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Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use.

Aerodynamic canopy height (h(a)) is the effective height of vegetation canopy for its influence on atmospheric fluxes and is a key parameter of surface-atmosphere coupling. However, methods to estimate h(a) from data are limited. This synthesis evaluates the applicability and robustness of the calculation of h(a) from eddy covariance momentum-flux data. At 69 forest sites, annual h(a) robustly predicted site-to-site and year-to-year differences in canopy heights (R-2=0.88, 111site-years). At 23 cropland/grassland sites, weekly h(a) successfully captured the dynamics of vegetation canopies over growing seasons (R-2>0.70 in 74site-years). Our results demonstrate the potential of flux-derived h(a) determination for tracking the seasonal, interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. The large-scale and time-varying h(a) derived from flux networks worldwide provides a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure. Plain Language Summary Vegetation canopy height is a key descriptor of the Earth surface and is in use by many modeling and conservation applications. However, large-scale and time-varying data of canopy heights are often unavailable. This synthesis evaluates the applicability and robustness of the calculation of canopy heights from the momentum flux data measured at eddy covariance flux tower sites (i.e., meteorological observation towers with high frequency measurements of wind speed and surface fluxes). We show that the aerodynamic estimation of annual canopy heights robustly predicts the site-to-site and year-to-year differences in canopy heights across a wide variety of forests. The weekly aerodynamic canopy heights successfully capture the dynamics of vegetation canopies over growing seasons at cropland and grassland sites. Our results demonstrate the potential of aerodynamic canopy heights for tracking the seasonal, interannual, and/or decadal dynamics of vegetation canopies including growth, harvest, land use change, and disturbance. Given the amount of data collected and the diversity of vegetation covered by the global networks of eddy covariance flux tower sites, the flux-derived canopy height has great potential for providing a new benchmark for regional and global Earth system models and satellite remote sensing of canopy structure. U.S. Department of Energy's Office of ScienceUnited States Department of Energy (DOE) [DE-SC0012456, DE-AC02-05CH11231] This study is supported by FLUXNET and AmeriFlux projects, sponsored by U.S. Department of Energy's Office of Science (DE-SC0012456 and DE-AC02-05CH11231). We thank the supports from AmeriFlux Data Team: Gilberto Pastorello, Deb Agarwal, Danielle Christianson, You-Wei Cheah, Norman Beekwilder, Tom Boden, Bai Yang, and Dario Papale, and Berkeley Biomet Lab: Siyan Ma, Joseph Verfaillie, Elke Eichelmann, and Sara Knox. This work uses eddy covariance and BADM data acquired and shared by the investigators involved in the AmeriFlux and Fluxnet-Canada Research Network. The site list and corresponding references are provided in the supporting information. We thank Claudia Wagner-Riddle, Andy Suyker, David Cook, Asko Noormets, Paul Stoy, and Brian Amiro for providing additional data. All actual canopy height data can be downloaded from AmeriFlux BADM. The R codes and aerodynamic canopy height data can be accessed at http://github.com/chuhousen/aerodynamic_canopy_height. Public domain – authored by a U.S. government employee

Nitrous oxide (N2O) fluxes measured using the eddy-covariance method capture the spatial and temporal heterogeneity of N2O emissions. Most closed-path trace-gas analyzers for eddy-covariance measurements have large-volume, multi-pass absorption cells that necessitate high flow rates for ample frequency response, thus requiring high-power sample pumps. Other sampling system components, including rain caps, filters, dryers, and tubing, can also degrade system frequency response. This field trial tested the performance of a closed-path eddy-covariance system for N2O flux measurements with improvements to use less power while maintaining the frequency response. The new system consists of a thermoelectrically cooled tunable diode laser absorption spectrometer configured to measure both N2O and carbon dioxide (CO2). The system features a relatively small, single-pass sample cell (200 mL) that provides good frequency response with a lower-powered pump ( ∼ 250 W). A new filterless intake removes particulates from the sample air stream with no additional mixing volume that could degrade frequency response. A single-tube dryer removes water vapour from the sample to avoid the need for density or spectroscopic corrections, while maintaining frequency response. This eddy-covariance system was collocated with a previous tunable diode laser absorption spectrometer model to compare N2O and CO2 flux measurements for two full growing seasons (May 2015 to October 2016) in a fertilized cornfield in Southern Ontario, Canada. Both spectrometers were placed outdoors at the base of the sampling tower, demonstrating ruggedness for a range of environmental conditions (minimum to maximum daily temperature range: −26.1 to 31.6 °C). The new system rarely required maintenance. An in situ frequency-response test demonstrated that the cutoff frequency of the new system was better than the old system (3.5 Hz compared to 2.30 Hz) and similar to that of a closed-path CO2 eddy-covariance system (4.05 Hz), using shorter tubing and no dryer, that was also collocated at the site. Values of the N2O fluxes were similar between the two spectrometer systems (slope = 1.01, r2 = 0.96); CO2 fluxes as measured by the short-tubed eddy-covariance system and the two spectrometer systems correlated well (slope = 1.03, r2 = 0.998). The new lower-powered tunable diode laser absorption spectrometer configuration with the filterless intake and single-tube dryer showed promise for deployment in remote areas.

