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Despite a rapid development of Nature-Based Solutions (NBS) for carbon removal in recent years, the methods for evaluating NBS still have certain gaps. We propose an approach based on a combination of remote sensing data and meteorological variables to reconstruct the spatiotemporal variation of net ecosystem exchange from eddy-covariance stations. A Lagrangian particle dispersion model was used for upscaling satellite images and flux towers. We trained data-driven models based on kernel methods separately for each selected land-cover class. The results suggest that the proposed approach to quantifying carbon exchange on a medium-to-large scale by blending eddy covariance flux data with moderate resolution satellite and weather data provides a set of key advantages over previously deployed methods: (1) scalability, achieved via the validation design based on a separate set of eddy covariance stations; (2) high spatial and temporal resolution thanks to the use of Landsat imagery; and (3) robust and accurate predictions due to improved data quality control, advanced machine learning techniques, and rigorous validation. The machine learning models yielded high cross-validation results. Stratification that uses separate Fluxnet stations for each fold of validation ensures that the models are accurate across the area covered by the Fluxnet sites. Overall, we present here a globally scaled technology for the land sector based on high resolution remote sensing imagery, meteorological variables, and direct carbon flux measurements of eddy covariance flux stations.

Land-atmosphere carbon exchange is known to be extremely heterogeneous in arctic ice-wedge polygonal tundra regions. In this study, a Kalman filter-based method was developed to estimate the spatio-temporal dynamics of daytime average net ecosystem exchange (NEEday) at 0.5-m resolution over a 550 m by 700 m study site. We integrated multi-scale, multi-type datasets, including normalized difference vegetation indices (NDVIs) obtained from a novel automated mobile sensor system (or tram system) and a greenness index map obtained from airborne imagery. We took advantage of the significant correlations between NDVI and NEEday identified based on flux chamber measurements. The weighted average of the estimated NEEday within the flux-tower footprint agreed with the flux tower data in term of its seasonal dynamics. We then evaluated the spatial variability of the growing season average NEEday, as a function of polygon geomorphic classes; i.e., the combination of polygon types—which are known to present different degradation stages associated with permafrost thaw—and microtopographic features (i.e., troughs, centers and rims). Our study suggests the importance of considering microtopographic features and their spatial coverage in computing spatially aggregated carbon exchange.

Across temperate North America, interannual variability (IAV) in gross primary production (GPP) and net ecosystem exchange (NEE) and their relationship with environmental drivers are poorly understood. Here, we examine IAV in GPP and NEE and their relationship to environmental drivers using two state-of-the-science flux products: NEE constrained by surface and space-based atmospheric CO2 measurements over 2010-2015 and satellite up-scaled GPP from FluxSat over 2001-2017. We show that the arid western half of temperate North America provides a larger contribution to IAV in GPP (104% of east) and NEE (127% of east) than the eastern half, in spite of smaller magnitude of annual mean GPP and NEE. This occurs because anomalies in western ecosystems are temporally coherent across the growing season leading to an amplification of GPP and NEE. In contrast, IAV in GPP and NEE in eastern ecosystems is dominated by seasonal compensation effects, associated with opposite responses to temperature anomalies in spring and summer. Terrestrial biosphere models in the MsTMIP ensemble generally capture these differences between eastern and western temperate North America, although there is considerable spread between models.

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 (NNC-part ). NNC-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. NNC-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, NNC-part is a valid data-driven approach to provide GPP and RECO estimates and complementary to the existing partitioning methods.

