Eddy Covariance Instrumentation Research Articles

Machine learning algorithms improve MODIS GPP estimates in United States croplands

Introduction: Machine learning methods combined with satellite imagery have the potential to improve estimates of carbon uptake of terrestrial ecosystems, including croplands. Studying carbon uptake patterns across the U.S. using research networks, like the Long-Term Agroecosystem Research (LTAR) network, can allow for the study of broader trends in crop productivity and sustainability.Methods: In this study, gross primary productivity (GPP) estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) for three LTAR cropland sites were integrated for use in a machine learning modeling effort. They are Kellogg Biological Station (KBS, 2 towers and 20 site-years), Upper Mississippi River Basin (UMRB - Rosemount, 1 tower and 12 site-years), and Platte River High Plains Aquifer (PRHPA, 3 towers and 52 site-years). All sites were planted to maize (Zea mays L.) and soybean (Glycine max L.). The MODIS GPP product was initially compared to in-situ measurements from Eddy Covariance (EC) instruments at each site and then to all sites combined. Next, machine learning algorithms were used to create refined GPP estimates using air temperature, precipitation, crop type (maize or soybean), agroecosystem, and the MODIS GPP product as inputs. The AutoML program in the h2o package tested a variety of individual and combined algorithms, including Gradient Boosting Machines (GBM), eXtreme Gradient Boosting Models (XGBoost), and Stacked Ensemble.Results and discussion: The coefficient of determination (r2) of the raw comparison (MODIS GPP to EC GPP) was 0.38, prior to machine learning model incorporation. The optimal model for simulating GPP across all sites was a Stacked Ensemble type with a validated r2 value of 0.87, RMSE of 2.62 units, and MAE of 1.59. The machine learning methodology was able to successfully simulate GPP across three agroecosystems and two crops.

Vegetation description around the savanna flux measurement site at Benfontein Nature Reserve, South Africa

A flux tower with eddy covariance instruments was recently erected at Benfontein Nature Reserve (BNR) outside of Kimberley. An understanding of the landscape within the flux tower footprint, in this case natural vegetation, is necessary to interpret the data collected by the eddy covariance instruments. The tower was erected as part of the Expanded Freshwater and Terrestrial Environmental Observation Network (EFTEON) infrastructure initiative to establish long-term monitoring platforms focused on socially relevant terrestrial landscapes and their coupled hydrological systems. We sought to describe the vegetation within the flux tower footprint to set a baseline of the vegetation in the landscape at the inception of the long-term monitoring of flux measurements at BNR. Woody vegetation was surveyed in five square 1 ha plots while the herbaceous layer was sampled across 105 circular plots following the Socio-Ecological Observatory for Southern African Woodland (SEOSAW) protocol. Woody vegetation was quantified in terms of abundance, diversity and biomass, together with Size Class Distribution (SCD) methods to describe the woody vegetation structure. The herbaceous layer was described by species count, basal cover, biomass, and diversity which was assessed using the Shannon-Weiner Diversity Index. Five tree species, dominated by Vachellia erioloba, were found in the plots. Recruits (0 and 1 m tall) were significantly more abundant than large trees (1.2–9.5 m high). The SCD for the woody vegetation yielded a Type IIIa curve i.e. populations missing one or more size classes, for all tree species except Ziziphus mucronata which yielded a Type IIIb curve representing a population missing small sized trees. The herbaceous layer was diverse, consisting of 10 grass and 32 forb species. Schmidtia pappophoroides was the dominant grass species in terms of count, basal cover and aboveground biomass. Herbaceous biomass was two times higher than that of woody vegetation, with the North plot contributing the highest biomass for herbaceous and woody vegetation. The results indicate that the vegetation around the flux tower represents a wooded grassland, which is a type of a savanna. These vegetation data will contribute to the interpretation of data collected by the flux tower instruments now and in the future. Furthermore, long-term data collection in this reserve is needed to capture the woody vegetation dynamics and its interaction with the herbaceous layer.

