Physiological and environmental regulation of interannual variability in CO2 exchange on rangelands in the western United States

For most ecosystems, net ecosystem exchange of CO₂ (NEE) varies within and among years in response to environmental change. We analyzed measurements of CO₂ exchange from eight native rangeland ecosystems in the western United States (58 site‐years of data) in order to determine the contributions of photosynthetic and respiratory (physiological) components of CO₂ exchange to environmentally caused variation in NEE. Rangelands included Great Plains grasslands, desert shrubland, desert grasslands, and sagebrush steppe. We predicted that (1) week‐to‐week change in NEE and among‐year variation in the response of NEE to temperature, net radiation, and other environmental drivers would be better explained by change in maximum rates of ecosystem photosynthesis (A_max) than by change in apparent light‐use efficiency (α) or ecosystem respiration at 10 °C (R₁₀) and (2) among‐year variation in the responses of NEE, A_max, and α to environmental drivers would be explained by changes in leaf area index (LAI). As predicted, NEE was better correlated with A_max than α or R₁₀ for six of the eight rangelands. Week‐to‐week variation in NEE and physiological parameters correlated mainly with time‐lagged indices of precipitation and water‐related environmental variables, like potential evapotranspiration, for desert sites and with net radiation and temperature for Great Plains grasslands. For most rangelands, the response of NEE to a given change in temperature, net radiation, or evaporative demand differed among years because the response of photosynthetic parameters (A_max, α) to environmental drivers differed among years. Differences in photosynthetic responses were not explained by variation in LAI alone. A better understanding of controls on canopy photosynthesis will be required to predict variation in NEE of rangeland ecosystems.     

Partitioning net ecosystem carbon exchange and the carbon isotopic disequilibrium in a subalpine forest

We investigate the utility of an improved isotopic method to partition the net ecosystem exchange of CO₂ (F) into net photosynthesis (F_A) and nonfoliar respiration (F_R). Measurements of F and the carbon isotopic content in air at a high‐elevation coniferous forest (the Niwot Ridge AmeriFlux site) were used to partition F into F_A and F_R. Isotopically partitioned fluxes were then compared with an independent flux partitioning method that estimated gross photosynthesis (GEE) and total ecosystem respiration (TER) based on statistical regressions of night‐time F and air temperature. We compared the estimates of F_A and F_R with expected canopy physiological relationships with light (photosynthetically active radiation) and air temperature. Estimates of F_A and GEE were dependent on light as expected, and TER, but not F_R, exhibited the expected dependence on temperature. Estimates of the isotopic disequilibrium D , or the difference between the isotopic signatures of net photosynthesis (δ_A, mean value ?24.6‰) and ecosystem respiration (δ_R, mean value ?25.1‰) were generally positive (δ_A>δ_R). The sign of D observed here is inconsistent with many other studies. The key parameters of the improved isotopic flux partitioning method presented here are ecosystem scale mesophyll conductance (g_m) and maximal vegetative stomatal conductance (g_cmax). The sensitivity analyses of F_A, F_R, and D to g_cmax indicated a critical value of g_cmax (0.15 mol m^?2 s^?1) above which estimates of F_A and F_R became larger in magnitude relative to GEE and TER. The value of D decreased with increasing values of g_m and g_cmax, but was still positive across all values of g_m and g_cmax. We conclude that the characterization of canopy‐scale mesophyll and stomatal conductances are important for further progress with the isotope partitioning method, and to confirm our anomalous isotopic disequilibrium findings.     

18O composition of CO2 and H2O ecosystem pools and fluxes in a tallgrass prairie: Simulations and comparisons to measurements

