Measuring fluxes of trace gases and energy between ecosystems and the atmosphere - the state and future of the eddy covariance method.
TL;DR: A perspective on the contributions and future opportunities of the eddy covariance method is provided and the pros and cons of this method relative to other methods used to measure the exchange of trace gases between ecosystems and the atmosphere are discussed.
Abstract: The application of the eddy covariance flux method to measure fluxes of trace gas and energy between ecosystems and the atmosphere has exploded over the past 25 years. This opinion paper provides a perspective on the contributions and future opportunities of the eddy covariance method. First, the paper discusses the pros and cons of this method relative to other methods used to measure the exchange of trace gases between ecosystems and the atmosphere. Second, it discusses how the use of eddy covariance method has grown and evolved. Today, more than 400 flux measurement sites are operating world-wide and the duration of the time series exceed a decade at dozens of sites. Networks of tower sites now enable scientists to ask scientific questions related to climatic and ecological gradients, disturbance, changes in land use, and management. The paper ends with discussions on where the field of flux measurement is heading. Topics discussed include role of open access data sharing and data mining, in this new era of big data, and opportunities new sensors that measure a variety of trace gases, like volatile organic carbon compounds, methane and nitrous oxide, and aerosols, may yield.
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01 Dec 2012
Abstract: We upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE). We trained MTE to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use. We applied the trained MTEs to generate global flux fields at a 0.5 degrees x 0.5 degrees spatial resolution and a monthly temporal resolution from 1982 to 2008. Cross-validation analyses revealed good performance of MTE in predicting among-site flux variability with modeling efficiencies (MEf) between 0.64 and 0.84, except for NEE (MEf = 0.32). Performance was also good for predicting seasonal patterns (MEf between 0.84 and 0.89, except for NEE (0.64)). By comparison, predictions of monthly anomalies were not as strong (MEf between 0.29 and 0.52). Improved accounting of disturbance and lagged environmental effects, along with improved characterization of errors in the training data set, would contribute most to further reducing uncertainties. Our global estimates of LE (158 +/- 7 J x 10(18) yr(-1)), H (164 +/- 15 J x 10(18) yr(-1)), and GPP (119 +/- 6 Pg C yr(-1)) were similar to independent estimates. Our global TER estimate (96 +/- 6 Pg C yr(-1)) was likely underestimated by 5-10%. Hot spot regions of interannual variability in carbon fluxes occurred in semiarid to semihumid regions and were controlled by moisture supply. Overall, GPP was more important to interannual variability in NEE than TER. Our empirically derived fluxes may be used for calibration and evaluation of land surface process models and for exploratory and diagnostic assessments of the biosphere.
948 citations
TL;DR: In this article, the authors performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines).
Abstract: . Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data and (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange (R2 0.6), gross primary production (R2> 0.7), latent heat (R2 > 0.7), sensible heat (R2 > 0.7), and net radiation (R2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well (R2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted (R2
473 citations
Cites background from "Measuring fluxes of trace gases and..."
...In situ continuous observations can be obtained with the eddy-covariance technique, which estimates the net exchanges of carbon dioxide (CO2), water vapor and energy between land ecosystems and the atmosphere (Aubinet at al., 2012; Baldocchi, 2014)....
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TL;DR: In this article, a review of theory, modeling, and observations of photosynthesis across space and time for decadal intervals beginning in the 1950s is provided, identifying the key uncertainties in global photosynthesis estimates, including evaluating light intercepted by canopies, biophysical forcings, the structure of light use efficiency models and their parameters, like photosynthetic capacity, and relationships between suninduced chlorophyll fluorescence and canopy photosynthesis.
238 citations
Cites background from "Measuring fluxes of trace gases and..."
...The emergence of networks of eddy covariance flux towers has significantly advanced our understanding of canopy photosynthesis processes (Baldocchi, 2014; Wofsy et al., 1993)....
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23 Jun 2016
TL;DR: In this article, the authors quantify the impact of extreme climate events on the carbon cycle and show that the detrimental effects of severe summer drought on ecosystem carbon storage can be mitigated by warming-induced increases in spring carbon uptake.
