Annual NEE Research Articles

Eddy Covariance CO2 Flux Gap Filling for Long Data Gaps: A Novel Framework Based on Machine Learning and Time Series Decomposition

Continuous long-term eddy covariance (EC) measurements of CO2 fluxes (NEE) in a variety of terrestrial ecosystems are critical for investigating the impacts of climate change on ecosystem carbon cycling. However, due to a number of issues, approximately 30–60% of annual flux data obtained at EC flux sites around the world are reported as gaps. Given that the annual total NEE is mostly determined by variations in the NEE data with time scales longer than one day, we propose a novel framework to perform gap filling in NEE data based on machine learning (ML) and time series decomposition (TSD). The novel framework combines the advantages of ML models in predicting NEE with meteorological and environmental inputs and TSD methods in extracting the dominant varying trends in NEE time series. Using the NEE data from 25 AmeriFlux sites, the performance of the proposed framework is evaluated under four different artificial scenarios with gap lengths ranging in length from one hour to two months. The combined approach incorporating random forest and moving average (MA-RF) is observed to exhibit better performance than other approaches at filling NEE gaps in scenarios with different gap lengths. For the scenario with a gap length of seven days, the MA-RF improves the R2 by 34% and reduces the root mean square error (RMSE) by 55%, respectively, compared to a traditional RF-based model. The improved performance of MA-RF is most likely due to the reduction in data variability and complexity of the variations in the extracted low-frequency NEE data. Our results indicate that the proposed MA-RF framework can provide improved gap filling for NEE time series. Such improved continuous NEE data can enhance the accuracy of estimations regarding the ecosystem carbon budget.

Impact of Shifts in Vegetation Phenology on the Carbon Balance of a Semiarid Sagebrush Ecosystem

Dryland ecosystems are critical in regulating the interannual variability of the global terrestrial carbon cycle. The responses of such ecosystems to weather and environmental conditions remain important factors that limit the accurate projections of carbon balance under future climate change. Here, we investigated how shifts in vegetation phenology resulting from changes in weather and environmental conditions influenced ecosystem carbon cycling in one semiarid ecosystem in the Hanford area of central Washington, United States. We examined two years of measurements of the phenology camera, eddy covariance, and soil chamber from an upland semiarid sagebrush ecosystem. Both years had contrasting diel and seasonal patterns of CO2 fluxes, primarily driven by differences in vegetation phenology. The net ecosystem exchange of CO2 (NEE) and evapotranspiration (ET) in 2019 were enlarged by shifted vegetation phenology, as a cold and snow-covered winter and warm and dry winter in 2020 resulted in constrained magnitudes of NEE and ET during the summer months. The annual gross primary productivity (GPP) was much higher in 2019 than in 2020 (−211 vs. −112 gC m−2), whereas ecosystem respiration was comparable in these two years (164 vs. 144 gC m−2). Thus, the annual NEE in 2019 was negative (−47 gC m−2) with the sagebrush ecosystem functioning as a carbon sink, while the positive annual NEE in 2020 indicated that the sagebrush ecosystem functioned as a carbon source. Our results demonstrate that winter snowpack can be a critical driver of annual carbon uptake in semiarid sagebrush ecosystems.

Response of Peatland CO2 and CH4 Fluxes to Experimental Warming and the Carbon Balance