In this paper we describe measurements and modeling of ¹⁸O in CO₂ and H₂O pools and fluxes at a tallgrass prairie site in Oklahoma. We present measurements of the δ¹⁸O value of leaf water, depth‐resolved soil water, atmospheric water vapor, and Keeling plot δ¹⁸O intercepts for net soil‐surface CO₂ and ecosystem CO₂ and H₂O fluxes during three periods of the 2000 growing season. Daytime discrimination against C¹⁸OO, as calculated from measured above‐canopy CO₂ and δ¹⁸O gradients, is also presented. To interpret the isotope measurements, we applied an integrated land‐surface and isotope model (ISOLSM) that simulates ecosystem H₂¹⁸O and C¹⁸OO stocks and fluxes. ISOLSM accurately predicted the measured isotopic composition of ecosystem water pools and the δ¹⁸O value of net ecosystem CO₂ and H₂O fluxes. Simulations indicate that incomplete equilibration between CO₂ and H₂O within C₄ plant leaves can have a substantial impact on ecosystem discrimination. Diurnal variations in the δ¹⁸O value of above‐canopy vapor had a small impact on the predicted δ¹⁸O value of ecosystem water pools, although sustained differences had a large impact. Diurnal variations in the δ¹⁸O value of above‐canopy CO₂ substantially affected the predicted ecosystem discrimination. Leaves dominate the ecosystem ¹⁸O‐isoflux in CO₂ during the growing season, while the soil contribution is relatively small and less variable. However, interpreting daytime measurements of ecosystem C¹⁸OO fluxes requires accurate predictions of both soil and leaf ¹⁸O‐isofluxes.     

Modelling the discrimination of 13CO2 above and within a temperate broad-leaved forest canopy on hourly to seasonal time scales

Fluxes and concentrations of carbon dioxide and ¹³CO₂ provide information about ecosystem physiological processes and their response to environmental variation. The biophysical model, CANOAK, was adapted to compute concentration profiles and fluxes of ¹³CO₂ within and above a temperate deciduous forest (Walker Branch Watershed, Tennessee, USA). Modifications to the model are described and the ability of the new model (CANISOTOPE) to simulate concentration profiles of ¹³CO₂, its flux density across the canopy–atmosphere interface and leaf‐level photosynthetic discrimination against ¹³CO₂ is demonstrated by comparison with field measurements. The model was used to investigate several aspects of carbon isotope exchange between a forest ecosystem and the atmosphere. During the 1998 growing season, the mean photosynthetic discrimination against ¹³CO₂, by the deciduous forest canopy (Δ_canopy), was computed to be 22·4‰, but it varied between 18 and 27‰. On a diurnal basis, the greatest discrimination occurred during the early morning and late afternoon. On a seasonal time scale, the greatest diurnal range in Δ_canopy occurred early and late in the growing season. Diurnal and seasonal variations in Δ_canopy resulted from a strong dependence of Δ_canopy on photosynthetically active radiation and vapour pressure deficit of air. Model calculations also revealed that the relationship between canopy‐scale water use efficiency (CO₂ assimilation/transpiration) and Δ_canopy was positive due to complex feedbacks among fluxes, leaf temperature and vapour pressure deficit, a finding that is counter to what is predicted for leaves exposed to well‐mixed environments.     

Radon fluxes in tropical forest ecosystems of Brazilian Amazonia: night-time CO2 net ecosystem exchange derived from radon and eddy covariance methods

Radon‐222 (Rn‐222) is used as a transport tracer of forest canopy–atmosphere CO₂ exchange in an old‐growth, tropical rain forest site near km 67 of the Tapajós National Forest, Pará, Brazil. Initial results, from month‐long periods at the end of the wet season (June–July) and the end of the dry season (November–December) in 2001, demonstrate the potential of new Rn measurement instruments and methods to quantify mass transport processes between forest canopies and the atmosphere. Gas exchange rates yield mean canopy air residence times ranging from minutes during turbulent daytime hours to greater than 12 h during calm nights. Rn is an effective tracer for net ecosystem exchange of CO₂ (CO₂ NEE) during calm, night‐time hours when eddy covariance‐based NEE measurements are less certain because of low atmospheric turbulence. Rn‐derived night‐time CO₂ NEE (9.00±0.99 μmol m^?2 s^?1 in the wet season, 6.39±0.59 in the dry season) was significantly higher than raw uncorrected, eddy covariance‐derived CO₂ NEE (5.96±0.51 wet season, 5.57±0.53 dry season), but agrees with corrected eddy covariance results (8.65±1.07 wet season, 6.56±0.73 dry season) derived by filtering out lower NEE values obtained during calm periods using independent meteorological criteria. The Rn CO₂ results suggest that uncorrected eddy covariance values underestimate night‐time CO₂ loss at this site. If generalizable to other sites, these observations indicate that previous reports of strong net CO₂ uptake in Amazonian terra firme forest may be overestimated.     