In the last few decades, temperatures in the Arctic have increased twice as much as the rest of the globe. As permafrost thaws in response to this warming, large amounts of soil organic matter may become vulnerable to decomposition. Microbial decomposition will release carbon (C) from permafrost soils, however, warmer conditions could also lead to enhanced plant growth and C uptake. Field and modeling studies show high uncertainty in soil and plant responses to climate change but there have been few studies that reconcile field and model data to understand differences and reduce uncertainty. Here, we evaluate gross primary productivity (GPP), ecosystem respiration (Reco), and net ecosystem C exchange (NEE) from eight years of experimental soil warming in moist acidic tundra against equivalent fluxes from the Community Land Model during simulations parameterized to reflect the field conditions associated with this manipulative field experiment. Over the eight-year experimental period, soil temperatures and thaw depths increased with warming in field observations and model simulations. However, the field and model results do not agree on warming effects on water table depth; warming created wetter soils in the field and drier soils in the models. In the field, initial increases in growing season GPP, Reco, and NEE to experimentally-induced permafrost thaw created a higher C sink capacity in the first years followed by a stronger C source in years six through eight. In contrast, both models predicted linear increases in GPP, Reco, and NEE with warming. The divergence of model results from field experiments reveals the role subsidence, hydrology, and nutrient cycling play in influencing the C flux responses to permafrost thaw, a complexity that the models are not structurally able to predict, and highlight challenges associated with projecting C cycle dynamics across the Arctic.

As the lifetime of regional flux networks approach twenty years, there is a growing number of papers that have published long term records (5 years or more) of net carbon fluxes between ecosystems and the atmosphere. Unanswered questions from this body of work are: 1) how variable are carbon fluxes on a year to year basis?; 2) what are the biophysical factors that may cause interannual variability and/or temporal trends in carbon fluxes?; and 3) how does the biophysical control on this carbon flux variability differ by climate and ecological spaces? To address these questions, we surveyed published data from 59 sites that reported on five or more years of continuous measurements, yielding 544 site-years of data.We found that the standard deviation of the interannual variability in net ecosystem carbon exchange (162gCm−2y−1) is large relative to its population mean (−200gCm−2 y−1). Broad-leaved evergreen forests and crops experienced the greatest absolute variability in interannual net carbon exchange (greater than ±300gCm−2y−1) and boreal evergreen forests and maritime wetlands were among the least variable (less than ±40 gCm−2y−1).A disproportionate fraction of the yearly variability in net ecosystem exchange was associated with biophysical factors that modulated ecosystem photosynthesis rather than ecosystem respiration. Yet, there was appreciable and statistically significant covariance between ecosystem photosynthesis and respiration. Consequently, biophysical conditions that conspired to increase ecosystem photosynthesis to from one year to the next were associated with an increase in ecosystem respiration, and vice versa; on average, the year to year change in respiration was 40% as large as the year to year change in photosynthesis. The analysis also identified sets of ecosystems that are on the verge of switching from being carbon sinks to carbon sources. These include sites in the Arctic tundra, the evergreen forests in the Pacific northwest and some grasslands, where year to year changes in respiration are outpacing those in photosynthesis.While a select set of climatic and ecological factors (e.g. light, rainfall, temperature, phenology) played direct and indirect roles on this variability, their impact differed conditionally, as well as by climate and ecological spaces. For example, rainfall had both positive and negative effects. Deficient rainfall caused a physiological decline in photosynthesis in temperate and semi-arid regions. Too much rain, in the humid tropics, limited photosynthesis by limiting light. In peatlands and tundra, excess precipitation limited ecosystem respiration when it raised the water table to the surface. For deciduous forests, warmer temperatures lengthened the growing season, increasing photosynthesis, but this effect also increased soil respiration.Finally, statistical analysis was performed to evaluate the detection limit of trends; we computed the confidence intervals of trends in multi-year carbon fluxes that need to be resolved to conclude whether the differences are to be attributed to randomness or biophysical forcings. Future studies and reports on interannual variations need to consider the role of the duration of the time series on random errors when quantifying potential trends and extreme events.

Clouds and aerosols increase the fraction of global solar irradiance that is diffuse light. This phenomenon is known to increase the photosynthetic light use efficiency (LUE) of closed-canopy vegetation by redistributing photosynthetic photon flux density (400–700nm) from saturated, sunlit leaves at the top of the canopy, to shaded leaves deeper in the canopy. We combined a process-based carbon cycle model with 10 years of eddy covariance carbon flux measurements and other ancillary data sets to assess 1) how this LUE enhancement influences interannual variation in carbon uptake, and 2) how errors in modeling diffuse fraction affect predictions of carbon uptake. Modeled annual gross primary productivity (GPP) increased by ≈0.94% when observed levels of diffuse fraction were increased by 0.01 (holding total irradiance constant). The sensitivity of GPP to increases in diffuse fraction was highest when the diffuse fraction was low to begin with, and lowest when the diffuse fraction was already high. Diffuse fraction also explained significantly more of the interannual variability of modeled net ecosystem exchange (NEE), than did total irradiance. Two tested radiation partitioning models yielded over- and underestimates of diffuse fraction at our site, which propagated to over- and underestimates of annual NEE, respectively. Our findings highlight the importance of incorporating LUE enhancement under diffuse light into models of global primary production, and improving models of diffuse fraction.