The function of peatlands as a large carbon (C) reservoir results from the net C uptake under cold, wet, and acid environments. However, in the context of global warming, the balance between C input and release is expected to change, which may further alter the C sink of peatlands. To examine the response to climate warming of a temperate Sphagnum peatland which has been invaded by vascular plants, a mesocosm experiment was conducted with open top chambers (OTCs) to simulate a moderate temperature increase. Gross primary production (GPP), ecosystem respiration (ER), and methane (CH4) emissions were monitored for 2 years. The CO2 and CH4 fluxes were modeled by relating to abiotic and biotic factors, including temperature, water table depth (WTD), and vegetation, in order to calculate the annual C budget. Results showed that the annual cumulated GPP was significantly enhanced by the simulated warming (−602 compared to −501 gC m−2 yr−1 in OTC and control plots, respectively), mainly due to the increase of graminoid biomass by warming, while experimental warming had no significant effect on the annual ER and CH4 emissions (an output of 615 and 500 gC m−2 yr−1 for ER; 21 and 16 gC m−2 yr−1 for CH4 emissions in OTC and control plots, respectively). The annual NEE and C budget were not affected by the short-term experimental warming. The mesocosms under both treatments acted as a gaseous C source with 34 and 14 gC m−2 yr−1 output under OTC and control treatment, respectively. This C source was driven by the strong net carbon dioxide (CO2) release during a low WTD period in summer, as CH4 emissions only accounted for 0.9–2.2% of the total C fluxes. Our study identified the effect of moderate warming on the C fluxes, even on a short-term basis. Also, our findings highlighted that the response of C fluxes to warming largely depends on the WTD and vegetation composition. Thus, long-term monitoring of hydrology and vegetation change under climate warming is essential to examine their interactions in determining the C fluxes in peatlands.

Relative importance of climatic variables, soil properties and plant traits to spatial variability in net CO2 exchange across global forests and grasslands

Compared to the well-known drivers of spatial variability in gross primary productivity (GPP), the relative importance of climatic variables, soil properties and plant traits to the spatial variability in net ecosystem exchange of CO2 between terrestrial ecosystem and atmosphere (NEE) is poorly understood. We used principal component regression to analyze data from 147 eddy flux sites to disentangle effects of climatic variables, soil properties and plant traits on the spatial variation in annual NEE and its components (GPP and ecosystem respiration (RE)) across global forests and grasslands. Our results showed that the largest unique contribution (proportion of variance only explained by one class of variables) to NEE variance came from climatic variables for forests (24%-30%) and soil properties for grasslands (41%-54%). Specifically, mean annual precipitation and potential evapotranspiration were the most important climatic variables driving forest NEE, whereas available soil water capacity, clay content and cation exchange capacity mainly influenced grassland NEE. Plant traits showed a small unique contribution to NEE in both forests and grasslands. However, leaf phosphorus content strongly interacted with soil total nitrogen density and clay content, and these combined factors represented a major contribution for grassland NEE. For GPP and RE, the majority of spatial variance was attributed to the common contribution of climate, soil and plant traits (50% - 62%, proportion of variance explained by more than one class of variables), rather than their unique contributions. Interestingly, those factors with only minor influences on GPP and RE variability (e.g., soil properties) have significant contributions to the spatial variability in NEE. Such emerging factors and the interactions between climatic variables, soil properties and plant traits are not well represented in current terrestrial biosphere models, which should be considered in future model improvement to accurately predict the spatial pattern of carbon cycling across forests and grasslands globally.

Effect of temperature change on CO2 Flux in temperate mixed forest ecosystem

Forest is the main carbon sink of terrestrial ecosystem. Due to the unique growth characteristics of plants, the response of their growth status and physiological activities to climate change will affect the carbon cycle process of forest ecosystem. Based on the local scale CO2 flux and temperature observation data recorded by the FLUXNET registration site and Harvard Forest FLUX observation tower from 2000 to 2012, combined with the phenological model, this paper analyzes the impact of temperature changes on CO2 flux in temperate forest ecosystems. The results show that: (1) the maximum NEE in 2000–2012 was 298.13 g·m-2·a-1, which occurred in 2010. Except in the 2010 and 2011, the annual NEE in other years was negative. (2) NEE, GPP, temperature and phenology models have good fitting effects (R2 > 0.8), which shows that the stable period of photosynthesis in temperate mixed forest ecosystem is mainly concentrated in summer, and vegetation growth is the dominant factor of carbon cycle in temperate mixed forest ecosystem. (3) The linear fitting results of the change time points of air temperature (maximum point, minimum point and 0 point date) and the change time points of NEE and GPP (maximum point, minimum point and 0 point date) show that there is a significant positive correlation between air temperature and CO2 flux (P < 0.01), and the change of air temperature affects the carbon cycle process of temperate mixed forest ecosystem.