Causal interaction in high frequency turbulence at the biosphere–atmosphere interface: Structural behavior

High-frequency (e.g., 10 Hz) eddy covariance measurements are typically used to estimate fluxes at the land–atmosphere interface at timescales of 15–60 min. These multivariate data contain information about the interdependency at high frequency between the interacting variables such as wind, humidity, temperature, and CO2. We use data at 10 Hz from an eddy covariance instrument located at 25 m above agricultural land in the Midwestern US, which offers an opportunity to move beyond the traditional spectral analyses to explore causal dependency among variables. In this study, we quantify the structure of inter-dependencies of interacting variables at high frequency represented by a directed acyclic graph (DAG). We compare DAGs to investigate changes in structural differences in causal interactions. We then apply a distance-based classification and k-means clustering approach to identify the evolution of the causal structure represented by a DAG. Our method selects an unbiased number of clusters of similar structures and characterizes the similarities and differences between them. We explore a range of dynamic behavior using data from a clear sky day and during a solar eclipse in 2017. Our results show well-defined clusters of similar causal dependencies as the system evolves. Our approach provides a methodological framework to understand how causal dependence in turbulence manifests in high-frequency data when represented through a DAG.

Causal interaction in high frequency turbulence at the biosphere-atmosphere interface: Structure-function coupling.

At the biosphere-atmosphere interface, nonlinear interdependencies among components of an ecohydrological complex system can be inferred using multivariate high frequency time series observations. Information flow among these interacting variables allows us to represent the causal dependencies in the form of a directed acyclic graph (DAG). We use high frequency multivariate data at 10 Hz from an eddy covariance instrument located at 25 m above agricultural land in the Midwestern US to quantify the evolutionary dynamics of this complex system using a sequence of DAGs by examining the structural dependency of information flow and the associated functional response. We investigate whether functional differences correspond to structural differences or if there are no functional variations despite the structural differences. We base our analysis on the hypothesis that causal dependencies are instigated through information flow, and the resulting interactions sustain the dynamics and its functionality. To test our hypothesis, we build upon causal structure analysis in the companion paper to characterize the information flow in similarly clustered DAGs from 3-min non-overlapping contiguous windows in the observational data. We characterize functionality as the nature of interactions as discerned through redundant, unique, and synergistic components of information flow. Through this analysis, we find that in turbulence at the biosphere-atmosphere interface, the variables that control the dynamic character of the atmosphere as well as the thermodynamics are driven by non-local conditions, while the scalar transport associated with CO2 and H2O is mainly driven by short-term local conditions.

A significant diurnal pattern of ammonia dry deposition to a cropland is detected by an open-path quantum cascade laser-based eddy covariance instrument

Large uncertainties and challenges remain in the quantification of land-atmosphere exchanges of ammonia (NH3), mainly due to limitations in measurement techniques. In this study, the eddy covariance (EC) technique based on an open-path quantum cascade laser (QCL) spectrometer was used to measure the NH3 fluxes at a typical cropland in the North China Plain, one of the global NH3 hotspots. It is the first attempt of measuring both NH3 volatilization and deposition fluxes at an agricultural ecosystem using the open-path instrument-based EC technique. During the one-month experimental period, the NH3 fluxes were characterized by enhanced emissions after fertilizer application and persistent dry depositions after ploughing practice, with the flux magnitude varying from −0.293 to 7.29 (median: −0.042) mg N m−2 h−1. Nearly 93% of the half-hourly fluxes (absolute values) exceeded the mean instrumental flux detection limit of 9.6 μg N m−2 h−1. Nitrogen loss rate from the wheat field through NH3 volatilization was 0.57–0.71% relative to the applied nitrogen fertilizers. Ammonia deposition dominated the period after the ploughing practice, showing an average deposition rate of 0.014 kg N ha−1 d−1 with a significant diurnal pattern. Both the local emission sources and meteorological conditions influenced the variation of NH3 dry deposition. The deposition fluxes measured by the EC technique were nearly one third the results modelled by the widely used inferential model method, but the difference needs to be validated by more observations that includes different surface and meteorological conditions. This study suggests that this open-path QCL-based EC instrument is an effective tool for long-term and high-frequency measurements of ecosystem NH3 exchanges. It also enables cross-validation between different methods to improve the understanding in the atmospheric reactive nitrogen cycling.