The annual cycles of CO2 and H2O exchange over a northern mixed forest as observed from a very tall tower

We present the annual patterns of net ecosystem‐atmosphere exchange (NEE) of CO₂ and H2O observed from a 447 m tall tower sited within a mixed forest in northern Wisconsin, USA. The methodology for determining NEE from eddy‐covariance flux measurements at 30, 122 and 396 m above the ground, and from CO₂ mixing ratio measurements at 11, 30, 76, 122, 244 and 396 m is described. The annual cycle of CO₂ mixing ratio in the atmospheric boundary layer (ABL) is also discussed, and the influences of local NEE and large‐scale advection are estimated. During 1997 gross ecosystem productivity (947?18 g C m^?2 yr^?1), approximately balanced total ecosystem respiration (963±19 g C m^?2 yr^?1), and NEE of CO₂ was close to zero (16±19 g C m^?2 yr^?1 emitted into the atmosphere). The error bars represent the standard error of the cumulative daily NEE values. Systematic errors are also assessed. The identified systematic uncertainties in NEE of CO₂ are less than 60 g C m^?2 yr^?1. The seasonal pattern of NEE of CO₂ was highly correlated with leaf‐out and leaf‐fall, and soil thaw and freeze, and was similar to purely deciduous forest sites. The mean daily NEE of CO₂ during the growing season (June through August) was ?1.3 g C m^?2 day^?1, smaller than has been reported for other deciduous forest sites. NEE of water vapor largely followed the seasonal pattern of NEE of CO₂, with a lag in the spring when water vapor fluxes increased before CO₂ uptake. In general, the Bowen ratios were high during the dormant seasons and low during the growing season. Evapotranspiration normalized by potential evapotranspiration showed the opposite pattern. The seasonal course of the CO₂ mixing ratio in the ABL at the tower led the seasonal pattern of NEE of CO₂ in time: in spring, CO₂ mixing ratios began to decrease prior to the onset of daily net uptake of CO₂ by the forest, and in fall mixing ratios began to increase before the forest became a net source for CO₂ to the atmosphere. Transport as well as local NEE of CO₂ are shown to be important components of the ABL CO₂ budget at all times of the year.     

Canopy-scale δ13C of photosynthetic and respiratory CO2 fluxes: observations in forest biomes across the United States

The δ¹³C values 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 photosynthetic ¹³C discrimination by terrestrial vegetation (Δ_A), and depends on δ¹³C values of respired CO₂ fluxes (δ¹³C_R). 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 of Δ_A can be successfully derived in terrestrial ecosystems. We also present the first weekly dataset of seasonal variations in δ¹³C_R from dominant forest ecosystems in the United States between 2001 and 2003. Our observations indicate considerable summer‐time variation in the weekly value of δ¹³C_R 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 of δ¹³C_R showed a smaller range (2–3‰), which appeared to significantly correlate with soil water availability. Values of δ¹³C_R were less variable during the growing season at the deciduous forest (Harvard Forest). We suggest that the negative correlation between δ¹³C_R 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 in δ¹³C_R and Δ_A could be of sufficient magnitude globally to impact partitioning calculations of CO₂ sinks between oceanic and terrestrial compartments.     

Ecophysiological controls over the net ecosystem exchange of mountain spruce stand. Comparison of the response in direct vs. diffuse solar radiation