Aim: Terrestrial ecosystems have sequestered, on average, the equivalent of 30% of anthropogenic carbon (C) emissions during the past decades, but annual sequestration varies from year to year. For effective C management, it is imperative to develop a predictive understanding of the interannual variability (IAV) of terrestrial net ecosystem C exchange (NEE). Location: Global terrestrial ecosystems. Methods: We conducted a comprehensive review to examine the IAV of NEE at global, regional and ecosystem scales. Then we outlined a conceptual framework for understanding how anomalies in climate factors impact ecological processes of C cycling and thus influence the IAV of NEE through biogeochemical regulation. Results: The phenomenon of IAV in land NEE has been ubiquitously observed at global, regional and ecosystem scales. Global IAV is often attributable to either tropical or semi-arid regions, or to some combination thereof, which is still under debate. Previous studies focus on identifying climate factors as driving forces of IAV, whereas biological mechanisms underlying the IAV of ecosystem NEE are less clear. We found that climate anomalies affect the IAV of NEE primarily through their differential impacts on ecosystem C uptake and respiration. Moreover, recent studies suggest that the carbon uptake period makes less contribution than the carbon uptake amplitude to IAV in NEE. Although land models incorporate most processes underlying IAV, their efficacy to predict the IAV in NEE remains low. Main conclusions: To improve our ability to predict future IAV of the terrestrial C cycle, we have to understand biological mechanisms through which anomalies in climate factors cause the IAV of NEE. Future research needs to pay more attention not only to the differential effects of climate anomalies on photosynthesis and respiration but also to the relative importance of the C uptake period and amplitude in causing the IAV of NEE. Ultimately, we need multiple independent approaches, such as benchmark analysis, data assimilation and time-series statistics, to integrate data, modelling frameworks and theory to improve our ability to predict future IAV in the terrestrial C cycle.

Rapid Arctic warming is expected to increase global greenhouse gas concentrations as permafrost thaw exposes immense stores of frozen carbon (C) to microbial decomposition. Permafrost thaw also stimulates plant growth, which could offset C loss. Using data from 7 years of experimental Air and Soil warming in moist acidic tundra, we show that Soil warming had a much stronger effect on CO2 flux than Air warming. Soil warming caused rapid permafrost thaw and increased ecosystem respiration (Reco ), gross primary productivity (GPP), and net summer CO2 storage (NEE). Over 7 years Reco , GPP, and NEE also increased in Control (i.e., ambient plots), but this change could be explained by slow thaw in Control areas. In the initial stages of thaw, Reco , GPP, and NEE increased linearly with thaw across all treatments, despite different rates of thaw. As thaw in Soil warming continued to increase linearly, ground surface subsidence created saturated microsites and suppressed Reco , GPP, and NEE. However Reco and GPP remained high in areas with large Eriophorum vaginatum biomass. In general NEE increased with thaw, but was more strongly correlated with plant biomass than thaw, indicating that higher Reco in deeply thawed areas during summer months was balanced by GPP. Summer CO2 flux across treatments fit a single quadratic relationship that captured the functional response of CO2 flux to thaw, water table depth, and plant biomass. These results demonstrate the importance of indirect thaw effects on CO2 flux: plant growth and water table dynamics. Nonsummer Reco models estimated that the area was an annual CO2 source during all years of observation. Nonsummer CO2 loss in warmer, more deeply thawed soils exceeded the increases in summer GPP, and thawed tundra was a net annual CO2 source.