Multi‐year carbon budget of a mature commercial short rotation coppice willow plantation

AbstractEnergy derived from second generation perennial energy crops is projected to play an increasingly important role in the decarbonization of the energy sector. Such energy crops are expected to deliver net greenhouse gas emissions reductions through fossil fuel displacement and have potential for increasing soil carbon (C) storage. Despite this, few empirical studies have quantified the ecosystem‐level C balance of energy crops and the evidence base to inform energy policy remains limited. Here, the temporal dynamics and magnitude of net ecosystem carbon dioxide (CO2) exchange (NEE) were quantified at a mature short rotation coppice (SRC) willow plantation in Lincolnshire, United Kingdom, under commercial growing conditions. Eddy covariance flux observations of NEE were performed over a four‐year production cycle and combined with biomass yield data to estimate the net ecosystem carbon balance (NECB) of the SRC. The magnitude of annual NEE ranged from −147 ± 70 to −502 ± 84 g CO2‐C m−2 year−1 with the magnitude of annual CO2 capture increasing over the production cycle. Defoliation during an unexpected outbreak of willow leaf beetle impacted gross ecosystem production, ecosystem respiration, and net ecosystem exchange during the second growth season. The NECB was −87 ± 303 g CO2‐C m−2 for the complete production cycle after accounting for C export at harvest (1,183 g C m−2), and was approximately CO2‐C neutral (−21 g CO2‐C m−2 year−1) when annualized. The results of this study are consistent with studies of soil organic C which have shown limited changes following conversion to SRC willow. In the context of global decarbonization, the study indicates that the primary benefit of SRC willow production at the site is through displacement of fossil fuel emissions.

Carbon and evapotranspiration dynamics of a non-native perennial grass with biofuel potential in the southern U.S. Great Plains

Old world bluestem cultivar WW-B Dahl [Bothriochloa bladhii (Retz.), S. T. Blake] is a non-native perennial C4 bunch grass with biofuel production potential grown predominantly in the Southern U.S. Great Plains. Although this is a popular introduced grass cultivar, data on carbon fluxes and evapotranspiration (ET) from this warm-season grass is rare. In this study, the eddy covariance method was used to measure CO2 and ET from an established stand of bluestem for three years (2013–2015). Year 2015 had the highest gross primary production (GPP; 1358 ± 143 g C m−2) followed by 2014 (1250 ± 31 g C m−2) and 2013 (1024 ± 91 g C m−2). The average loss of GPP as ecosystem respiration (Reco) was 76%. Annual NEE sums were -302 ± 15 g C m−2 in 2013, -265 ± 41 g C m-2 in 2014, and -287 ± 32 g C m−2 in 2015. Results from this study show that the NEE in grasslands in years with normal precipitation that is well distributed may not vary from years with above-normal precipitation. This is because precipitation enhances Reco along with carbon uptake, which may result in lower net carbon uptake in perennial grasslands in higher precipitation years than normal precipitation years. Gross primary production showed a linear relationship with ET (R2 = 0.90) and above ground biomass (R2 = 0.74). Only 26% of the GPP was allocated to above ground biomass indicating a higher allocation of carbon to below ground biomass. The water use efficiency of bluestem (2.9 g C kg-1 of water) matched well with that of native prairies and other dedicated biomass crops grown in the Southern Great Plains. As the demand for cellulosic biofuels is increasing, results from field experiments quantifying seasonal changes in carbon fluxes and ET could be important in understanding the contributions of large-scale production of novel biomass crops to regional carbon and hydrologic cycles.