Technical note: Novel triple O<sub>2</sub> sensor aquatic eddy covariance instrument with improved time shift correction reveals central role of microphytobenthos for carbon cycling in coral reef sands

Abstract. The aquatic eddy covariance technique stands out as a powerful method for benthic O2 flux measurements in shelf environments because it integrates effects of naturally varying drivers of the flux such as current flow and light. In conventional eddy covariance instruments, the time shift caused by spatial separation of the measuring locations of flow and O2 concentration can produce substantial flux errors that are difficult to correct. We here introduce a triple O2 sensor eddy covariance instrument (3OEC) that by instrument design eliminates these errors. This is achieved by positioning three O2 sensors around the flow measuring volume, which allows the O2 concentration to be calculated at the point of the current flow measurements. The new instrument was tested in an energetic coastal environment with highly permeable coral reef sands colonised by microphytobenthos. Parallel deployments of the 3OEC and a conventional eddy covariance system (2OEC) demonstrate that the new instrument produces more consistent fluxes with lower error margin. 3OEC fluxes in general were lower than 2OEC fluxes, and the nighttime fluxes recorded by the two instruments were statistically different. We attribute this to the elimination of uncertainties associated with the time shift correction. The deployments at ∼ 10 m water depth revealed high day- and nighttime O2 fluxes despite the relatively low organic content of the coarse sediment and overlying water. High light utilisation efficiency of the microphytobenthos and bottom currents increasing pore water exchange facilitated the high benthic production and coupled respiration. 3OEC measurements after sunset documented a gradual transfer of negative flux signals from the small turbulence generated at the sediment–water interface to the larger wave-dominated eddies of the overlying water column that still carried a positive flux signal, suggesting concurrent fluxes in opposite directions depending on eddy size and a memory effect of large eddies. The results demonstrate that the 3OEC can improve the precision of benthic flux measurements, including measurements in environments considered challenging for the eddy covariance technique, and thereby produce novel insights into the mechanisms that control flux. We consider the fluxes produced by this instrument for the permeable reef sands the most realistic achievable with present-day technology.

Evapotranspiration and energy partitioning across a forest-shrub vegetation gradient in a subarctic, alpine catchment

As a result of altitude and latitude amplified climate change, widespread changes in vegetation composition, density and distribution have been observed across northern regions. Despite wide documentation of shrub proliferation and treeline advance, few field-based studies have evaluated the hydrological implications of these changes. Quantification of total evapotranspiration (ET) across a range of vegetation gradients is essential for predicting water yield, yet challenging in cold alpine catchments due to heterogeneous land cover, including both boreal forest and shrub taiga ecosystems. Here, we present six years of surface energy balance components and ET dynamics at three sites along an elevational gradient in a subarctic, alpine catchment near Whitehorse, Yukon Territory, Canada. These sites span a gradient of thermal and vegetation regimes, providing a space-for-time comparison for future ecosystem shifts: 1) a low-elevation boreal white spruce forest (~12–20 m), 2) a mid-elevation subalpine taiga comprised of tall, dense willow (Salix) and birch (Betula) shrubs (~1–3 m) and 3) a high-elevation subalpine taiga with short, sparse shrub cover (<0.75 m) and moss, lichen, and bare rock. Eddy covariance instrumentation ran year-round at the forest and during the growing season at the two shrub sites. Total ET decreased and interannual variability increased with elevation, with mean May to September ET totals of 349 (±3) mm at the forest, 249 (±10) mm at the tall, dense shrub site, and 240 (±26) mm at the short, sparse shrub site. Comparatively, over the same period, ET:R ratios were the highest and most variable at the forest (2.19 ± 0.37) and similar at the tall, dense shrub (1.22 ± 0.09) and short, sparse shrub (1.14 ± 0.05) sites. Our results suggest that advances in treeline will increase overall ET and lower interannual variability; however, the large growing season water deficit at the forest indicates strong reliance on soil moisture from late fall and snowmelt recharge. In contrast, ET was considerably less at the cooler higher elevation shrub sites, which exhibited similar ET losses over 6 years despite differences in shrub height and abundance. ET rates between the two shrub sites were similar throughout the year, except during the peak growing season. Greater interannual variability in ET at the short, sparse shrub site indicates the reduced influence of vegetation controls on ET. Results suggest that predicted changes in vegetation type and structure in northern regions will have a considerable impact on water partitioning and will vary in a complex way in response to changing precipitation timing, phase and magnitude, growing season length, and vegetation snow and rain interactions.