Global modeling efforts indicate semiarid regions dominate the increasing trend and interannual variation of net CO2 exchange with the atmosphere, mainly driven by water availability. Many semiarid regions are expected to undergo climatic drying, but the impacts on net CO2 exchange are poorly understood due to limited semiarid flux observations. Here we evaluated 121 site-years of annual eddy covariance measurements of net and gross CO2 exchange (photosynthesis and respiration), precipitation, and evapotranspiration (ET) in 21 semiarid North American ecosystems with an observed range of 100 - 1000 mm in annual precipitation and records of 4-9 years each. In addition to evaluating spatial relationships among CO2 and water fluxes across sites, we separately quantified site-level temporal relationships, representing sensitivity to interannual variation. Across the climatic and ecological gradient, photosynthesis showed a saturating spatial relationship to precipitation, whereas the photosynthesis-ET relationship was linear, suggesting ET was a better proxy for water available to drive CO2 exchanges after hydrologic losses. Both photosynthesis and respiration showed similar site-level sensitivity to interannual changes in ET among the 21 ecosystems. Furthermore, these temporal relationships were not different from the spatial relationships of long-term mean CO2 exchanges with climatic ET. Consequently, a hypothetical 100-mm change in ET, whether short term or long term, was predicted to alter net ecosystem production (NEP) by 64 gCm(-2) yr(-1). Most of the unexplained NEP variability was related to persistent, site-specific function, suggesting prioritization of research on slow-changing controls. Common temporal and spatial sensitivity to water availability increases our confidence that site-level responses to interannual weather can be extrapolated for prediction of CO2 exchanges over decadal and longer timescales relevant to societal response to climate change.

Climatic variables not only directly affect the interannual variability (IAV) in net ecosystem exchange of CO2 (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.

Climatic variables not only directly affect the interannual variability (IAV) in net ecosystem exchange of CO2 (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.

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

Invasive dense-flowered cordgrass (Spartina densiflora) is impacting the primary productivity of Humboldt Bay salt marshes.

Disturbances are important for renewal of North American forests. Here we summarize more than 180 site years of eddy covariance measurements of carbon dioxide flux made at forest chronosequences in North America. The disturbances included stand-replacing fire (Alaska, Arizona, Manitoba, and Saskatchewan) and harvest (British Columbia, Florida, New Brunswick, Oregon, Quebec, Saskatchewan, and Wisconsin) events, insect infestations (gypsy moth, forest tent caterpillar, and mountain pine beetle), Hurricane Wilma, and silvicultural thinning (Arizona, California, and New Brunswick). Net ecosystem production (NEP) showed a carbon loss from all ecosystems following a stand-replacing disturbance, becoming a carbon sink by 20 years for all ecosystems and by 10 years for most. Maximum carbon losses following disturbance (g C m−2y−1) ranged from 1270 in Florida to 200 in boreal ecosystems. Similarly, for forests less than 100 years old, maximum uptake (g C m−2y−1) was 1180 in Florida mangroves and 210 in boreal ecosystems. More temperate forests had intermediate fluxes. Boreal ecosystems were relatively time invariant after 20 years, whereas western ecosystems tended to increase in carbon gain over time. This was driven mostly by gross photosynthetic production (GPP) because total ecosystem respiration (ER) and heterotrophic respiration were relatively invariant with age. GPP/ER was as low as 0.2 immediately following stand-replacing disturbance reaching a constant value of 1.2 after 20 years. NEP following insect defoliations and silvicultural thinning showed lesser changes than stand-replacing events, with decreases in the year of disturbance followed by rapid recovery. NEP decreased in a mangrove ecosystem following Hurricane Wilma because of a decrease in GPP and an increase in ER.