Cloud cover increases the proportion of diffuse radiation reaching the Earth's surface and affects many microclimatic factors such as temperature, vapour pressure deficit and precipitation. We compared the relative efficiencies of canopy photosynthesis to diffuse and direct photosynthetic photon flux density (PPFD) for a Norway spruce forest (25‐year‐old, leaf area index 11 m² m⁻²) during two successive 7‐day periods in August. The comparison was based on the response of net ecosystem exchange (NEE) of CO₂ to PPFD. NEE and stomatal conductance at the canopy level (G_canopy) was estimated from half‐hourly eddy‐covariance measurements of CO₂ and H₂O fluxes. In addition, daily courses of CO₂ assimilation rate (A_N) and stomatal conductance (G_s) at shoot level were measured using a gas‐exchange technique applied to branches of trees. The extent of spectral changes in incident solar radiation was assessed using a spectroradiometer. We found significantly higher NEE (up to 150%) during the cloudy periods compared with the sunny periods at corresponding PPFDs. Prevailing diffuse radiation under the cloudy days resulted in a significantly lower compensation irradiance (by ca. 50% and 70%), while apparent quantum yield was slightly higher (by ca. 7%) at canopy level and significantly higher (by ca. 530%) in sun‐acclimated shoots. The main reasons for these differences appear to be (1) more favourable microclimatic conditions during cloudy periods, (2) stimulation of photochemical reactions and stomatal opening via an increase of blue/red light ratio, and (3) increased penetration of light into the canopy and thus a more equitable distribution of light between leaves. Our analyses identified the most important reason of enhanced NEE under cloudy sky conditions to be the effective penetration of diffuse radiation to lower depths of the canopy. This subsequently led to the significantly higher solar equivalent leaf area compared with the direct radiation. Most of the leaves in such dense canopy are in deep shade, with marginal or negative carbon balances during sunny days. These findings show that the energy of diffuse, compared with direct, solar radiation is used more efficiently in assimilation processes at both leaf and canopy levels.     

Carbon cycling in temperate grassland under elevated temperature

An increase in mean soil surface temperature has been observed over the last century, and it is predicted to further increase in the future. The effect of increased temperature on ecosystem carbon fluxes in a permanent temperate grassland was studied in a long‐term (6 years) field experiment, using multiple temperature increments induced by IR lamps. Ecosystem respiration (R‐eco) and net ecosystem exchange (NEE) were measured and modeled by a modified Lloyd and Taylor model including a soil moisture component for R‐eco (average R² of 0.78) and inclusion of a photosynthetic component based on temperature and radiation for NEE (R² = 0.65). Modeled NEE values ranged between 2.3 and 5.3 kg CO₂ m^?2 year^?1, depending on treatment. An increase of 2 or 3°C led to increased carbon losses, lowering the carbon storage potential by around 4 tonnes of C ha^?1 year^?1. The majority of significant NEE differences were found during night‐time compared to daytime. This suggests that during daytime the increased respiration could be offset by an increase in photosynthetic uptake. This was also supported by differences in δ¹³C and δ¹⁸O, indicating prolonged increased photosynthetic activity associated with the higher temperature treatments. However, this increase in photosynthesis was insufficient to counteract the 24 h increase in respiration, explaining the higher CO₂ emissions due to elevated temperature.     

Coupling between carbon cycling and climate in a high-elevation,subalpine forest: a model-data fusion analysis

Fundamental questions exist about the effects of climate on terrestrial net ecosystem CO₂ exchange (NEE), despite a rapidly growing body of flux observations. One strategy to clarify ecosystem climate–carbon interactions is to partition NEE into its component fluxes, gross ecosystem CO₂ exchange (GEE) and ecosystem respiration (R _E), and evaluate the responses to climate of each component flux. We separated observed NEE into optimized estimates of GEE and R _E using an ecosystem process model combined with 6 years of continuous flux data from the Niwot Ridge AmeriFlux site. In order to gain further insight into the processes underlying NEE, we partitioned R _E into its components: heterotrophic (R _H) and autotrophic (R _A) respiration. We were successful in separating GEE and R _E, but less successful in accurately partitioning R _E into R _A and R _H. Our failure in the latter was due to a lack of adequate contrasts in the assimilated data set to distinguish between R _A and R _H. We performed most model runs at a twice-daily time step. Optimizing on daily-aggregated data severely degraded the model’s ability to separate GEE and R _E. However, we gained little benefit from using a half-hourly time step. The model-data fusion showed that most of the interannual variability in NEE was due to variability in GEE, and not R _E. In contrast to several previous studies in other ecosystems, we found that longer growing seasons at Niwot Ridge were correlated with less net CO₂ uptake, due to a decrease of available snow-melt water during the late springtime photosynthetic period. Warmer springtime temperatures resulted in increased net CO₂ uptake only if adequate moisture was available; when warmer springtime conditions led into mid-summer drought, the annual net uptake declined.     