Atmospheric CO2 Exchange of a Small Mountain Lake: Limitations of Eddy Covariance and Boundary Layer Modeling Methods in Complex Terrain

AbstractLakes receive and transform significant amounts of terrestrial carbon and are often considered a source of atmospheric carbon dioxide (CO2). Yet, continuous direct measurements of lake‐atmosphere CO2 exchange with high temporal resolution are sparse. In this study, we measured the CO2 exchange of a mountain lake in the eastern Austrian Alps continuously for one year using the eddy covariance (EC) and the boundary layer model (BLM) approaches. Results from both the EC and the BLM methods indicated the lake to be a small source of atmospheric CO2 with highest emissions in fall. EC flux measurements were affected by low‐frequency contributions especially during low wind conditions. The CO2 concentration gradient at the air‐water interface decreased during night‐time due to an increase in atmospheric CO2 above the lake, likely caused by cold and CO2‐rich air draining from the surrounding land. Consequently, BLM fluxes were lower during night‐time than during daytime. This diel pattern was lacking in the EC flux measurements because the EC instruments deployed at the shore of the lake did not capture low nocturnal lake CO2 fluxes due to the local wind regime. Overall, this study illustrates the effect of the surrounding landscape on lake‐atmosphere flux measurements. We conclude that estimating CO2 evasion from lakes situated in complex topography needs to explicitly account for biases in EC flux measurements caused by low‐frequency contributions and local wind regimes.

Quantifying the Stable Water Isotopologue Exchange Between the Snow Surface and Lower Atmosphere by Direct Flux Measurements

AbstractSurface processes in high latitudes play an important role in global climate and thus understanding the physics of these systems is critical for improving climate projections. The characterization of the stable water isotopologue flux between the surface and the atmosphere offers the potential to constrain parameterizations of these physical surface exchange processes in numerical models. In addition, observations of isotopologue surface fluxes allow the evaluation of surface fluxes as a process influencing the formation of the climate signal retrieved from ice core isotopologue records. Here, we present a record of stable water isotopologue surface fluxes measured in‐situ in the accumulation zone of the Greenland Ice Sheet at the East Greenland Ice Core Project site. We measured isotopologue fluxes above the snow surface directly by combining high‐frequency eddy covariance measurements with low‐frequency isotopologue measurements from a cavity ring‐down spectrometer (CRDS). We developed a method to correct for the high‐frequency loss of the CRDS by combining humidity measurements from both the CRDS and eddy covariance instruments. Using this approach our measurements provide the first direct observations of water isotopologue fluxes in polar areas. We observed a clear diurnal cycle in the fluxes of the different water isotopologues. The isotopic composition of the sublimation and deposition flux showed to be dependent on the snow and vapor isotopic composition, respectively. To a first order, the isotopic composition of the sublimation flux could be derived assuming equilibrium fractionation during sublimation.

Temporal and Spatial Characteristics of CO2 Flux in Plateau Urban Wetlands and Their Influencing Factors Based on Eddy Covariance Technique

Urban wetlands, an important part of the urban ecosystem, play an important role in regional carbon cycles and the carbon balance. To analyze the CO2 source and sink effects of plateau urban wetlands, based on the data measured by an eddy covariance instrument, the temporal and spatial characteristics of CO2 flux and their influencing factors in the urban wetland of Xining City in the Qinghai Province of China during a warm season (July to September 2020) were studied. The results show that: (1) On the daily scale, the CO2 flux exhibited an obvious “U”-type variation, characterized by strong uptake in the daytime and weak emission at night, with an average daily flux of −0.05 mg·m−2·s−1. The CO2 uptake peak of the wetland took place at 13:00 (−0.62 mg·m−2·s−1), and the emission peak occurred at 23:30 (0.34 mg·m−2·s−1); (2) on the monthly scale, the CO2 flux of the wetland in the study period showed a net uptake each month. The flux increased month by month, and the maximum value occurred in September (−142.82 g·m−2·month−1); (3) from a spatial point of view, the river area showed a weak CO2 uptake (−0.07 ± 0.03 mg·m−2·s−1), while the artificial wetland area showed a strong CO2 uptake (−0.14 ± 0.03 mg·m−2·s−1). The former was significantly lower than the latter (p &lt; 0.01); (4) the regression analysis results show that the CO2 flux was significantly correlated with PAR, VPD, Tsoil, and SWC (p &lt; 0.01). The relationships between the flux and PAR, Tsoil, and SWC were rectangular hyperbola (y = 0.2304 − 2 × 10−3x/(0.9037 + 0.0022x), R2 = 0.64), exponential (y = 0.046exp(0.091x), R2 = 0.88), and quadratic (y = −0.0041x2 + 0.1784x − 1.6946, R2 = 0.83), respectively. Under the joint action of various environmental factors, the urban wetland ecosystem in plateau displayed a strong carbon sink function in warm seasons. This study can establish a data scaffold for the accurate estimation of carbon budget of this type of ecosystem.