Groundwater‐River Water Exchange Enhances Growing Season Evapotranspiration and Carbon Uptake in a Semiarid Riparian Ecosystem

AbstractSemiarid ecosystems play a critical role in determining the interannual variability of the global terrestrial carbon sink. Water availability is a critical driver of productivity in semiarid ecosystems, which often alternate between carbon sink/source functioning during wet/dry years. In this study, we investigate how groundwater availability resulting from groundwater‐river water exchange influences net ecosystem exchange of CO2 (NEE), evapotranspiration (ET), and the surface energy balance at two semiarid ecosystems along the Columbia River in central Washington, USA. We examined 1 year of eddy covariance measurements from an upland sagebrush ecosystem primarily fed by rainfall without groundwater access and a riparian grassland ecosystem with groundwater access during the dry season due to lateral groundwater‐river water exchange. The two sites had distinct seasonal patterns of NEE and ET, driven by differences in water availability. While NEE at the upland sagebrush site was strongly constrained by water availability during the dry months, access to groundwater allowed the riparian site to maintain high NEE magnitude and ET during the same dry months. The riparian site had larger annual gross primary productivity than the upland site (612 vs. 424 gC/m2), which was offset by higher ecosystem respiration (558 vs. 363 gC/m2). Thus, the magnitude of the annual NEE at the upland site was larger than that at the riparian site (−62 vs. −54 gC/m2). Our results demonstrate that groundwater access determined by connectivity between groundwater and surface water can be a critical driver of carbon uptake and ET in semiarid ecosystems.

Multi-year net ecosystem carbon balance of a restored peatland reveals a return to carbon sink.

Peatlands after drainage and extraction are large sources of carbon (C) to the atmosphere. Restoration, through re-wetting and revegetation, aims to return the C sink function by re-establishing conditions similar to that of an undrained peatland. However, the time needed to re-establish C sequestration is not well constrained due to the lack of multi-year measurements. We measured over 3years the net ecosystem exchange of CO2 (NEE), methane ( ), and dissolved organic carbon (DOC) at a restored post-extraction peatland (RES) in southeast Canada (restored 14years prior to the start of the study) and compared our observations to the C balance of an intact reference peatland (REF) that has a long-term continuous flux record and is in the same climate zone. Small but significant differences in winter respiration driven by temperature were mainly responsible for differences in cumulative NEE between years. Low growing season inter-annual variability was linked to constancy of the initial spring water table position, controlled by the blocked drainage ditches and the presence of water storage structures (bunds and pools). Half-hour at RES was small except when Typha latifolia-invaded drainage ditches were in the tower footprint; this effect at the ecosystem level was small as ditches represent a minor fraction of RES. The restored peatland was an annual sink for CO2 (-90±18gCm-2 year-1 ), a source of CH4 (4.4±0.2gCm-2 year-1 ), and a source of DOC (6.9±2.2gCm-2 year-1 ), resulting in mean net ecosystem uptake of 78±17gCm-2 year-1 . Annual NEE at RES was most similar to wetter, more productive years at REF. Integrating structures to increase water retention, alongside re-establishing key species, have been effective at re-establishing the net C sink rate to that of an intact peatland.