Contribution of volatile organic compound fluxes to the ecosystem carbon budget of a poplar short‐rotation plantation

Biogenic volatile organic compounds (BVOCs) are major precursors of both ozone and secondary organic aerosols (SOA) in the troposphere and represent a non‐negligible portion of the carbon fixed by primary producers, but long‐term ecosystem‐scale measurements of their exchanges with the atmosphere are lacking. In this study, the fluxes of 46 ions corresponding to 36 BVOCs were continuously monitored along with the exchanges of mass (carbon dioxide and water vapor) and energy (sensible and latent heat) for an entire year in a poplar (Populus) short‐rotation crop (SRC), using the eddy covariance methodology. BVOC emissions mainly consisted of isoprene, acetic acid, and methanol. Total net BVOC emissions were 19.20 kg C ha^?1 yr^?1, which represented 0.63% of the net ecosystem exchange (NEE), resulting from ?23.59 Mg C ha^?1 yr^?1 fixed as CO₂ and 20.55 Mg C ha^?1 yr^?1 respired as CO₂ from the ecosystem. Isoprene emissions represented 0.293% of NEE, being emitted at a ratio of 1 : 1709 mol isoprene per mol of CO₂ fixed. Based on annual ecosystem‐scale measurements, this study quantified for the first time that BVOC carbon emissions were lower than previously estimated in other studies (0.5–2% of NEE) on poplar trees. Furthermore, the seasonal and diurnal emission patterns of isoprene, methanol, and other BVOCs provided a better interpretation of the relationships with ecosystem CO₂ and water vapor fluxes, with air temperature, vapor pressure deficit, and photosynthetic photon flux density.     

Soil CO2 efflux in contrasting boreal deciduous and coniferous stands and its contribution to the ecosystem carbon balance

Similar nonsteady‐state automated chamber systems were used to measure and partition soil CO₂ efflux in contrasting deciduous (trembling aspen) and coniferous (black spruce and jack pine) stands located within 100 km of each other near the southern edge of the Boreal forest in Canada. The stands were exposed to similar climate forcing in 2003, including marked seasonal variations in soil water availability, which provided a unique opportunity to investigate the influence of climate and stand characteristics on soil CO₂ efflux and to quantify its contribution to the net ecosystem CO₂ exchange (NEE) as measured with the eddy‐covariance technique. Partitioning of soil CO₂ efflux between soil respiration (including forest‐floor vegetation) and forest‐floor photosynthesis showed that short‐ and long‐term temporal variations of soil CO₂ efflux were related to the influence of (1) soil temperature and water content on soil respiration and (2) below‐canopy light availability, plant water status and forest‐floor plant species composition on forest‐floor photosynthesis. Overall, the three stands were weak to moderate sinks for CO₂ in 2003 (NEE of ?103, ?80 and ?28 g C m^?2 yr^?1 for aspen, black spruce and jack pine, respectively). Forest‐floor respiration accounted for 86%, 73% and 75% of annual ecosystem respiration, in the three respective stands, while forest‐floor photosynthesis contributed to 11% and 14% of annual gross ecosystem photosynthesis in the black spruce and jack pine stands, respectively. The results emphasize the need to perform concomitant measurements of NEE and soil CO₂ efflux at longer time scales in different ecosystems in order to better understand the impacts of future interannual climate variability and vegetation dynamics associated with climate change on each component of the carbon balance.     