Modeling Transpiration with Sun-Induced Chlorophyll Fluorescence Observations via Carbon-Water Coupling Methods

Successfully applied in the carbon research area, sun-induced chlorophyll fluorescence (SIF) has raised the interest of researchers from the water research domain. However, current works focused on the empirical relationship between SIF and plant transpiration (T), while the mechanistic linkage between them has not been fully explored. Two mechanism methods were developed to estimate T via SIF, namely the water-use efficiency (WUE) method and conductance method based on the carbon–water coupling framework. The T estimated by these two methods was compared with T partitioned from eddy covariance instrument measured evapotranspiration at four different sites. Both methods showed good performance at the hourly (R2 = 0.57 for the WUE method and 0.67 for the conductance method) and daily scales (R2 = 0.67 for the WUE method and 0.78 for the conductance method). The developed mechanism methods provide theoretical support and have a great potential basis for deriving ecosystem T by satellite SIF observations.

Technical note: Measurements and data analysis of sediment–water oxygen flux using a new dual-optode eddy covariance instrument

Abstract. Sediment–water oxygen fluxes are widely used as a proxy for organic carbon production and mineralization at the seafloor. In situ fluxes can be measured non-invasively with the aquatic eddy covariance technique, but a critical requirement is that the sensors of the instrument are able to correctly capture the high-frequency variations in dissolved oxygen concentration and vertical velocity. Even small changes in sensor characteristics during deployment as caused, e.g. by biofouling can result in erroneous flux data. Here we present a dual-optode eddy covariance instrument (2OEC) with two fast oxygen fibre sensors and document how erroneous flux interpretations and data loss can effectively be reduced by this hardware and a new data analysis approach. With deployments over a carbonate sandy sediment in the Florida Keys and comparison with parallel benthic advection chamber incubations, we demonstrate the improved data quality and data reliability facilitated by the instrument and associated data processing. Short-term changes in flux that are dubious in measurements with single oxygen sensor instruments can be confirmed or rejected with the 2OEC and in our deployments provided new insights into the temporal dynamics of benthic oxygen flux in permeable carbonate sands. Under steady conditions, representative benthic flux data can be generated with the 2OEC within a couple of hours, making this technique suitable for mapping sediment–water, intra-water column, or atmosphere–water fluxes.

To What Extend Does the Eddy Covariance Footprint Cutoff Influence the Estimation of Surface Energy Fluxes Using Two Source Energy Balance Model and High-Resolution Imagery in Commercial Vineyards?

Validation of surface energy fluxes from remote sensing sources is performed using instantaneous field measurements obtained from eddy covariance (EC) instrumentation. An eddy covariance measurement is characterized by a footprint function / weighted area function that describes the mathematical relationship between the spatial distribution of surface flux sources and their corresponding magnitude. The orientation and size of each flux footprint / source area depends on the micro-meteorological conditions at the site as measured by the EC towers, including turbulence fluxes, friction velocity (ustar), and wind speed, all of which influence the dimensions and orientation of the footprint. The total statistical weight of the footprint is equal to unity. However, due to the large size of the source area / footprint, a statistical weight cutoff of less than one is considered, ranging between 0.85 and 0.95, to ensure that the footprint model is located inside the study area. This results in a degree of uncertainty when comparing the modeled fluxes from remote sensing energy models (i.e., TSEB2T) against the EC field measurements. In this research effort, the sensitivity of instantaneous and daily surface energy flux estimates to footprint weight cutoffs are evaluated using energy balance fluxes estimated with multispectral imagery acquired by AggieAir sUAS (small Unmanned Aerial Vehicle) over commercial vineyards near Lodi, California, as part of the ARS-USDA Agricultural Research Service's Grape Remote Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) project. The instantaneous fluxes from the eddy covariance tower will be compared against instantaneous fluxes obtained from different TSEB2T aggregated footprint weights (cutoffs). The results indicate that the size, shape, and weight of pixels inside the footprint source area are strongly influenced by the cutoff values. Small cutoff values, such as 0.3 and 0.35, yielded high weights for pixels located within the footprint domain, while large cutoffs, such as 0.9 and 0.95, result in low weights. The results also indicate that the distribution of modelled LE values within the footprint source area are influenced by the cutoff values. A wide variation in LE was observed at high cutoffs, such as 0.90 and 0.95, while a low variation was observed at small cutoff values, such as 0.3. This happens due to the large number of pixel units involved inside the footprint domain when using high cutoff values, whereas a limited number of pixels are obtained at lower cutoff values.