Diversifying annual crop rotations is postulated to promote soil ecosystem services through reduction of greenhouse gas emissions, control of soil evaporation, moderation of soil freeze-thaw cycles, increases in soil organic carbon, and reduced nutrient leaching, all of which are processes that are impacted by the water balance. A newly-installed facility with large monolithic weighing soil lysimeters dedicated to studying changes in soil ecosystem services induced by rotation diversification was installed in June 2016 in Elora, ON, Canada. The high-precision lysimeters, nine for each of two different soils (silt loam, loamy sand) are a closed system to fully evaluate water balance components. In the first year of operation, the lysimeters were not subject to any diversification treatments. This provided an opportunity to study water budget components (precipitation, P; evapotranspiration, ET; change is soil storage, Δ S; drainage, D) measured by the 9 replicate lysimeters for each soil type. The objectives of this study were to 1) determine the total uncertainty of P, ET, Δ S and D induced by data smoothing and gap filling data procedures; and 3) characterize the spatial variability of water budget components for the baseline year. Cumulative sums of water balance variables from data processing procedures found that the adaptive window and adaptive threshold (AWAT) data smoothing method introduced minimal errors (0.2 to 1.9%). Filling missing data gaps using data from replicate lysimeters, i.e., lysimeters of the same soil type and agronomy, introduced errors of only 0.3 to 0.5% for P and ET (120-day sums). There was greater uncertainty for D and Δ S (10.8% and 2.1%, respectively) because of the variability in D. P showed a small degree of spatial variation across all 18 lysimeters, with variations being 1.5% of the mean cumulative sums when using data with no gaps, which demonstrated the high precision of the lysimeter measurements. Spatial variability of evapotranspiration (ET) was higher (6.1% for the silt loam and 5.7% for the loamy sand), but within the range of variability estimated for similar lysimeter facilities. The differences in plant cover on individual lysimeters were the main source of variation for ET and S. Results inform future comparisons of water budget components for other lysimeter sites and demonstrate the suitability of this facility for examining the complex impacts of crop diversification on soil ecosystem services, providing a basis for future evaluations of water balance components.

The multi-plot flux-gradient (FG) technique is well-suited for non-intrusive measurements of agricultural N2O emissions for individually-treated field-scale plots across growing seasons at high temporal and spatial resolution. The degree of random error associated with N2O flux measurements is unknown; knowledge of these errors will increase confidence in the flux measurements and strengthen comparisons of total N2O emissions between treatments. An error estimation routine was developed to determine the random error (σ) associated with FG-measured fluxes (σF). The combination of a moving-block bootstrapping technique and the filtering method of Salesky et al. (2012) estimated the σ values for each variable used in calculating individual 30-min FG-derived fluxes. This error analysis was applied to a year-long dataset where a four-plot FG system measured N2O fluxes semi-continuously in a soybean field in Southwestern Ontario, Canada, with each plot having different treatments affecting N2O emissions. Errors of the concentration differences contributed the largest proportion to the σF values. The individual 30-min σF values did not correlate with the magnitude of the flux but were positively correlated with turbulence conditions. Random errors of N2O fluxes greater than 45 ng N m−2 s−1 had values representative of 9% of the measured flux, whereas error of fluxes close to zero frequently exceeded the value of the measured flux. Cumulating the errors over the experiment reduced the degree of error associated with the cumulated total N2O emissions with an average value of 31.5 g N ha−1, which represented on average ±5.5% of the total N2O emissions. The proposed framework is applicable to other scalar fluxes being determined by the flux-gradient method.

