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Abstract: 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 1km×1km 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 7.33PgCyr−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. [Copyright &y& Elsevier]

With representation of the global carbon cycle becoming increasingly complex in climate models, it is important to develop ways to quantitatively evaluate model performance against in situ and remote sensing observations. Here we present a systematic framework, the Carbon-LAnd Model Intercomparison Project (C-LAMP), for assessing terrestrial biogeochemistry models coupled to climate models using observations that span a wide range of temporal and spatial scales. As an example of the value of such comparisons, we used this framework to evaluate two biogeochemistry models that are integrated within the Community Climate System Model (CCSM) – Carnegie-Ames-Stanford Approach′ (CASA′) and carbon–nitrogen (CN). Both models underestimated the magnitude of net carbon uptake during the growing season in temperate and boreal forest ecosystems, based on comparison with atmospheric CO2 measurements and eddy covariance measurements of net ecosystem exchange. Comparison with MODerate Resolution Imaging Spectroradiometer (MODIS) measurements show that this low bias in model fluxes was caused, at least in part, by 1–3 month delays in the timing of maximum leaf area. In the tropics, the models overestimated carbon storage in woody biomass based on comparison with datasets from the Amazon. Reducing this model bias will probably weaken the sensitivity of terrestrial carbon fluxes to both atmospheric CO2 and climate. Global carbon sinks during the 1990s differed by a factor of two (2.4 Pg C yr−1 for CASA′ vs. 1.2 Pg C yr−1 for CN), with fluxes from both models compatible with the atmospheric budget given uncertainties in other terms. The models captured some of the timing of interannual global terrestrial carbon exchange during 1988–2004 based on comparison with atmospheric inversion results from TRANSCOM ( r=0.66 for CASA′ and r=0.73 for CN). Adding (CASA′) or improving (CN) the representation of deforestation fires may further increase agreement with the atmospheric record. Information from C-LAMP has enhanced model performance within CCSM and serves as a benchmark for future development. We propose that an open source, community-wide platform for model-data intercomparison is needed to speed model development and to strengthen ties between modeling and measurement communities. Important next steps include the design and analysis of land use change simulations (in both uncoupled and coupled modes), and the entrainment of additional ecological and earth system observations. Model results from C-LAMP are publicly available on the Earth System Grid. [ABSTRACT FROM AUTHOR]

Variability in three Pacific teleconnection patterns are examined to see if net carbon exchange at a low-elevation, old-growth forest is affected by climatic changes associated with these periodicities. Examined are the Pacific Decadal Oscillation (PDO), Pacific/North American Oscillation (PNA) and El Niño-Southern Oscillation (ENSO). We use 9 years of eddy covariance CO2, H2O and energy fluxes measured at the Wind River AmeriFlux site, Washington, USA and 8 years of tower-pixel remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to address this question. We compute a new Composite Climate Index (CCI) based on the three Pacific Oscillations to divide the measurement period into positive- (2003 and 2005), negative- (1999 and 2000) and neutral-phase climate years (2001, 2002, 2004, 2006 and 2007). The forest transitioned from an annual net carbon sink (NEP=+217 g C m−2 yr−1, 1999) to a source (NEP=−100 g C m−2 yr−1, 2003) during two dominant teleconnection patterns. Net ecosystem productivity (NEP), water use efficiency (WUE) and light use efficiency (LUE) were significantly different ( P<0.01) during positive (NEP=−0.27 g C m−2 day−1, WUE=4.1 mg C g−1 H2O, LUE=0.94 g C MJ−1) and negative (NEP=+0.37 g C m−2 day−1, WUE=3.4 mg C g−1 H2O, LUE=0.83 g C MJ−1) climate phases. The CCI was linked to variability in the MODIS Enhanced Vegetation Index (EVI) but not to MODIS Fraction of absorbed Photosynthetically Active Radiation (FPAR). EVI was highest during negative climate phases (1999 and 2000) and was positively correlated with NEP and showed potential for using MODIS to estimate teleconnection-driven anomalies in ecosystem CO2 exchange in old-growth forests. This work suggests that any increase in the strength or frequency of ENSO coinciding with in-phase, low frequency Pacific oscillations (PDO and PNA) will likely increase CO2 uptake variability in Pacific Northwest conifer forests. [ABSTRACT FROM AUTHOR]

The article reports on the roles played by advective fluxes to the process of net ecosystem exchange in a highly elevated subalpine forest. This study done at the Niwot Ridge AmeriFlux site in Colorado, involved measurements of the vertical and horizontal advective carbon dioxide fluxes. It utilized a number of towers as measurement approach. Results show that low surface friction velocities noted comparatively high rates of horizontal and vertical advective fluxes. Moreover, horizontal advetive flux was confined to thin layers of subcanopy air, while the observed vertical advective flux is from above the canopy.