Evaluating the performance of two SEB models for estimating ET based on satellite images in arid regions

Surface energy balance (SEB) models are one of the most important methods for estimating evapotranspiration (ET). This study was aimed at assessing the applications of two SEB models under arid conditions. This was achieved by integrating in situ meteorological data and Landsat 8 satellite images for two consecutive years (2014 and 2015) for alfalfa cultivation in 2014 and maize cultivation in 2015. The performance of the two SEB models was evaluated by comparing the ET estimated by the SEB models and that measured using an Eddy covariance (EC) instrument. Mapping the ET at high resolution using internalized calibration (METRIC) displayed the best performance in 2014, with a coefficient of determination, R2 of 0.8, followed by the simplified surface energy balance index (S-SEBI) model (with R2 = 0.67). In addition, METRIC showed high efficiency, with a Nash Sutcliffe (NSE) model efficiency coefficient of 0.98, followed by S-SEBI, with an NSE of 0.93. Poor performance was observed in 2015 where the R2 for both METRIC and S-SEBI were 0.3 and 0.45, respectively. In addition, the NSE for METRIC decreased to 0.91. Conversely, the NSE for S-SEBI improved to 0.97. Therefore, the performance of the models was affected by instability due to soil water content (SWC) and low precipitation (62.2 mm in 2015). However, the performance of METRIC was better than that of S-SEBI. In general, METRIC is considered a good SEB model for arid regions. In addition, S-SEBI could be an adequate model for overcoming the difficulty associated with obtaining meteorological data.

Surface renewal measurements of H, λE and CO2 fluxes over two different agricultural systems

The importance of understanding turbulent scalar exchange over agricultural landscapes motivated this study of the surface renewal (SR) method for deployment in place of or alongside eddy covariance (EC) instrumentation. High-frequency (20 Hz) scalar data were used with turbulence and similarity parameters for SR measurements of turbulent sensible heat (H), latent heat (λE), and CO2 (Fc) flux. The eddy covariance method was used to provide a reference data set to compare the performance of SR to EC flux measurements when the SR input requirements were determined with either: (1) fast-response (SR1) or (2) slow-response (SR2) wind velocities. We test SR1 and SR2 over two agricultural crops, cotton and rice, that are suitable for adaptive (“climate-smart”) management solutions which rely on decisions informed by extensive micrometeorological measurements. One advantage that the SR method provides is its simplicity of deployment and maintenance, requiring less energy and resources than typical EC networks. Regardless of the crop and scalar eddy flux, both SR flux methods agreed well with the EC flux measurements; coefficients of determination (R2) and slopes (s) of linear regression analysis ranges were [0.88, 0.98] and [1.01, 1.22], respectively. It was concluded that when EC measurements are unavailable, SR may be used as an alternative for additional climate-smart agriculture research efforts and this method may allow for higher spatial monitoring resolution because of the possibility to avoid the use of sonic anemometry.