Dairy production constitutes a significant amount of the total global anthropogenic greenhouse gas (GHG) emission. One of the proposed strategies to mitigate GHG emission from dairy production is by enhancing soil carbon sequestration through promoting the growing of perennial over annual dairy feed crop. We determined the net ecosystem carbon budget (NECB) of a hay and corn field grown side-by-side over three years to compare the GHG mitigation potential of perennial over annual feed crops in Elora, Ontario, Canada. The NECB was determined using measurements of net ecosystem exchange (NEE), total plant carbon content, and carbon content in applied dairy manure. The greenhouse gas balance (GHGB) were determined using the NECB plus the total nitrous oxide (N 2 O) fluxes measured by a complementary study at the same site. The effect of plowing of the hay field on the NECB and GHGB was also investigated. Our observations indicate that on average over the three study years, NECB of hay (7 ± 51 g C m −2 yr −1 ) was significantly lower than corn (154 ± 79 g C m −2 yr −1 ) indicating that corn was a larger carbon source than hay. The three-year average GHGB of 796 and 127 g CO 2 -eq m −2 yr −1 for corn and hay, respectively, indicated that corn was a larger emitter of GHG than hay. The NECB was the more dominant factor than N 2 O emissions in influencing the outcome of the annual GHGB. We conclude that hay has a larger potential than corn in sequestering carbon and mitigating GHG emission even when emissions from hay plow-down are included.

Seasonal freezing induces large thaw emissions of nitrous oxide, a trace gas that contributes to stratospheric ozone destruction and atmospheric warming. Cropland soils are by far the largest anthropogenic source of nitrous oxide. However, the global contribution of seasonal freezing to nitrous oxide emissions from croplands is poorly quantified, mostly due to the lack of year-round measurements and difficulty in capturing short-lived pulses of nitrous oxide with traditional measurement methods. Here we present measurements collected with half-hourly resolution at two contrasting cropland sites in Ontario and Manitoba, Canada, over 14 and 9 years, respectively. We find that the magnitude of freeze-thaw-induced nitrous oxide emissions is related to the number of days with soil temperatures below 0 °C, and we validate these findings with emissions data from 11 additional sites from cold climates around the globe. Based on an estimate of cropland area experiencing seasonal freezing, reanalysis model estimates of soil temperature, and the relationship between cumulative soil freezing days and emissions that we derived from the cropland sites, we estimate that seasonally frozen cropland contributes 1.07 ± 0.59 Tg of nitrogen as nitrous oxide annually. We conclude that neglecting freeze-thaw emissions would lead to an underestimation of global agricultural nitrous oxide emissions by 17 to 28%.

Residue removal for biofuel production may have unintended consequences for N2O emissions from soils, and it is not clear how N2O emissions are influenced by crop residue removal from different tillage systems. Thus, we measured field-scale N2O flux over 5 years (2005–2007, 2010–2011) from an annual crop rotation to evaluate how N2O emissions are influenced by no-till (NT) compared to conventional tillage (CV), and how crop residue removal (R−) rather than crop residue return to soil (R+) affects emissions from these two tillage systems. Data from all 5 years indicated no differences in N2O flux between tillage practices at the onset of the growing season, but CT had 1.4–6.3 times higher N2O flux than NT overwinter. Nitrous oxide emissions were higher due to R− compared to R+, but the effect was more marked under CT than NT and overwinter than during spring. Our results thus challenge the assumption based on IPCC methodology that crop residue removal will result in reduced N2O emissions. The potential for higher N2O emission with residue removal implies that the benefit of utilizing biomass as biofuels to mitigate greenhouse gas emission may be overestimated. Interestingly, prior to an overwinter thaw event, dissolved organic C (DOC) was negatively correlated to peak N2O flux (r = −0.93). This suggests that lower N2O emissions with R+ vs. R− may reflect more complete stepwise denitrification to N2 during winter and possibly relate to the heterotrophic microbial capacity for processing crop residue into more soluble C compounds and a shift in the preferential C source utilized by the microbial community overwinter.