Understanding relationships between canopy structure and the seasonal dynamics of photosynthetic uptake of CO2 by forest canopies requires improved knowledge of canopy phenology at eddy covariance flux tower sites. We investigated whether digital webcam images could be used to monitor the trajectory of spring green-up in a deciduous northern hardwood forest. A standard, commercially available webcam was mounted at the top of the eddy covariance tower at the Bartlett AmeriFlux site. Images were collected each day around midday. Red, green, and blue color channel brightness data for a 640 × 100-pixel region-of-interest were extracted from each image. We evaluated the green-up signal extracted from webcam images against changes in the fraction of incident photosynthetically active radiation that is absorbed by the canopy ( f APAR), a broadband normalized difference vegetation index (NDVI), and the light-saturated rate of canopy photosynthesis ( A max), inferred from eddy flux measurements. The relative brightness of the green channel (green %) was relatively stable through the winter months. A steady rising trend in green % began around day 120 and continued through day 160, at which point a stable plateau was reached. The relative brightness of the blue channel (blue %) also responded to spring green-up, although there was more day-to-day variation in the signal because blue % was more sensitive to changes in the quality (spectral distribution) of incident radiation. Seasonal changes in blue % were most similar to those in f APAR and broadband NDVI, whereas changes in green % proceeded more slowly, and were drawn out over a longer period of time. Changes in A max lagged green-up by at least a week. We conclude that webcams offer an inexpensive means by which phenological changes in the canopy state can be quantified. A network of cameras could offer a novel opportunity to implement a regional or national phenology monitoring program. [ABSTRACT FROM AUTHOR]

Tower-based eddy covariance measurements of forest-atmosphere carbon dioxide (CO2) exchange from many sites around the world indicate that there is considerable year-to-year variation in net ecosystem exchange (NEE). Here, we use a statistical modeling approach to partition the interannual variability in NEE (and its component fluxes, ecosystem respiration, Reco, and gross photosynthesis, Pgross) into two main effects: variation in environmental drivers (air and soil temperature, solar radiation, vapor pressure deficit, and soil water content) and variation in the biotic response to this environmental forcing (as characterized by the model parameters). The model is applied to a 9-year data set from the Howland AmeriFlux site, a spruce-dominated forest in Maine, USA. Gap-filled flux measurements at this site indicate that the forest has been sequestering, on average, 190 g C m−2 yr−1, with a range from 130 to 270 g C m−2 yr−1. Our fitted model predicts somewhat more uptake (mean 270 g C m−2 yr−1), but interannual variation is similar, and wavelet variance analyses indicate good agreement between tower measurements and model predictions across a wide range of timescales (hours to years). Associated with the interannual variation in NEE are clear differences among years in model parameters for both Reco and Pgross. Analysis of model predictions suggests that, at the annual time step, about 40% of the variance in modeled NEE can be attributed to variation in environmental drivers, and 55% to variation in the biotic response to this forcing. As model predictions are aggregated at longer timescales (from individual days to months to calendar year), variation in environmental drivers becomes progressively less important, and variation in the biotic response becomes progressively more important, in determining the modeled flux. There is a strong negative correlation between modeled annual Pgross and Reco ( r=−0.93, P≤0.001); two possible explanations for this correlation are discussed. The correlation promotes homeostasis of NEE: the interannual variation in modeled NEE is substantially less than that for either Pgross or Reco [ABSTRACT FROM AUTHOR]