Exposure to an enriched CO2 atmosphere alters carbon assimilation and allocation in a pine forest ecosystem

We linked a leaf-level CO₂ assimilation model with a model that accounts for light attenuation in the canopy and measurements of sap-flux-based canopy conductance into a new canopy conductance-constrained carbon assimilation (4C-A) model. We estimated canopy CO₂ uptake (A_nC) at the Duke Forest free-air CO₂ enrichment (FACE) study. Rates of A_nC estimated from the 4C-A model agreed well with leaf gas exchange measurements (A_net) in both CO₂ treatments. Under ambient conditions, monthly sums of net CO₂ uptake by the canopy (A_nC) were 13% higher than estimates based on eddy-covariance and chamber measurements. Annual estimates of A_nC were only 3% higher than carbon (C) accumulations and losses estimated from ground-based measurements for the entire stand. The C budget for the Pinus taeda component was well constrained (within 1% of ground-based measurements). Although the closure of the C budget for the broadleaf species was poorer (within 20%), these species are a minor component of the forest. Under elevated CO₂, the C used annually for growth, turnover, and respiration balanced only 80% of the A_nC. Of the extra 700 g C m⁻² a⁻¹ (1999 and 2000 average), 86% is attributable to surface soil CO₂ efflux. This suggests that the production and turnover of fine roots was underestimated or that mycorrhizae and rhizodeposition became an increasingly important component of the C balance. Under elevated CO₂, net ecosystem production increased by 272 g C m⁻² a⁻¹: 44% greater than under ambient CO₂. The majority (87%) of this C was sequestered in a moderately long-term C pool in wood, with the remainder in the forest floor–soil subsystem.     

Carbon exchange of a mature,naturally regenerated pine forest in north Florida

We used eddy covariance and biomass measurements to quantify the carbon (C) dynamics of a naturally regenerated longleaf pine/slash pine flatwoods ecosystem in north Florida for 4 years, July 2000 to June 2002 and 2004 to 2005, to quantify how forest type, silvicultural intensity and environment influence stand‐level C balance. Precipitation over the study periods ranged from extreme drought (July 2000–June 2002) to above‐average precipitation (2004 and 2005). After photosynthetic photon flux density (PPFD), vapor pressure deficit (VPD) >1.5 kPa and air temperature <10 °C were important constraints on daytime half‐hourly net CO₂ exchange (NEE_day) and reduced the magnitude of midday CO₂ exchange by >5 μmol CO₂ m^?2 s^?1. Analysis of water use efficiency indicated that stomatal closure at VPD>1.5 kPa moderated transpiration similarly in both drought and wet years. Night‐time exchange (NEE_night) was an exponential function of air temperature, with rates further modulated by soil moisture. Estimated annual net ecosystem production (NEP) was remarkably consistent among the four measurement years (range: 158–192 g C m^?2 yr^?1). In comparison, annual ecosystem C assimilation estimates from biomass measurements between 2000 and 2002 ranged from 77 to 136 g C m^?2 yr^?1. Understory fluxes accounted for approximately 25–35% of above‐canopy NEE over 24‐h periods, and 85% and 27% of whole‐ecosystem fluxes during night and midday (11:00–15:00 hours) periods, respectively. Concurrent measurements of a nearby intensively managed slash pine plantation showed that annual NEP was three to four times greater than that of the Austin Cary Memorial Forest, highlighting the importance of silviculture and management in regulating stand‐level C budgets.     

Evaporation and carbonic anhydrase activity recorded in oxygen isotope signatures of net CO2 fluxes from a Mediterranean soil

The oxygen stable isotope composition (δ¹⁸O) of CO₂ is a valuable tool for studying the gas exchange between terrestrial ecosystems and the atmosphere. In the soil, it records the isotopic signal of water pools subjected to precipitation and evaporation events. The δ¹⁸O of the surface soil net CO₂ flux is dominated by the physical processes of diffusion of CO₂ into and out of the soil and the chemical reactions during CO₂–H₂O equilibration. Catalytic reactions by the enzyme carbonic anhydrase, reducing CO₂ hydration times, have been proposed recently to explain field observations of the δ¹⁸O signatures of net soil CO₂ fluxes. How important these catalytic reactions are for accurately predicting large‐scale biosphere fluxes and partitioning net ecosystem fluxes is currently uncertain because of the lack of field data. In this study, we determined the δ¹⁸O signatures of net soil CO₂ fluxes from soil chamber measurements in a Mediterranean forest. Over the 3 days of measurements, the observed δ¹⁸O signatures of net soil CO₂ fluxes became progressively enriched with a well‐characterized diurnal cycle. Model simulations indicated that the δ¹⁸O signatures recorded the interplay of two effects: (1) progressive enrichment of water in the upper soil by evaporation, and (2) catalytic acceleration of the isotopic exchange between CO₂ and soil water, amplifying the contributions of ‘atmospheric invasion’ to net signatures. We conclude that there is a need for better understanding of the role of enzymatic reactions, and hence soil biology, in determining the contributions of soil fluxes to oxygen isotope signals in atmospheric CO₂.     

