ecosystem fluxes of CO2 and water.

More accurate projections of future carbon dioxide concentrations in the atmosphere and associated climate change depend on improved scientific understanding of the terrestrial carbon cycle. Despite the consensus that U.S. terrestrial ecosystems provide a carbon sink, the size, distribution, and interannual variability of this sink remain uncertain. Here we report a terrestrial carbon sink in the conterminous U.S. at 0.63 pg C yr −1 with the majority of the sink in regions dominated by evergreen and deciduous forests and savannas. This estimate is based on our continuous estimates of net ecosystem carbon exchange (NEE) with high spatial (1 km) and temporal (8-day) resolutions derived from NEE measurements from eddy covariance flux towers and wall-to-wall satellite observations from Moderate Resolution Imaging Spectroradiometer (MODIS). We find that the U.S. terrestrial ecosystems could offset a maximum of 40% of the fossil-fuel carbon emissions. Our results show that the U.S. terrestrial carbon sink varied between 0.51 and 0.70 pg C yr −1 over the period 2001–2006. The dominant sources of interannual variation of the carbon sink included extreme climate events and disturbances. Droughts in 2002 and 2006 reduced the U.S. carbon sink by ∼20% relative to a normal year. Disturbances including wildfires and hurricanes reduced carbon uptake or resulted in carbon release at regional scales. Our results provide an alternative, independent, and novel constraint to the U.S. terrestrial carbon sink.

This paper describes a new low-power instrument for measuring methane flux by eddy covariance method at sites without grid power. Design and field performance of the LI-7700 Methane Analyzer (LI-COR Biosciences) are examined in this study. The instrument uses 8 W of power in steady-state operation and employs a tunable diode laser in an open Herriott cell configuration with 0.47 m base path and 30 m optical path length. Methane number density is measured using wavelength modulation spectroscopy (WMS) with 2f detection. Typical signal noise is

investigated. Overall annual moss production at the intensive black spruce site was about 120 g m-1 yr-1 or about twice as high as the corresponding annual spruce production. Maximum rates of net photosynthesis varied from 2.7 mg CO2 g-1 h-' in Polytrichum commune Hedw. to 0.6 mg CO2 g-1 h-1 in Sphagnum nemoreum Scop. The photosynthesis of overwintered leaves early in the season was low and as a result of new growth a steady increase in net photosynthesis occurred throughout the season. Leaf water content was found to be the most important limiting factor for growth under natural conditions. There was a strong increase in growth and photosynthesis of Sphagnum nemoreum

Satellite observations have shown greening trends in tundra in response to climate change, suggesting increases in productivity. To better understand the ability of remote sensing to detect climate impacts on tundra vegetation productivity, we applied a photosynthetic light use efficiency model to simulated climate change treatments of tundra vegetation. We examined changes in the Normalized Difference Vegetation Index (NDVI) and photosynthetic light use efficiency (e) in experimental warming and moisture treatments designed to simulate climate change in northern Alaska. Plots were warmed either passively, using Open Top Chambers, or actively using electric heaters in the soil. In one set of plots water table depth was actively altered, while other plots were established in locations that were naturally wet or dry. Over two growing seasons, plot-level carbon flux and spectral reflectance measurements were collected, and the results were used to derive a light use efficiency model that could explore the effects of moisture and temperature treatments using remote sensing. Warming increased values of canopy greenness (NDVI) relative to control plots, this effect being more pronounced in wet plots than in dry plots. Light use efficiency (LUE), the relationship between absorbed photosynthetically active radiation (PAR) and gross ecosystem production (GEP), was consistent across warming treatments, growing season, subsequent years, and sites. However, LUE was affected by vegetation type, which varied with moisture; plots in naturally dry locations showed reduced light use efficiency relative to moist plots. Additionally moss exhibited reduced LUE relative to vascular plants. Understory moss production, not accounted for by the usual definition of the fraction of absorbed PAR (fAPAR), was found to be a significant part of total GEP, particularly in areas with low vascular plant cover. These results support the use of light use efficiency models driven by spectral reflectance for estimating GEP in tundra vegetation, provided effects of vegetation functional type (e.g. mosses versus vascular plants) and microtopography are considered.

The quantification of carbon fluxes between the terrestrial biosphere and the atmosphere is of scientific importance and also relevant to climate-policy making. Eddy covariance flux towers provide continuous measurements of ecosystem-level exchange of carbon dioxide spanning diurnal, synoptic, seasonal, and interannual time scales. However, these measurements only represent the fluxes at the scale of the tower footprint. Here we used remotely sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to upscale gross primary productivity (GPP) data from eddy covariance flux towers to the continental scale. We first combined GPP and MODIS data for 42 AmeriFlux towers encompassing a wide range of ecosystem and climate types to develop a predictive GPP model using a regression tree approach. The predictive model was trained using observed GPP over the period 2000–2004, and was validated using observed GPP over the period 2005–2006 and leave-one-out cross-validation. Our model predicted GPP fairly well at the site level. We then used the model to estimate GPP for each 1 km × 1 km cell across the U.S. for each 8-day interval over the period from February 2000 to December 2006 using MODIS data. Our GPP estimates provide a spatially and temporally continuous measure of gross primary production for the U.S. that is a highly constrained by eddy covariance flux data. Our study demonstrated that our empirical approach is effective for upscaling eddy flux GPP data to the continental scale and producing continuous GPP estimates across multiple biomes. With these estimates, we then examined the patterns, magnitude, and interannual variability of GPP. We estimated a gross carbon uptake between 6.91 and 7.33 Pg C yr− 1 for the conterminous U.S. Drought, fires, and hurricanes reduced annual GPP at regional scales and could have a significant impact on the U.S. net ecosystem carbon exchange. The sources of the interannual variability of U.S. GPP were dominated by these extreme climate events and disturbances.