The oxidative ratio (OR) of the net ecosystem carbon balance is the ratio of net O2 and CO2 fluxes resulting from photosynthesis, respiration, decomposition, and other lateral and vertical carbon flows. The OR of the terrestrial biosphere must be well characterized to accurately estimate the terrestrial CO2 sink using atmospheric measurements of changing O2 and CO2 levels. To estimate the OR of the terrestrial biosphere, measurements are needed of changes in the OR of aboveground and belowground carbon pools associated with decadal timescale disturbances (e.g., land use change and fire). The OR of aboveground pools can be measured using conventional approaches including elemental analysis. However, measuring the OR of soil carbon pools is technically challenging, and few soil OR data are available. In this paper we test three solid-state nuclear magnetic resonance (NMR) techniques for measuring soil OR, all based on measurements of the closely related parameter, organic carbon oxidation state (Cox). Two of the three techniques make use of a molecular mixing model which converts NMR spectra into concentrations of a standard suite of biological molecules of known Cox. The third technique assigns Cox values to each peak in the NMR spectrum. We assess error associated with each technique using pure chemical compounds and plant biomass standards whose Cox and OR values can be directly measured by elemental analyses. The most accurate technique, direct polarization solid-state 13C NMR with the molecular mixing model, agrees with elemental analyses to ±0.036 Cox units (±0.009 OR units). Using this technique, we show a large natural variability in soil Cox and OR values. Soil Cox values have a mean of −0.26 and a range from −0.45 to 0.30, corresponding to OR values of 1.08 ± 0.06 and a range from 0.96 to 1.22. We also estimate the OR of the carbon flux from a boreal forest fire. Analysis of soils from nearby intact soil profiles imply that soil carbon losses associated with the fire had an OR of 1.091 (±0.003). Fire appears to be a major factor driving the soil C pool to higher oxidation states and lower OR values. Episodic fluxes caused by disturbances like fire may have substantially different ORs from ecosystem respiration fluxes and therefore should be better quantified to reduce uncertainties associated with our understanding of the global atmospheric carbon budget.

Degree of oxidation of organic carbon (Cox) is a fundamental property of the carbon cycle, reflecting the synthesis and decomposition of natural organic matter. Cox is also related to ecosystem oxidative ratio (OR), the molar ratio of O2 to CO2 fluxes associated with net ecosystem exchange (NEE). Here we compare two methods for measuring Cox and OR: (1) %C, %H, %N, and %O elemental analysis, and (2) heat of combustion (ΔHc) measured by means of bomb calorimetry coupled with %C elemental analysis (hereafter referred to as calorimetry). Compared with %C, %N, %H, and %O elemental analysis, calorimetry generates Cox and OR data more rapidly and cheaply. However, calorimetric measurements yield less accurate Cox and OR data. We additionally report Cox and OR data for a pair of biomass standards and a suite of biomass samples. The OR values we measured in these samples were less variable than OR data reported in the literature (generated by simultaneous measurement of ecosystem O2 and CO2 gas mixing ratios). Our biomass OR values had a mean of 1.03 and range of 0.99–1.06. These estimates are lower than the OR value of 1.10 that is often used to partition uptake of fossil fuel CO2 between the ocean and the terrestrial biosphere.

Understanding how changes in the boreal fire regime will affect high latitude climate requires knowledge of the sensitivity of the surface energy budget to shifts in vegetation cover. We measured components of the surface energy budget in three ecosystems that were part of a fire chronosequence in interior Alaska for 3 years. Our sites were within the perimeter of stand-replacing fires that occurred in 1999, 1987, and ∼1920 (hereafter referred to as the 1999-burn, the 1987-burn, and the control). Vegetation cover consisted primarily of sparse short grasses at the 1999-burn, aspen and willow (deciduous trees and shrubs) at the 1987-burn, and black spruce (evergreen conifer trees) at the control. Averaged over the 3 years of our study, annual net radiation decreased by approximately 25% at the 1999-burn and 30% at the 1987-burn, relative to the control. Sensible heat decreased by an even larger amount, by approximately 57% for the 1999-burn and 44% for the 1987-burn as compared with the control. Climate during spring and summer varied considerably among the 3 years. The three stands responded differently to this climate variability with consequences for surface energy exchange. As a result of earlier snow cover loss in 2003 and 2004, net radiation during spring increased substantially in the recently disturbed stands, but not in the control. In response to a sustained summer drought in 2004, latent heat decreased more in the 1987-burn during August than in the control. Our results imply that a shift in plant functional types expected to accompany increases in boreal fire activity may amplify interannual climate variability during both spring and summer.

Observations of the column-averaged dry molar mixing ratio of CO2 above both Park Falls, Wisconsin and Kitt Peak, Arizona, together with partial columns derived from aircraft profiles over Eurasia and North America are used to estimate the seasonal integral of net ecosystem exchange (NEE) between the atmosphere and the terrestrial biosphere in the Northern Hemisphere. We find that NEE is ∼25% larger than predicted by the Carnegie Ames Stanford Approach (CASA) model. We show that the estimates of NEE may have been biased low by too weak vertical mixing in the transport models used to infer seasonal changes in Northern Hemisphere CO2 mass from the surface measurements of CO2 mixing ratio.