Carbon exchange in an Amazon forest: from hours to years

Abstract. In Amazon forests, the relative contributions of climate, phenology, and disturbance to net ecosystem exchange of carbon (NEE) are not well understood. To partition influences across various timescales, we use a statistical model to represent eddy-covariance-derived NEE in an evergreen eastern Amazon forest as a constant response to changing meteorology and phenology throughout a decade. Our best fit model represented hourly NEE variations as changes due to sunlight, while seasonal variations arose from phenology influencing photosynthesis and from rainfall influencing ecosystem respiration, where phenology was asynchronous with dry-season onset. We compared annual model residuals with biometric forest surveys to estimate impacts of drought disturbance. We found that our simple model represented hourly and monthly variations in NEE well (R2=0.81 and 0.59, respectively). Modeled phenology explained 1 % of hourly and 26 % of monthly variations in observed NEE, whereas the remaining modeled variability was due to changes in meteorology. We did not find evidence to support the common assumption that the forest phenology was seasonally light- or water-triggered. Our model simulated annual NEE well, with the exception of 2002, the first year of our data record, which contained 1.2 MgC ha−1 of residual net emissions, because photosynthesis was anomalously low. Because a severe drought occurred in 1998, we hypothesized that this drought caused a persistent, multi-year depression of photosynthesis. Our results suggest drought can have lasting impacts on photosynthesis, possibly via partial damage to still-living trees.

ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO<sub>2</sub>, water, and energy fluxes on daily to annual scales

Abstract. Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 = 0.76; Nash–Sutcliffe modeling efficiency, MEF = 0.76) and ecosystem respiration (ER, r2 = 0.78, MEF = 0.75), with lesser accuracy for latent heat fluxes (LE, r2 = 0.42, MEF = 0.14) and and net ecosystem CO2 exchange (NEE, r2 = 0.38, MEF = 0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 < 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.

Multi-temporal scale analysis of impacts of extreme high temperature on net carbon uptake in subtropical coniferous plantation.

Extreme high temperature is one of important extreme weathers that impact forest ecosystem carbon cycle. In this study, applying CO2 flux and routine meteorological data measured during 2003-2012, we examined the impacts of extreme high temperature and extreme high temperature event on net carbon uptake of subtropical coniferous plantation in Qianyanzhou. Combining with wavelet analysis, we analyzed environmental controls on net carbon uptake at different temporal scales, when the extreme high temperature and extreme high temperature event happened. The results showed that mean daily cumulative NEE decreased by 51% in the days with daily maximum air temperature range between 35 ℃ and 40 ℃, compared with that in the days with the range between 30 ℃ and 34 ℃. The effects of the extreme high temperature and extreme high temperature event on monthly NEE and annual NEE related to the strength and duration of extreme high tempe-rature event. In 2003, when strong extreme high temperature event happened, the sum of monthly cumulative NEE in July and August was only -11.64 g C·m-2·(2 month)-1. The value decreased by 90%, compared with multi-year average value. At the same time, the relative variation of annual NEE reached -6.7%. In July and August, when the extreme high temperature and extreme high temperature event occurred, air temperature (Ta) and vapor press deficit (VPD) were the dominant controller for the daily variation of NEE. The coherency between NEE Ta and NEE VPD was 0.97 and 0.95, respectively. At 8-, 16-, and 32-day periods, Ta, VPD, soil water content at 5 cm depth (SWC), and precipitation (P) controlled NEE. The coherency between NEE SWC and NEE P was higher than 0.8 at monthly scale. The results indicated that atmospheric water deficit impacted NEE at short temporal scale, when the extreme high temperature and extreme high temperature event occurred, both of atmospheric water deficit and soil drought stress impacted NEE at long temporal scales in this ecosystem.

Can abandoned peatland pasture sequestrate more carbon dioxide from the atmosphere than an adjacent pristine bog in Newfoundland, Canada?