Response of Tallgrass Prairie to Management in the U.S. Southern Great Plains: Site Descriptions, Management Practices, and Eddy Covariance Instrumentation for a Long-Term Experiment

Understanding the consequences of different management practices on vegetation phenology, forage production and quality, plant and microbial species composition, greenhouse gas emissions, and water budgets in tallgrass prairie systems is vital to identify best management practices. As part of the Southern Plains Long-Term Agroecosystem Research (SP-LTAR) grassland study, a long-term integrated Grassland-LivestOck Burning Experiment (iGLOBE) has been established with a cluster of six eddy covariance (EC) systems on differently managed (i.e., different burning and grazing regimes) native tallgrass prairie systems located in different landscape positions. The purpose of this paper is to describe this long-term experiment, report preliminary results on the responses of differently managed tallgrass prairies under variable climates using satellite remote sensing and EC data, and present future research directions. In general, vegetation greened-up and peaked early, and produced greater forage yields in burned years. However, drought impacts were greater in burned sites due to reductions in soil water availability by burning. The impact of grazing on vegetation phenology was confounded by several factors (e.g., cattle size, stocking rate, precipitation). Moreover, prairie systems located in different landscapes responded differently, especially in dry years due to differences in water availability. The strong correspondence between vegetation phenology and eddy fluxes was evidenced by strong linear relationships of a greenness index (i.e., enhanced vegetation index) with evapotranspiration and gross primary production. Results indicate that impacts of climate and management practices on vegetation phenology may profoundly impact carbon and water budgets of tallgrass prairie. Interacting effects of multiple management practices and inter-annual climatic variability on the responses of tallgrass prairie highlight the necessity of establishing an innovative and comprehensive long-term experiment to address inconsistent responses of tallgrass prairie to different intensities, frequencies, timing, and duration of management practices, and to identify best management practices.

An evaluation of the flux-gradient and the eddy covariance method to measure CH4, CO2, and H2O fluxes from small ponds

Despite their small overall area, small ponds play a large role in the greenhouse gas budgets of inland water bodies. This study aims to evaluate the performance of the flux-gradient (FG) and the eddy covariance (EC) method for measuring the fluxes of CO2, CH4, and H2O at two small fish ponds (fetch < 120 m) in subtropical climate conditions. The EC fluxes were subject to two sources of error: high frequency flux loss and footprint contamination. Of the three gaseous fluxes, the CH4 flux suffered the largest high frequency loss (18%) due to a combination of low EC instrument height and long optical path of the CH4 analyzer. Despite the low measurement height, the EC fluxes were influenced by sources outside the boundary of the target fish ponds, with the footprint contamination most severe on the CO2 flux and least severe on the CH4 flux. With regards to the FG method, one major uncertainty lies in the eddy diffusivity calculation. Of the three eddy diffusivity models evaluated [the aerodynamic (AE) model deploying the full Obukhov stability correction, the modified Bowen-ratio model using H2O as a tracer, and the wind profile model for neutral stability], the AE model yielded the best results for the CO2 and CH4 fluxes. Our results support Horst’s (1999, Boundary-Layer Meteorology 90, 171) theoretical prediction that the footprint of the AE flux based on a two-level concentration profile measurement should be much smaller than that of the gradient flux footprint and the EC flux footprint at the geometric mean of the two heights. We conclude that the most appropriate micrometeorological method for measuring fluxes from small water bodies is a hybrid scheme, whereby an EC system is deployed to measure the eddy diffusivity and a precision gas analyzer is used to obtain the concentration gradient of the target gas.

Measurement of Unirrigated Turfgrass Evapotranspiration Rate in the Red River Valley

Core Ideas Soil moisture is needed in defining well‐watered turfgrass condition in evapotranspiration measurement. Deep soil moisture supports turfgrass growth when surface soil moisture is not sufficient. The ETa can be estimated from 0.96 ETo using the ASCE‐EWRI standardized method for well‐watered turfgrass. The ASCE‐EWRI standardized reference ET equation can be used for water management of turfgrass in northern cool climates and during drought periods. Turfgrass actual evapotranspiration (ETa) measurements are critical for water management and irrigation scheduling. With no historical ETa measurements in eastern North Dakota, turfgrass ETa rates were measured with the residual method using eddy covariance instrumentation and two arrays of soil moisture sensors on unirrigated turfgrass under natural conditions in the 2011, 2012, and 2013 growing seasons. An on‐site weather station provided weather data to calculate the standardized grass‐based reference evapotranspiration (ETo) (Allen et al., 2005). The daily ETa/ETo ratios were screened using the criteria of soil moisture ≥50% of available water for the top 30 cm of the root zone, rain amounts ≤10 mm, and a recovering period after drought. The screened monthly average ETa/ETo ratios for the unirrigated turfgrass were 1.03, 0.98, 0.94, 0.90, 0.82, and 1.18 from May to October. The mean ETa/ETo ratio for the entire growing seasons was 0.96, implying that the American Society of Civil Engineering–Environmental and Water Resource Institute ETo method was valid for guiding the turfgrass ETa calculation even in unirrigated and cold climate conditions. Because this is the first reported study on ETa measurement of a turfgrass site, the limited data can provide a baseline on water management for turfgrass under various weather conditions in this region. The results indicated that a monthly refinement of ETa/ETo values might be required to maintain the landscape turfgrass quality more precisely in terms of water management.