Environmental variation is directly responsible for short- but not long-term variation in forest-atmosphere carbon exchange

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, R_eco, and gross photosynthesis, P_gross) 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 R_eco and P_gross. 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 P_gross and R_eco (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 P_gross or R_eco     

Partitioning net carbon dioxide fluxes into photosynthesis and respiration using neural networks

The eddy covariance (EC) technique is used to measure the net ecosystem exchange (NEE) of CO₂ between ecosystems and the atmosphere, offering a unique opportunity to study ecosystem responses to climate change. NEE is the difference between the total CO₂ release due to all respiration processes (RECO), and the gross carbon uptake by photosynthesis (GPP). These two gross CO₂ fluxes are derived from EC measurements by applying partitioning methods that rely on physiologically based functional relationships with a limited number of environmental drivers. However, the partitioning methods applied in the global FLUXNET network of EC observations do not account for the multiple co‐acting factors that modulate GPP and RECO flux dynamics. To overcome this limitation, we developed a hybrid data‐driven approach based on combined neural networks (NN_C‐part). NN_C‐part incorporates process knowledge by introducing a photosynthetic response based on the light‐use efficiency (LUE) concept, and uses a comprehensive dataset of soil and micrometeorological variables as fluxes drivers. We applied the method to 36 sites from the FLUXNET2015 dataset and found a high consistency in the results with those derived from other standard partitioning methods for both GPP (R² > .94) and RECO (R² > .8). High consistency was also found for (a) the diurnal and seasonal patterns of fluxes and (b) the ecosystem functional responses. NN_C‐part performed more realistic than the traditional methods for predicting additional patterns of gross CO₂ fluxes, such as: (a) the GPP response to VPD, (b) direct effects of air temperature on GPP dynamics, (c) hysteresis in the diel cycle of gross CO₂ fluxes, (d) the sensitivity of LUE to the diffuse to direct radiation ratio, and (e) the post rain respiration pulse after a long dry period. In conclusion, NN_C‐part is a valid data‐driven approach to provide GPP and RECO estimates and complementary to the existing partitioning methods.     

Using ecosystem CO2 measurements to estimate the timing and magnitude of greenhouse gas mitigation potential of forest bioenergy

Forest bioenergy opportunities may be hindered by a long greenhouse gas (GHG) payback time. Estimating this payback time requires the quantification of forest‐atmosphere carbon exchanges, usually through process‐based simulation models. Such models are prone to large uncertainties, especially over long‐term carbon fluxes from dead organic matter pools. We propose the use of whole ecosystem field‐measured CO₂ exchanges obtained from eddy covariance flux towers to assess the GHG mitigation potential of forest biomass projects as a way to implicitly integrate all field‐level CO₂ fluxes and the inter‐annual variability in these fluxes. As an example, we perform the evaluation of a theoretical bioenergy project that uses tree stems as bioenergy feedstock and include multi‐year measurements of net ecosystem exchange (NEE) from forest harvest chronosequences in the boreal forest of Canada to estimate the time dynamics of ecosystem CO₂ exchanges following harvesting. Results from this approach are consistent with previous results using process‐based models and suggest a multi‐decadal payback time for our project. The time for atmospheric carbon debt repayment of bioenergy projects is highly dependent on ecosystem‐level CO₂ exchanges. The use of empirical NEE measurements may provide a direct evaluation of, or at least constraints on, the GHG mitigation potential of forest bioenergy projects.     