Net ecosystem exchange of carbon dioxide (NEE) and its components, gross primary productivity (GPP) and ecosystem respiration (ER), were compared between a bog and an abandoned peatland pasture within the same peatland complex in western Newfoundland, Canada. Measurements based on the eddy covariance technique from April 2014 to April 2016 were used to examine the influence of agricultural management and abandonment on peatland carbon dioxide (CO2) exchange. NEE, GPP and ER at both sites showed pronounced seasonal variation, peaking near the middle growing season. The maximum net CO2 uptake rate of −28.61μmolm−2s−1 and emission rate of 14.39μmolm−2s−1 at the pasture were significantly higher than those at the bog (−9.67μmolm−2s−1 and 5.50μmolm−2s−1, respectively). Daytime average GPP was related to photosynthetic photon flux density and air temperature and the nighttime average ER decreased with soil water content, but increased with surface soil temperature for both sites. Annual NEE of the pasture (−128±60gCm−2yr−1 in 2014–15 and −124±56gCm−2yr−1 in 2015–16) was considerably larger than that of the bog (−46±36gCm−2yr−1 in 2014–15). GPP of 1086±141gCm−2yr−1 in 2014–15 and 982±123gCm−2yr−1 in 2015–16 and ER of 957±129gCm−2yr−1 in 2014–15 and 858±112gCm−2yr−1 in 2015–16 at the pasture were approximately twice the magnitude of the corresponding fluxes at the bog. The difference in GPP between the bog and pasture was mainly related to their different aboveground biomass. Higher ER at the pasture was probably related to its lower water table depth, greater substrate availability and higher autotrophic respiration. Unlike previous findings that managed peatlands are large CO2 emitters, our results suggest that abandoned peatland pastures can function like natural grasslands and sequester considerable amounts of CO2 from the atmosphere.

CO2 balance of a secondary tropical peat swamp forest in Sarawak, Malaysia

Tropical peat swamp forest (PSF) has accumulated a huge amount of carbon as peat over millennia, though the carbon rich ecosystem is now threatened with disturbances due to land-use change to industrial plantations of oil palm and pulp woods. Through the land conversion, peat carbon has become vulnerable and potentially changes to a great carbon dioxide (CO2) source to the atmosphere. It is essential to quantify the CO2 balance of the ecosystem and understand how the CO2 balance responds to environmental changes to predict the role of PSF in global carbon cycles. However, filed studies based on the ecosystem-scale monitoring of CO2 flux are quite limited. Thus, we began CO2 flux monitoring over a secondary PSF in Sarawak, Malaysia, by the eddy covariance technique in 2010. Daily NEE and RE were significantly different between the dry and wet periods (p<0.01), respectively, whereas no significant difference was found in daily GPP. As a result, the seasonal difference in NEE between the two periods (0.52gCm−2d−1) was due to that in RE (0.57gCm−2d−1). Daily RE was significantly greater in the dry period mainly because of lower groundwater level (GWL). Lower GWL enhances peat aeration and potentially increases oxidative peat decomposition, which results in higher soil CO2 efflux. Annual NEE was −136±51gCm−2yr−1 (mean±1 standard deviation) during the four years until 2014. The negative annual NEE was equivalent to those of some tropical rain forests on mineral soil, but was more negative than 174gCm−2yr−1 for an almost undrained PSF in Central Kalimantan, Indonesia (Hirano et al., 2012). The difference in annual NEE between the two sites is attributable to higher leaf area index and less distinct seasonality in precipitation in this site.

Extensive green roof CO2 exchange and its seasonal variation quantified by eddy covariance measurements

The CO2 surface-atmosphere exchange of an unirrigated, extensive green roof in Berlin, Germany was measured by means of the eddy covariance method over a full annual cycle. The present analysis focusses on the cumulative green roof net ecosystem exchange of CO2 (NEE), on its seasonal variation and on green roof physiological characteristics by applying a canopy (A-gs) model. The green roof was a carbon sink with an annual cumulative NEE of −313gCO2m−2year−1, equivalent to −85gCm−2year−1. Three established CO2 flux gap-filling methods were applied to estimate NEE and to study the performance during different meteorological situations. A best estimate NEE time series was established, which chooses the gap filling method with the highest performance. During dry periods daytime carbon uptake was shown to decline linearly with substrate moisture below a threshold of 0.05m3m−3, whereas night-time respiration was unaffected by substrate moisture variation. The roof turned into a temporary C source during dry conditions in summer 2015. We conclude that the carbon uptake of the present green roof can be optimized when substrate moisture is kept above 0.05m3m−3.