Abstract: Significance Carbon uptake by terrestrial ecosystems mitigates the impact of anthropogenic fossil fuel emissions on atmospheric CO2 concentrations, but the strength of this carbon sink is highly sensitive to large-scale extreme climate events. In 2012, the United States experienced the most severe drought since the Dust Bowl period, along with the warmest spring on record. Here, we quantify the impact of this climate anomaly on the carbon cycle. Our results show that warming-induced earlier vegetation activity increased spring carbon uptake, and thus compensated for reduced carbon uptake during the summer drought in 2012. This compensation, however, came at the cost of soil moisture depletion from increased spring evapotranspiration that likely enhanced summer heating through land-atmosphere coupling. The global terrestrial carbon sink offsets one-third of the world’s fossil fuel emissions, but the strength of this sink is highly sensitive to large-scale extreme events. In 2012, the contiguous United States experienced exceptionally warm temperatures and the most severe drought since the Dust Bowl era of the 1930s, resulting in substantial economic damage. It is crucial to understand the dynamics of such events because warmer temperatures and a higher prevalence of drought are projected in a changing climate. Here, we combine an extensive network of direct ecosystem flux measurements with satellite remote sensing and atmospheric inverse modeling to quantify the impact of the warmer spring and summer drought on biosphere-atmosphere carbon and water exchange in 2012. We consistently find that earlier vegetation activity increased spring carbon uptake and compensated for the reduced uptake during the summer drought, which mitigated the impact on net annual carbon uptake. The early phenological development in the Eastern Temperate Forests played a major role for the continental-scale carbon balance in 2012. The warm spring also depleted soil water resources earlier, and thus exacerbated water limitations during summer. Our results show that the detrimental effects of severe summer drought on ecosystem carbon storage can be mitigated by warming-induced increases in spring carbon uptake. However, the results also suggest that the positive carbon cycle effect of warm spring enhances water limitations and can increase summer heating through biosphere–atmosphere feedbacks.
215 citations
TL;DR: Directions for synthesis that combine approaches in metaecosystem and metacommunity ecology and integrate cross‐scale feedbacks are suggested and new research on the role of scale in BEF will guide policy linking the goals of managing biodiversity and ecosystems.
Abstract: A rich body of knowledge links biodiversity to ecosystem functioning (BEF), but it is primarily focused on small scales. We review the current theory and identify six expectations for scale dependence in the BEF relationship: (1) a nonlinear change in the slope of the BEF relationship with spatial scale; (2) a scale-dependent relationship between ecosystem stability and spatial extent; (3) coexistence within and among sites will result in a positive BEF relationship at larger scales; (4) temporal autocorrelation in environmental variability affects species turnover and thus the change in BEF slope with scale; (5) connectivity in metacommunities generates nonlinear BEF and stability relationships by affecting population synchrony at local and regional scales; (6) spatial scaling in food web structure and diversity will generate scale dependence in ecosystem functioning. We suggest directions for synthesis that combine approaches in metaecosystem and metacommunity ecology and integrate cross-scale feedbacks. Tests of this theory may combine remote sensing with a generation of networked experiments that assess effects at multiple scales. We also show how anthropogenic land cover change may alter the scaling of the BEF relationship. New research on the role of scale in BEF will guide policy linking the goals of managing biodiversity and ecosystems.
214 citations
Cites background from "Measuring fluxes of trace gases and..."
...…reflects gradients of energy and limiting resources, it also contributes to how effectively those gradients are exploited to confer ecosystem functioning, such as variability in the rates of primary and secondary production (Baldocchi 2014; Niu et al. 2017; Pappas et al. 2017; Jia et al. 2018)....
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...Even while the distribution of biodiversity reflects gradients of energy and limiting resources, it also contributes to how effectively those gradients are exploited to confer ecosystem functioning, such as variability in the rates of primary and secondary production (Baldocchi 2014; Niu et al. 2017; Pappas et al. 2017; Jia et al. 2018)....
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References
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TL;DR: Interdisciplinary science that integrates knowledge of the many interacting climate services of forests with the impacts of global change is necessary to identify and understand as yet unexplored feedbacks in the Earth system and the potential of forests to mitigate climate change.
Abstract: The world's forests influence climate through physical, chemical, and biological processes that affect planetary energetics, the hydrologic cycle, and atmospheric composition. These complex and nonlinear forest-atmosphere interactions can dampen or amplify anthropogenic climate change. Tropical, temperate, and boreal reforestation and afforestation attenuate global warming through carbon sequestration. Biogeophysical feedbacks can enhance or diminish this negative climate forcing. Tropical forests mitigate warming through evaporative cooling, but the low albedo of boreal forests is a positive climate forcing. The evaporative effect of temperate forests is unclear. The net climate forcing from these and other processes is not known. Forests are under tremendous pressure from global change. Interdisciplinary science that integrates knowledge of the many interacting climate services of forests with the impacts of global change is necessary to identify and understand as yet unexplored feedbacks in the Earth system and the potential of forests to mitigate climate change.
4,541 citations
"Measuring fluxes of trace gases and..." refers background in this paper
...Together, these processes and their interactions with the environment and one another exert a plethora of positive and negative feedbacks on the interactions between fluxes and the state of the environment (Sellers et al., 1996; Bonan, 2008)....
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University of California, Berkeley1, University of Bayreuth2, Oak Ridge National Laboratory3, United States Department of Agriculture4, University of Montana5, Oregon State University6, Dresden University of Technology7, Duke University8, Yale University9, University of Edinburgh10, National Oceanic and Atmospheric Administration11, Harvard University12, San Diego State University13, Technical University of Denmark14, Indiana University15, Tuscia University16, University of Nebraska–Lincoln17, University of Helsinki18
TL;DR: The FLUXNET project as mentioned in this paper is a global network of micrometeorological flux measurement sites that measure the exchanges of carbon dioxide, water vapor, and energy between the biosphere and atmosphere.