Modeling dynamics of stable carbon isotopic exchange between a boreal forest ecosystem and the atmosphere

Stable isotopes of CO₂ contain unique information on the biological and physical processes that exchange CO₂ between terrestrial ecosystems and the atmosphere. In this study, we developed an integrated modeling system to simulate dynamics of stable carbon isotope of CO₂, as well as moisture, energy, and momentum, between a boreal forest ecosystem and the atmosphere, as well as their transport/mixing processes through the convective boundary layer (CBL), using remotely sensed surface parameters to characterize the surface heterogeneity. It has the following characteristics: (i) it accounts for the influences of the CBL turbulent mixing and entrainment of the air aloft; (ii) it scales individual leaf‐level photosynthetic discrimination up to the whole canopy (Δ_canopy) through the separation of sunlit and shaded leaf groups; (iii) it has the capacity to examine the detailed interrelationships among plant water‐use efficiency, isotope discrimination, and vapor pressure deficit; and (iv) it has the potential to investigate how an ecosystem discriminates against ¹³C at various time and spatial scales. The monthly mean isotopic signatures of ecosystem respiration (i.e. δ¹³C_R) used for isotope flux calculation are retrieved from the nighttime flask data from the intensive campaigns (1998–2000) at 20 m level on Fraserdale tower, and the data from the growing season in 1999 are used for model validation. Both the simulated CO₂ mixing ratio and δ¹³C of CO₂ at the 20 m level agreed with the measurements well in different phases of the growing season. On a diurnal basis, the greatest photosynthetic discrimination at canopy level (i.e. Δ_canopy) occurred early morning and late afternoon with a varying range of 10–26‰. The diurnal variability of Δ_canopy was also associated with the phases of growing season and meteorological variables. The annual mean Δ_canopy in 1999 was computed to be 19.58‰. The monthly averages of Δ_canopy varied between 18.55‰ and 20.84‰ with a seasonal peak during the middle growing season. Because of the strong opposing influences of respired and photosynthetic fluxes on forest air (both CO₂ and ¹³CO₂) on both the diurnal and seasonal time scales, CO₂ was consistently enriched with the heavier ¹³C isotope (less negative δ¹³C) from July to October and depleted during the remaining months, whereas on a diurnal basis, CO₂ was enriched with the heavier ¹³C in the late afternoon and depleted in early morning. For the year 1999, the model results reveal that the boreal ecosystem in the vicinity of Fraserdale tower was a small sink with net uptake of 29.07 g ¹²C m^?2 yr^?1 and 0.34 g ¹³C m^?2 yr^?1.     

Comparison of the mass and energy exchange of a pasture and a mature transitional tropical forest of the southern Amazon Basin during a seasonal transition

This research utilized tower‐based eddy covariance to quantify the trends in net ecosystem mass (CO₂ and H₂O vapor) and energy exchange of important land‐cover types of NW Mato Grosso during the March–December 2002 seasonal transition. Measurements were made in a mature transitional (ecotonal) tropical forest near Sinop, Mato Grosso, and a cattle pasture near Cotriguaçú, Mato Grosso, located 500 km WNW of Sinop. Pasture net ecosystem CO₂ exchange (NEE) was considerably more variable than the forest NEE over the seasonal transition, and the pasture had significantly higher rates of maximum gross primary production in every season except the dry–wet season transition (September–October). The pasture also had significantly higher rates of whole‐ecosystem dark respiration than the forest during the wetter times of the year. Average (±95% CI) rates of total daily NEE during the March–December 2002 measurement period were 26±15 mmol m^?2 day^?1 for the forest (positive values indicate net CO₂ loss by the ecosystem) and ?38±26 mmol m^?2 day^?1 for the pasture. While both ecosystems partitioned more net radiation (R_n) into latent heat flux (L_e), the forest had significantly higher rates of L_e and lower rates of sensible heat flux (H) than the pasture; a trend that became more extreme during the onset of the dry season. Large differences in pasture and forest mass and energy exchange occurred even though seasonal variations in micrometeorology (air temperature, humidity, and radiation) were relatively similar for both ecosystems. While the short measurement period and lack of spatial replication limit the ability to generalize these results to pasture and forest regions of the Amazon Basin, these results suggest important differences in the magnitude and seasonal variation of NEE and energy partitioning for pasture and transitional tropical forest.