Globally, soil microbes preside over vast carbon stores, and both microbial biomass and activity are known to be regulated by bottom-up controls, that is, limitation by nutrients and energy. However, there is evidence that grazing by protozoans exerts top-down controls on biomass. Here, we investigate top-down control by phage on soil microbes using an experimental site near Barrow, Alaska (71 degrees N, 157 degrees W) during the 2007 growing season. Soil measurements were taken from sites that covered a range of microtopographical features within a drained and thawed lake basin including high- and low-centred ice-wedge polygons to estimate the availability of carbon and nitrogen for microbes. Using both field and laboratory experiments, we successfully increased both microbial biomass and respiration by decreasing phage populations. The addition of carbon and nutrients to soils had no significant effects on biomass or respiration, indicating a lack of bottom-up controls. Additionally, we present the first use of tea extracts as a potent anti-phage agent in soils. Our results suggest that top-down controls, such as phage predation, are critical to regulation of microbial activities in Arctic soils.

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.

Many current models of ecosystem carbon exchange based on remote sensing, such as the MODIS product termed MOD17, still require considerable input from ground based meteorological measurements and look up tables based on vegetation type. Since these data are often not available at the same spatial scale as the remote sensing imagery, they can introduce substantial errors into the carbon exchange estimates. Here we present further development of a gross primary production (GPP) model based entirely on remote sensing data. In contrast to an earlier model based only on the enhanced vegetation index (EVI), this model, termed the Temperature and Greenness (TG) model, also includes the land surface temperature (LST) product from MODIS. In addition to its obvious relationship to vegetation temperature, LST was correlated with vapor pressure deficit and photosynthetically active radiation. Combination of EVI and LST in the model substantially improved the correlation between predicted and measured GPP at 11 eddy correlation flux towers in a wide range of vegetation types across North America. In many cases, the TG model provided substantially better predictions of GPP than did the MODIS GPP product. However, both models resulted in poor predictions for sparse shrub habitats where solar angle effects on remote sensing indices were large. Although it may be possible to improve the MODIS GPP product through improved parameterization, our results suggest that simpler models based entirely on remote sensing can provide equally good predictions of GPP.

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.

Interannual variability (IAV, represented by standard deviation) in net ecosystem exchange of CO2 (NEE) is mainly driven by climatic drivers and biotic variations (i.e., the changes in photosynthetic and respiratory responses to climate), the effects of which are referred to as climatic (CE) and biotic effects (BE), respectively. Evaluating the relative contributions of CE and BE to the IAV in carbon (C) fluxes and understanding their controlling mechanisms are critical in projecting ecosystem changes in the future climate. In this study, we applied statistical methods with flux data from 65 sites located in the Northern Hemisphere to address this issue. Our results showed that the relative contribution of BE (CnBE) and CE (CnCE) to the IAV in NEE was 57%+/- 14% and 43%+/- 14%, respectively. The discrepancy in the CnBE among sites could be largely explained by water balance index (WBI). Across water-stressed ecosystems, the CnBE decreased with increasing aridity (slope =0.18%mm(-1)). In addition, the CnBE tended to increase and the uncertainty reduced as timespan of available data increased from 5 to 15 years. Inter-site variation of the IAV in NEE mainly resulted from the IAV in BE (72%) compared to that in CE (37%). Interestingly, positive correlations between BE and CE occurred in grasslands and dry ecosystems (r> 0.45, P< 0.05) but not in other ecosystems. These results highlighted the importance of BE in determining the IAV in NEE and the ability of ecosystems to regulate C fluxes under climate change might decline when the ecosystems experience more severe water stress in the future. (C) 2015 Elsevier B.V. All rights reserved.

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.

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.