Annual budgets and fitted temperature response curves for soil respiration and ecosystem respiration provide useful information for partitioning annual carbon budgets of ecosystems, but they may not adequately reveal seasonal variation in the ratios of these two fluxes. Soil respiration ( Rs) typically contributes 30–80% of annual total ecosystem respiration ( Reco) in forests, but the temporal variation of these ratios across seasons has not been investigated. The objective of this study was to investigate seasonal variation in the Rs/ Reco ratio in a mature forest dominated by conifers at Howland, ME, USA. We used chamber measurements of Rs and tower-based eddy covariance measurements of Reco. The Rs/ Reco ratio reached a minimum of about 0.45 in the early spring, gradually increased through the late spring and early summer, leveled off at about 0.65 for the summer, and then increased again to about 0.8 in the autumn. A spring pulse of aboveground respiration presumably causes the springtime minimum in this ratio. Soil respiration ‘catches up’ as the soils warm and as root growth presumably accelerates in the late spring, causing the Rs/ Reco ratios to increase. The summertime plateau of Rs/ Reco ratios is consistent with summer drought suppressing Rs that would otherwise be increasing, based on increasing soil temperature alone, thus causing the Rs/ Reco ratios to not increase as soils continue to warm. Declining air temperatures and litter fall apparently contribute to increased Rs/ Reco ratios in the autumn. Differences in phenology of growth of aboveground and belowground plant tissues, mobilization and use of stored substrates within woody plants, seasonal variation in photosynthate and litter substrates, and lags between temperature changes of air and soil contribute to a distinct seasonal pattern of Rs/ Reco ratios. [ABSTRACT FROM AUTHOR]

Abstract: The need for carbon dioxide (CO2) flux estimations covering larger areas and the limitations of the point eddy covariance technique to address this requirement necessitates the modeling of CO2 flux from other micrometeorological variables. The non-linearity of the relationship between CO2 flux and other micrometeorological flux parameters such as energy fluxes limits the applicability of carbon flux models to accurately estimate the flux dynamics. Black box models such as the artificial neural network (ANN) provide a mathematically flexible structure to identify the complex non-linear relationship between inputs and outputs without attempting to explain the nature of the phenomena. A multilayer perceptron ANN technique with an error back propagation algorithm was applied to a CO2 flux simulation study on three different ecosystems (forest, grassland and wheat). Energy fluxes (net radiation, latent heat, sensible heat and soil heat flux) and temperature (air and soil) were used to train the ANN and predict the flux of CO2. Diurnal hourly fluxes data from 15 days of observations were divided into training and testing. Results of the CO2 flux simulation show that the technique can successfully predict the observed values with R 2 values between 0.75 and 0.94. Predictions from the forest and wheat field show higher promise than the grassland site. The technique is reliable, efficient and highly significant to estimate regional or global CO2 fluxes from point measurements and understand the spatiotemporal budget of the CO2 fluxes. [Copyright &y& Elsevier]

Evapotranspiration, a major component in terrestrial water balance and net primary productivity models, is difficult to measure and predict. This study compared five models of potential evapotranspiration (PET) applied to a ponderosa pine forest ecosystem at an AmeriFlux site in Northern California. The AmeriFlux sites are research forests across the United States, Canada, Brazil, and Costa Rica with instruments on towers that measure carbon, water, and energy fluxes into and out of the ecosystems. The evapotranspiration models ranged from simple temperature and solar radiation-driven equations to physically-based combination approaches and included reference surface and surface cover-dependent algorithms. For each evapotranspiration model, results were compared against mean daily latent heat from half-hourly measurements recorded on a tower above the forest canopy. All models calculate potential evapotranspiration (assuming well-watered soils at field capacity), rather than actual evapotranspiration (based on soil moisture limitations), and thus overpredicted values from the dry summer seasons of 1997 and 1998. A soil moisture function was integrated to estimate actual evapotranspiration, resulting in improved accuracy in model simulations. A modified Priestley–Taylor model performed well given its relative simplicity. [Copyright &y& Elsevier]