We present a decadal (1994-2004) record of carbon dioxide flux in a 160-year-old black spruce forest/veneer bog complex in central Manitoba, Canada. The ecosystem shifted from a source (+41 g Cm-2, 1995) to a sink (-21 g C m-2, 2004) of CO2 over the decade, with an average net carbon balance near zero. Annual mean temperatures increased 1-2° during the period, consistent with the decadal trend across the North American boreal biome. We found that ecosystem carbon exchange responded strongly to air temperature, moisture status, potential evapotranspiration, and summertime solar radiation. The seasonal cycle of ecosystem respiration significantly lagged that of photosynthesis, limited by the rate of soil thaw and the slow drainage of the soil column. Factors acting over long time scales, especially water table depth, strongly influenced the carbon budget on annual time scales. Net uptake was enhanced and respiration inhibited by multiple years of rainfall in excess of evaporative demand. Contrary to expectations, we observed no correlation between longer growing seasons and net uptake, possibly because of offsetting increases in ecosystem respiration. The results indicate that the interactions between soil thaw and water table depth provide critical controls on carbon exchange in boreal forests underlain by peat, on seasonal to decadal time scales, and these factors must be simulated in terrestrial biosphere models to predict response of these regions to future climate. © 2007 Blackwell Publishing Ltd.

Recent projections of climatic change have focused a great deal of scientific and public attention on patterns of carbon (C) cycling as well as its controls, particularly the factors that determine whether an ecosystem is a net source or sink of atmospheric carbon dioxide (CO2). Net ecosystem production (NEP), a central concept in C-cycling research, has been used by scientists to represent two different concepts. We propose that NEP be restricted to just one of its two original definitions-the imbalance between gross primary production (GPP) and ecosystem respiration (ER). We further propose that a new term-net ecosystem carbon balance (NECB)-be applied to the net rate of C accumulation in (or loss from [negative sign]) ecosystems. Net ecosystem carbon balance differs from NEP when C fluxes other than C fixation and respiration occur, or when inorganic C enters or leaves in dissolved form. These fluxes include the leaching loss or lateral transfer of C from the ecosystem; the emission of volatile organic C, methane, and carbon monoxide; and the release of soot and CO2 from fire. Carbon fluxes in addition to NEP are particularly important determinants of NECB over long time scales. However, even over short time scales, they are important in ecosystems such as streams, estuaries, wetlands, and cities. Recent technological advances have led to a diversity of approaches to the measurement of C fluxes at different temporal and spatial scales. These approaches frequently capture different components of NEP or NECB and can therefore be compared across scales only by carefully specifying the fluxes included in the measurements. By explicitly identifying the fluxes that comprise NECB and other components of the C cycle, such as net ecosystem exchange (NEE) and net biome production (NBP), we can provide a less ambiguous framework for understanding and communicating recent changes in the global C cycle.

We developed an individual-based stochastic-empirical model to simulate the carbon dynamics of live and dead trees in a Central Amazon forest near Manaus, Brazil. The model is based on analyses of extensive field studies carried out on permanent forest inventory plots, and syntheses of published studies. New analyses included: (1) growth suppression of small trees, (2) maximum size (trunk base diameter) for 220 tree species, (3) the relationship between growth rate and wood density, and (4) the growth response of surviving trees to catastrophic mortality (from logging). The model simulates a forest inventory plot, and tracks recruitment, growth, and mortality of live trees, decomposition of dead trees (coarse litter), and how these processes vary with changing environmental conditions. Model predictions were tested against aggregated field data, and also compared with independent measurements including maximum tree age and coarse litter standing stocks. Spatial analyses demonstrated that a plot size of approximately 10 ha was required to accurately measure wood (live and dead) carbon balance. With the model accurately predicting relevant pools and fluxes, a number of model experiments were performed to predict forest carbon balance response to perturbations including: (1) increased productivity due to CO2 fertilization, (2) a single semi-catastrophic (10%) mortality event, (3) increased recruitment and mortality (turnover) rates, and (4) the combined effects of increased turnover, increased tree growth rates, and decreased mean wood density of new recruits. Results demonstrated that carbon accumulation over the past few decades observed on tropical forest inventory plots (approximately 0.5 Mg C ha(-1) year(-1)) is not likely caused by CO2 fertilization. A maximum 25% increase in woody tissue productivity with a doubling of atmospheric CO2 only resulted in an accumulation rate of 0.05 Mg C ha(-1) year(-1) for the period 1980-2020 for a Central Amazon forest, or an order of magnitude less than observed on the inventory plots. In contrast, model parameterization based on extensive data from a logging experiment demonstrated a rapid increase in tree growth following disturbance, which could be misinterpreted as carbon sequestration if changes in coarse litter stocks were not considered. Combined results demonstrated that predictions of changes in forest carbon balance during the twenty-first century are highly dependent on assumptions of tree response to various perturbations, and underscores the importance of a close coupling of model and field investigations.