Evaluation of a hierarchy of models reveals importance of substrate limitation for predicting carbon dioxide and methane exchange in restored wetlands

AbstractWetlands and flooded peatlands can sequester large amounts of carbon (C) and have high greenhouse gas mitigation potential. There is growing interest in financing wetland restoration using C markets; however, this requires careful accounting of both CO2and CH4exchange at the ecosystem scale. Here we present a new model, the PEPRMT model (Peatland Ecosystem Photosynthesis Respiration and Methane Transport), which consists of a hierarchy of biogeochemical models designed to estimate CO2and CH4exchange in restored managed wetlands. Empirical models using temperature and/or photosynthesis to predict respiration and CH4production were contrasted with a more process‐based model that simulated substrate‐limited respiration and CH4production using multiple carbon pools. Models were parameterized by using a model‐data fusion approach with multiple years of eddy covariance data collected in a recently restored wetland and a mature restored wetland. A third recently restored wetland site was used for model validation. During model validation, the process‐based model explained 70% of the variance in net ecosystem exchange of CO2(NEE) and 50% of the variance in CH4exchange. Not accounting for high respiration following restoration led to empirical models overestimating annual NEE by 33–51%. By employing a model‐data fusion approach we provide rigorous estimates of uncertainty in model predictions, accounting for uncertainty in data, model parameters, and model structure. The PEPRMT model is a valuable tool for understanding carbon cycling in restored wetlands and for application in carbon market‐funded wetland restoration, thereby advancing opportunity to counteract the vast degradation of wetlands and flooded peatlands.

Biogenic fluxes of carbon dioxide in the old-growth spruce forest in the middle taiga: Results of eddy covariance measurements

Fluxes of carbon dioxide in the old-growth bilberry spruce forest in the European Taiga are measured by the eddy covariance technique. A carbon dioxide sink to the ecosystem was observed from April until September; the maximum net-exchange rate of carbon dioxide was recorded in July. During the cold period of the year from October to March, the biogenic flux of CO2 was directed from the forest canopy to the atmosphere. According to measurements at u* > 0.2, the total annual NEE was 219 g C m–2; the annual values of the ecosystem respiration Reco and the gross photosynthesis Pgross were 483 and 966 g C m–2, respectively. The conclusion is that the old-growth bilberry spruce forest in the middle taiga subzone was the sink of carbon from the atmosphere during the year of observation.

Preserving the variance in imputed eddy-covariance measurements: Alternative methods for defensible gap filling

The high utility of eddy covariance (EC) data has made it the cornerstone of carbon dynamics research for more than two decades. However, a substantial number of measurements from EC data can be missing for various reasons. Robust gap-filling methods are required to estimate carbon budgets from net ecosystem exchange measurements of CO2 (NEE) with high precision and accuracy. While the gap-filled methods used have provided unbiased estimates of annual NEE, little research has been done on preserving the variance structures associated with gap-filled flux data. In this project, we used EC data from a longleaf pine ecosystem located in the southeast US to investigate variance preservation in gap-filling methods.We used three non-linear regression approaches to impute artificially created gaps of different sizes via light and temperature response curves: 1) “traditional” fixed monthly window, 2) moving window, and 3) moving window with parameter prediction using physiological drivers. The results of gap-filling simulations showed that the variability of NEE estimates made with moving window and parameter prediction methods were closer to that of observed NEE, whereas the traditional method had overall lower variability. The average root mean square errors (RMSE) of predictions was lower for moving window and parameter prediction (3.38 and 3.22, respectively), versus that of the traditional method (3.42) over one year, including both daytime and nighttime data across all gap sizes. The variances associated with moving window and parameter prediction methods were 52% and 57%, respectively, of the observed variance, versus that of the traditional (51%), while the average of first-order autocorrelation coefficients was 0.76 for each method compared to 0.58 for observed. The results showed that the moving window approaches provided better estimates (lower RMSEs and more similar variance) at annual scales, yet underestimated the observed variance. These results contribute toward the development of a framework of standardized gap-filling approaches which maintain variation inherent in EC data. Moreover, these results call for further research on potential environmental drivers and their interactions for inclusion in gap-filling models, as well as exploration of sampling size of estimation windows and averaging time (half hour) of flux data to promote variance maintenance and decrease the autocorrelation of predictions.