Theδ13 Cvalues of atmospheric carbon dioxide (CO2) can be used to partition global patterns of CO2 source/sink relationships among terrestrial and oceanic ecosystems using the inversion technique. This approach is very sensitive to estimates of photosynthetic13 Cdiscrimination by terrestrial vegetation (ΔA), and depends onδ13 Cvalues of respired CO2 fluxes (δ13 CR). Here we show that by combining two independent data streams– the stable isotope ratios of atmospheric CO2 and eddy-covariance CO2 flux measurements– canopy scale estimates ofΔA can be successfully derived in terrestrial ecosystems. We also present the first weekly dataset of seasonal variations inδ13 CR from dominant forest ecosystems in the United States between 2001 and 2003. Our observations indicate considerable summer-time variation in the weekly value ofδ13 CR within coniferous forests (4.0‰ and 5.4‰ at Wind River Canopy Crane Research Facility and Howland Forest, respectively, between May and September). The monthly mean values ofδ13 CR showed a smaller range (2–3‰), which appeared to significantly correlate with soil water availability. Values ofδ13 CR were less variable during the growing season at the deciduous forest (Harvard Forest). We suggest that the negative correlation betweenδ13 CR and soil moisture content observed in the two coniferous forests should represent a general ecosystem response to the changes in the distribution of water resources because of climate change. Shifts inδ13 CR andΔA could be of sufficient magnitude globally to impact partitioning calculations of CO2 sinks between oceanic and terrestrial compartments. [ABSTRACT FROM AUTHOR]

Seven years of carbon dioxide flux measurements indicate that a∼90-year-old spruce dominated forest in Maine, USA, has been sequestering 174±46 g C m−2 yr−1 (mean±1 standard deviation, nocturnal friction velocity (u*) threshold>0.25 m s−1). An analysis of monthly flux anomalies showed that above-average spring and fall temperatures were significantly correlated with greater monthly C uptake while above-average summer temperatures were correlated with decreased net C uptake. Summer months with significantly drier or wetter soils than normal were also characterized by lower rates of C uptake. Years with above-average C storage were thus typically characterized by warmer than average spring and fall temperatures and adequate summer soil moisture.Environmental and forest–atmosphere flux data recorded from a second tower surrounded by similar forest, but sufficiently distant that flux source regions (‘footprints’), did not overlap significantly showed almost identical temperature and solar radiation conditions, but some differences in energy partitioning could be seen. Half-hourly as well as integrated (annual) C exchange values recorded at the separate towers were very similar, with average annual net C uptake differing between the two towers by<6%. Interannual variability in net C exchange was found to be much greater than between tower variability. Simultaneous measurements from two towers were used to estimate flux data uncertainty from a single tower. Carbon-flux model parameters derived independently from each flux tower data set were not significantly different, demonstrating that flux towers can provide a robust method for establishing C exchange model parameters. [ABSTRACT FROM AUTHOR]

To assess annual budgets of CO2 exchange between the biosphere and atmosphere over representative ecosystems, long-term measurements must be made over ecosystems that do not exist on ideal terrain. How to interpret eddy covariance measurements correctly remains a major task. At present, net ecosystem CO2 exchange is assessed, by members of the micrometeorological community, as the sum of eddy covariance measurements and the storage of CO2 in the underlying air. This approach, however, seems unsatisfactory as numerous investigators are reporting that it may be causing nocturnal respiration flux densities to be underestimated. A new theory was recently published by Lee (1998, Agricultural and Forest Meteorology 91: 39–50) for assessing net ecosystem-atmosphere CO2 exchange (Ne) over non-ideal terrain. It includes a vertical advection term. We apply this equation over a temperate broadleaved forest growing in undulating terrain. Inclusion of the vertical advection term yields hourly, daily and annual sums of net ecosystem CO2 exchange that are more ecologically correct during the growing season. During the winter dormant period, on the other hand, corrected CO2 flux density measurements of an actively respiring forest were near zero. This observation is unrealistic compared to chamber measurements and model calculations. Only during midday, when the atmosphere is well-mixed, do measurements of Ne match estimates based on model calculations and chamber measurements. On an annual basis, sums of Ne without the advection correction were 40% too large, as compared with computations derived from a validated and process-based model. With the inclusion of the advection correction term, we observe convergence between measured and calculated values of Ne on hourly, daily and yearly time scales. We cannot, however, conclude that inclusion of a one-dimensional, vertical advection term into the continuity equation is sufficient for evaluating CO2 exchange over tall forests in complex terrain. There is an indication that the neglected term, ū}(∂ c/∂ x), is non-zero and that CO2 may be leaking from the sides of the control volume during the winter. In this circumstance, forest floor CO2 efflux densities exceed effluxes measured above the canopy. [ABSTRACT FROM AUTHOR]