Understanding how tropical forest carbon balance will respond to global change requires knowledge of individual heterotrophic and autotrophic respiratory sources, together with factors that control respiratory variability. We measured leaf, live wood, and soil respiration, along with additional environmental factors over a 1-yr period in a Central Amazon terra firme forest. Scaling these fluxes to the ecosystem, and combining our data with results from other studies, we estimated an average total ecosystem respiration (Reco) of 7.8 μmol·m−2·s−1. Average estimates (per unit ground area) for leaf, wood, soil, total heterotrophic, and total autotrophic respiration were 2.6, 1.1, 3.2, 5.6, and 2.2 μmol·m−2·s−1, respectively. Comparing autotrophic respiration with net primary production (NPP) estimates indicated that only ∼30% of carbon assimilated in photosynthesis was used to construct new tissues, with the remaining 70% being respired back to the atmosphere as autotrophic respiration. This low ecosystem carbon use efficiency (CUE) differs considerably from the relatively constant CUE of ∼0.5 found for temperate forests. Our Reco estimate was comparable to the above-canopy flux (Fac) from eddy covariance during defined sustained high turbulence conditions (when presumably Fac = Reco) of 8.4 (95% ci = 7.5– 9.4). Multiple regression analysis demonstrated that ∼50% of the nighttime variability in Fac was accounted for by friction velocity (u*, a measure of turbulence) variables. After accounting for u* variability, mean Fac varied significantly with seasonal and daily changes in precipitation. A seasonal increase in precipitation resulted in a decrease in Fac, similar to our soil respiration response to moisture. The effect of daily changes in precipitation was complex: precipitation after a dry period resulted in a large increase in Fac, whereas additional precipitation after a rainy period had little effect. This response was similar to that of surface litter (coarse and fine), where respiration is greatly reduced when moisture is limiting, but increases markedly and quickly saturates with an increase in moisture.

Fluxes of CO2, water vapor, and sensible heat were measured by the eddy covariance method above a young ponderosa pine plantation in the Sierra Nevada Mountains (CA) over two growing seasons (1 June-10 September 1997 and 1 May-30 October 1998). The Mediterranean-type climate of California is characterized by a protracted summer drought, with precipitation occurring mainly from October through May. While drought stress increased continuously over both summer growing seasons, 1998 was wetter and cooler than average due to EL Nino climate patterns and 1997 was hotter and drier than average. One extreme 3-day heat wave in 1997 (Days 218-221) caused a step change in the relationship between H2O flux and vapor pressure deficit, resulting in a change in canopy conductance, possibly due to cavitation of the tree xylem. This step change was also correlated with decreased rates of C sequestration and evapotranspiration; we estimate that this extreme climatic event decreased gross ecosystem production (GEP) by roughly 20% (4 μmol C m-2 s-1) for the rest of the growing season. In contrast, a cooler, wetter spring in 1998 delayed the onset of photosynthesis by about 3 weeks, resulting in roughly 20% lower GEP relative to the spring of 1997. We conclude that the net C balance of Mediterranean-climate pine ecosystems is sensitive to extreme events under low soil moisture conditions and could be altered by slight changes in the climate or hydrologic regime. (C) 2000 Elsevier Science B.V.