Advancing Terrestrial Ecosystem Science With a Novel Automated Measurement System for Sun‐Induced Chlorophyll Fluorescence for Integration With Eddy Covariance Flux Networks

AbstractSun‐induced chlorophyll fluorescence (SIF) provides critical information on the dynamics of gross primary productivity, a unique role not readily achievable using other methods. Long‐term continuous SIF observations have the potential to advance terrestrial ecosystem science. Realizing this potential, however, requires synergistic implementation of SIF measurements within eddy covariance (EC) flux networks. There is a need for SIF systems that can integrate seamlessly with EC instrumentation to maximize synergistic use of obtained data. Here we introduce the Fluorescence Auto‐Measurement Equipment (FAME) and protocol that fulfill such a purpose. FAME is designed specifically for plug‐and‐play integration with existing EC data acquisition systems. Its innovative hardware and software designs provide versatility, extensibility, autonomous operation, and ease of maintenance for acquiring SIF data of high quality and quantity. A major novel feature of FAME is its synchronized sampling of spectral irradiance and environmental variables, allowing for more precise interpretation of the SIF signal. FAME has been deployed since September 2016 at the Missouri Ozark AmeriFlux site, providing high‐quality measurements even when air temperatures approached 40 °C. Results reveal that canopy SIF saturated or even slightly decreased at high light, similar to leaf‐level photosynthesis. Clear diurnal hysteresis was observed: For the same light, morning SIF was higher than afternoon. Dynamic energy dissipation processes and stress‐induced movements of chloroplasts and leaves may explain the observed pattern. The technology and measurement protocol introduced here advances the coordinated observation of SIF and EC fluxes and represents a step change in observational ecosystem and carbon cycle science research.

Annual ecosystem respiration of maize was primarily driven by crop growth and soil water conditions

In the context of global warming, carbon dioxide emissions have become a global concern. Cropland respiration is an important component of carbon dioxide emissions from terrestrial ecosystem. A large number of studies have investigated cropland respiration, although many controversies remain about its interannual variations and mechanisms.In this study, an eddy covariance instrument was used to observe carbon fluxes in a maize field for four consecutive years (2014–2017) in the arid region of Northwest China. The night-time respiration rates measured by eddy covariance were used to validate the accuracy of the Van’t Hoff, Arrhenius, and Taylor models in estimating the respiration rate of a maize field.All three models performed well, although the Van’t Hoff model had the highest accuracy. The three models were used to simultaneously estimate the respiration rate of the maize field throughout the growth season. The results showed that in the years 2014, 2015, 2016, and 2017, the annual respiration rates were 485, 1063, 711, and 651 g m−2y-1, respectively. Surprisingly, the respiration rate in 2015 was markedly higher than that in the other three years, and the values were 119%, 49%, and 63% higher than the rates in 2014, 2016, and 2017, respectively. To interpret this observation, this article analyzed the relationships between the respiration rate in the maize field ecosystem and the maximum leaf area index, air temperature, soil surface temperature, and soil water content. The results show that at the interannual scale, the ecosystem respiration showed significant linear positive correlations with the maximum leaf area index and soil water content. The highest values for canopy area, net radiation, irrigation rate, and soil water content were observed in 2015; the crop biomass in 2015 was also greater than that in the other three years, which significantly increased the crop respiration and caused 2015 to have the highest respiration rate.The results showed that at the interannual scale, crop growth and soil surface water conditions were the critical determinants of respiration. This study provided a new perspective and a basis for an in-depth understanding of the mechanism of carbon dioxide emission in croplands.