The goal of this study was to explore the utility of the 970 nm water band index (WBI) in estimating evapotranspiration and vegetation water status for a semiarid shrubland ecosystem. Between 2001 and 2003, spectral reflectance coupled with CO2 and water flux data were collected at Sky Oaks Biological Field Station, a chaparral-dominated ecosystem in southern California, and one of the sites within the SpecNet network. The reflectance data were collected either by walking along a 100 m transect or by using a semi-automated tram system installed later at the site along the same 100 m transect. CO2 and water flux data were gathered with an eddy covariance flux tower adjacent to the tram system. The 970 nm WBI and normalized difference vegetation index (NDVI) were derived from the spectral reflectance. The two indices were expressed both as points approximately a meter apart along the transect and as whole-transect averages, where all of the reflectance values along the transect were averaged together, simulating a large pixel. This study encompassed a wet year with normal precipitation (2001), a 100-year record drought (2002), and a recovery year (2003), allowing for comparison over time and between precipitation regimes. Species-specific responses to wet and dry periods were evident in the reflectance spectra, providing a basis for separating species based on their optical properties. The WBI was significantly correlated with the NDVI revealing a strong link between canopy water content and green canopy structure; however this relationship varied with species and water status, providing evidence for the independence of these two optical indices. The WBI was also strongly linked to surface–atmosphere fluxes, explaining 49% of the variance in the water vapor flux, and 24% of the carbon dioxide fluxes. These results suggest that WBI or other similar water status indices may be useful variables in modeling CO2 and water fluxes when combined with other physiological, environmental, and atmospheric factors.

The Moderate Resolution Spectroradiometer (MODIS) sensor has provided near real-time estimates of gross primary production (GPP) since March 2000. We compare four years (2000 to 2003) of satellite-based calculations of GPP with tower eddy CO2 flux-based estimates across diverse land cover types and climate regimes. We examine the potential error contributions from meteorology, leaf area index (LAI)/fPAR, and land cover. The error between annual GPP computed from NASA's Data Assimilation Office's (DAO) and tower-based meteorology is 28%, indicating that NASA's DAO global meteorology plays an important role in the accuracy of the GPP algorithm. Approximately 62% of MOD15-based estimates of LAI were within the estimates based on field optical measurements, although remaining values overestimated site values. Land cover presented the fewest errors, with most errors within the forest classes, reducing potential error. Tower-based and MODIS estimates of annual GPP compare favorably for most biomes, although MODIS GPP overestimates tower-based calculations by 20%-30%. Seasonally, summer estimates of MODIS GPP are closest to tower data, and spring estimates are the worst, most likely the result of the relatively rapid onset of leaf-out. The results of this study indicate, however, that the current MODIS GPP algorithm shows reasonable spatial patterns and temporal variability across a diverse range of biomes and climate regimes. So, while continued efforts are needed to isolate particular problems in specific biomes, we are optimistic about the general quality of these data, and continuation of the MOD17 GPP product will likely provide a key component of global terrestrial ecosystem analysis, providing continuous weekly measurements of global vegetation production

High latitude ecosystems were thought to enhance CH_4 emission in relation to the current arctic warming. However, we have little information about this potential feedback mechanisms on climate change, thus, model parameterization is insufficient and the observational data are required. We observed CH_4 flux at several types of tundra in Alaska over the growing seasons since 1995. From these observed data, we examined current CH_4 emission and its controlling factors on Alaskan tundra. Then we discussed about spatial and temporal differences in CH_4 flux. Daily trend of half hourly CH_4 flux had little relation with soil temperature, but the seasonal trend of daily flux changed with soil or water temperature. Cumulative CH_4 fluxes during the growing seasons were 8.1gCH_4m^(-2) on wet sedge tundra at Happy Valley in 1995, 3.3gCH_4m^(-2) on non-acidic moist tundra in 1996, and 3.58-8.24gCH_4m^(-2) on wet sedge tundra at Barrow between 1999-2003. Non-acidic tundra had low CH_4 emission with low CO_2 accumulation. There was large spatial difference in CH_4 flux caused by tundra type, and the large temporal difference at the wet sedge tundra reflected yearly weather variability.

This study reports the effects of long-term elevated atmospheric CO 2 on root production and microbial activity, biomass, and diversity in a chaparral ecosystem in southern California. The free air CO 2 enrichment (FACE) ring was located in a stand dominated by the woody shrub Adenostoma fasciculatum . Between 1995 and 2003, the FACE ring maintained an average daytime atmospheric CO 2 concentration of 550 ppm. During the last two years of operation, observations were made on soil cores collected from the FACE ring and adjacent areas of chaparral with ambient CO 2 levels. Root biomass roughly doubled in the FACE plot. Microbial biomass and activity were related to soil organic matter (OM) content, and so analysis of covariance was used to detect CO 2 effects while controlling for variation across the landscape. Extracellular enzymatic activity (cellulase and amylase) and microbial biomass C (chloroform fumigation-extraction) increased more rapidly with OM in the FACE plot than in controls, but glucose substrate-induced respiration (SIR) rates did not. The metabolic quotient (field respiration over potential respiration) was significantly higher in FACE samples, possibly indicating that microbial respiration was less C limited under high CO 2 . The treatments also differed in the ratio of SIR to microbial biomass C, indicating a metabolic difference between the microbial communities. Bacterial diversity, described by 16S rRNA clone libraries, was unaffected by the CO 2 treatment, but fungal biomass was stimulated. Furthermore, fungal biomass was correlated with cellulase and amylase activities, indicating that fungi were responsible for the stimulation of enzymatic activity in the FACE treatment.