Abstract: FLUXNET is a global network of micrometeorological flux measurement sites that measure the exchanges of carbon dioxide, water vapor, and energy between the biosphere and atmosphere. At present over 140 sites are operating on a long-term and continuous basis. Vegetation under study includes temperate conifer and broadleaved (deciduous and evergreen) forests, tropical and boreal forests, crops, grasslands, chaparral, wetlands, and tundra. Sites exist on five continents and their latitudinal distribution ranges from 70°N to 30°S. FLUXNET has several primary functions. First, it provides infrastructure for compiling, archiving, and distributing carbon, water, and energy flux measurement, and meteorological, plant, and soil data to the science community. (Data and site information are available online at the FLUXNET Web site, http://www-eosdis.ornl.gov/FLUXNET/.) Second, the project supports calibration and flux intercomparison activities. This activity ensures that data from the regional networks are intercomparable. And third, FLUXNET supports the synthesis, discussion, and communication of ideas and data by supporting project scientists, workshops, and visiting scientists. The overarching goal is to provide information for validating computations of net primary productivity, evaporation, and energy absorption that are being generated by sensors mounted on the NASA Terra satellite. Data being compiled by FLUXNET are being used to quantify and compare magnitudes and dynamics of annual ecosystem carbon and water balances, to quantify the response of stand-scale carbon dioxide and water vapor flux densities to controlling biotic and abiotic factors, and to validate a hierarchy of soil–plant–atmosphere trace gas exchange models. Findings so far include 1) net CO 2 exchange of temperate broadleaved forests increases by about 5.7 g C m −2 day −1 for each additional day that the growing season is extended; 2) the sensitivity of net ecosystem CO 2 exchange to sunlight doubles if the sky is cloudy rather than clear; 3) the spectrum of CO 2 flux density exhibits peaks at timescales of days, weeks, and years, and a spectral gap exists at the month timescale; 4) the optimal temperature of net CO 2 exchange varies with mean summer temperature; and 5) stand age affects carbon dioxide and water vapor flux densities.
3,162 citations
"Measuring fluxes of trace gases and..." refers background in this paper
..., 2010); (4) the response of photosynthesis and respiration to temperature acclimates (Baldocchi et al., 2001; Mahecha et al., 2010a); (5) ecosystem photosynthetic capacity adjusts with time of season (Wang et al....
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...…varies as a function of time since disturbance (Amiro et al., 2010); (4) the response of photosynthesis and respiration to temperature acclimates (Baldocchi et al., 2001; Mahecha et al., 2010a); (5) ecosystem photosynthetic capacity adjusts with time of season (Wang et al., 2007); and (6) how…...
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TL;DR: A critical reassessment of the quality and the robustness of these models across tropical forest types, using a large dataset of 2,410 trees ≥ 5 cm diameter, directly harvested in 27 study sites across the tropics, is provided.
Abstract: Tropical forests hold large stores of carbon, yet uncertainty remains regarding their quantitative contri- bution to the global carbon cycle. One approach to quantifying carbon biomass stores consists in inferring changes from long-term forest inventory plots. Regres- sion models are used to convert inventory data into an estimate of aboveground biomass (AGB). We provide a critical reassessment of the quality and the robustness of these models across tropical forest types, using a large dataset of 2,410 trees ‡ 5 cm diameter, directly harvested in 27 study sites across the tropics. Proportional rela- tionships between aboveground biomass and the prod- uct of wood density, trunk cross-sectional area, and total height are constructed. We also develop a regres- sion model involving wood density and stem diameter only. Our models were tested for secondary and old- growth forests, for dry, moist and wet forests, for low- land and montane forests, and for mangrove forests. The most important predictors of AGB of a tree were, in decreasing order of importance, its trunk diameter, wood specific gravity, total height, and forest type (dry, moist, or wet). Overestimates prevailed, giving a bias of 0.5-6.5% when errors were averaged across all stands. Our regression models can be used reliably to predict aboveground tree biomass across a broad range of tropical forests. Because they are based on an unprece- dented dataset, these models should improve the quality
2,786 citations
"Measuring fluxes of trace gases and..." refers background in this paper
...For example, they are labor intensive, so the replication of harvest samples across species, size, and age structure classes can be less than ideal (Woodwell & Whittaker, 1968); one review reports that only about 2400 trees have been harvested to determine the allometric scaling rules of the world’s tropical forests (Chave et al., 2005)....
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...…the replication of harvest samples across species, size, and age structure classes can be less than ideal (Woodwell & Whittaker, 1968); one review reports that only about 2400 trees have been harvested to determine the allometric scaling rules of the world’s tropical forests (Chave et al., 2005)....
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