Comparison of carbon budget, evapotranspiration, and albedo effect between the biofuel crops switchgrass and corn

Interest in biofuels produced from perennial crops like switchgrass (Panicum virgatum L.) has increased over the past decades. It has been suggested that perennial biofuel crops have additional climate benefits compared to annual crops, such as carbon sequestration and albedo increase, but these effects have not been quantified in field studies. We compared carbon dioxide and water exchange results from eddy covariance measurements and surface albedo over a switchgrass and a corn field in Southwestern Ontario, Canada, for the year 2014. Results for the carbon budget showed more carbon uptake for switchgrass compared to corn (annual net ecosystem exchange NEE of −336±40 vs +64±41gCm−2). Switchgrass was a small sink of carbon with a net ecosystem carbon balance (NECB) of −66±59gCm−2 but corn was a source for a scenario where corn grain only is harvested (NECB 393±44gCm−2) and a 1.5 times larger source if both corn grain and stover are harvested (NECB 699±47gCm−2). Switchgrass had, however, a lower yield 568±93gm−2 than either corn scenario (751±40gm−2 for grain only and 1439±52gm−2 for grain plus stover). Results from the albedo measurements showed a negative radiative forcing on an annual basis for the switchgrass field compared to corn. Differences in albedo were especially pronounced during spring and fall when radiative forcing values of −10.2 and −5.5Wm−2 were observed, respectively. Qualitative analysis of the carbon budget, evapotranspiration, and albedo results from this study suggests that biofuel produced from switchgrass can have more climate benefits than biofuel produced from continuous corn cropping systems.

Importance of Early Season Conditions and Grazing on Carbon Dioxide Fluxes in Colorado Shortgrass Steppe

Understanding the influence of grazing management and environmental drivers on net ecosystem exchange of CO2 (NEE) is essential for optimizing carbon (C) uptake in rangelands. Herein, using 15 treatment-years (two 3-yr experiments, one with three grazing treatments, the other two) and Bowen ratio flux towers, we evaluated the influence of grazing intensity, soil water content (SWC), and plant cover (Normalized Difference Vegetation Index, or NDVI) on NEE in Colorado shortgrass steppe. Among several soil water and plant cover traits evaluated over 6-yr, early season (April, DOY 91–120) SWC and early season (DOY 130) NDVI were most highly correlated with NEE (−0.96 and −0.98, respectively) during the second quarter (April to June) of the year and also over the entire growing season (April to September; −0.97 and −0.96). Due to the strong effect of early-season SWC, an average of 166 g m−2 CO2 were lost in 2 yr with dry spring weather, compared with an average annual uptake of 218 g m−2 CO2 in 4 yr with more abundant early-season precipitation and plant cover. Grazing effects on NEE were also apparent. In one experiment, moderate grazing resulted in annual CO2 uptake of 267 g m−2 CO2 over 3 yr compared with essentially zero NEE in heavily grazed pasture. However, that treatment difference in annual NEE was only half that experienced between dry and wet years. Similar trends were observed in a second experiment, although results were insignificant. Results suggest that the recommended moderate grazing intensity for the Colorado shortgrass steppe is near optimal for CO2 uptake under season-long continuous grazing, with annual climatic variability sometimes being more influential. To enhance C sequestration in the western Great Plains of North America, grazing management strategies should emphasize flexible and adaptive practices that consider early-season SWC and promote vegetation cover during the key early spring growth period.