Multi-layer Lagrangian models could be useful techniques for studying stable isotope exchange within and just above plant canopies. The main objective of this study was to evaluate the use of an analytical Lagrangian analysis (localized near-field theory, LNF), to study 13CO2 and C18OO isotope exchange in different plant canopies by comparing the LNF estimates with those provided by the eddy covariance (EC) technique and the isotope flux ratio method (IFR). Mixing ratios of stable isotopes of CO2 were measured within and above a temperate deciduous forest, tallgrass prairie and corn field using a multi-port sampling system and the tunable diode laser spectroscopy technique. Wind velocity data and the net CO2 ecosystem exchange (NEE) were measured above the plant canopies using an EC system. The wind velocity data and CO2 stable isotope mixing ratios were combined with the LNF theory to infer NEE and source/sinks of isotopes inside canopies. The LNF NEE estimates were likely affected by the flux decoupling in the forest canopy, resulting in a low correlation (R2 ranging from 0.03 to 0.35) between LNF and EC NEE estimates. On the other hand, LNF NEE estimates for corn and grassland canopies showed better correlation with EC NEE estimates (R2 ranging from 0.58 to 0.85), suggesting better coupling between in and above canopy air flows. Although, both LNF and IFR estimates showed large variability, our results show that the LNF approach reduced the uncertainties of the isotope compositions of NEE when compared to the IFR approach. These results suggest that LNF is a useful tool to study CO2 isotope exchange within short canopies where flux measurements are more challenging than inside tall canopies.

Stable isotopologues of CO2, such as 13CO2 and C18OO, have been used to study the CO2 exchange between land and atmosphere. The advent of new measuring techniques has allowed near-continuous measurements of stable isotopes in the air. These measurements can be used with micrometeorological techniques, providing new tools to investigate the isotope exchange in ecosystems. The objectives of this study were to evaluate the use of the isotope flux ratio method (IFR) near the forest floor of a temperate deciduous forest and to study the temporal dynamics of δ18O of CO2 flux near the forest floor by comparing IFR estimates with estimates of δ18O of net soil CO2 flux provided by an analytical model. Mixing ratios of 12C16O2, 13CO2 and C16O18O were measured within and above a temperate deciduous forest, using the tunable diode laser spectroscopy technique. The half-hourly compositions of the CO2 flux near the forest floor (δ13CF and δ18OF) were calculated by IFR and compared with estimates provided by a modified Keeling plot technique (mKP) and by a Lagrangian dispersion analysis (WT analysis). The mKP and IFR δ18OF estimates showed good agreement (slope = 1.03 and correlation, R2 = 0.80). The δ13CF estimates from the two methods varied in a narrow range of −32.7 and −23‰; the mean (± SE) mKP and IFR δ13CF values were −27.5‰ (±0.2) and −27.3‰ (±0.1), respectively, and were statistically identical (p>0.05). WT analysis and IFR δ18OF estimates showed better correlation (R2 = 0.37) when only turbulent periods (u*>0.6 m s−1) were included in the analysis. The large amount of data captured (~95 % of half-hour periods evaluated) for the IFR in comparison with mKP (27 %) shows that the former provides new opportunities for studying δ18OF dynamics within forest canopies. Values of δ18OF showed large temporal variation, with values ranging from −31.4‰ (DOY 208) to −11.2‰ (DOY 221). Precipitation events caused substantial variation (~8‰) in δ18OF over a period of approximately 24 h. A diel trend of δ18OF was observed, with more depleted values present during the daytime. Model simulations indicate that the activity of the carbonic anhydrase enzyme was quite variable during the evaluated period. These simulations indicate that more frequent sampling of δ18O of soil water could improve the estimates of δ18O of net soil CO2 flux.

Perennial crops can deliver a wide range of ecosystem services compared to annual crops. Some of these benefits are achieved by lengthening the growing season, which increases the period of crop water and nutrient uptake, pointing to a potential role for perennial systems to mitigate soil nitrous oxide (N2 O) emissions. Employing a micrometeorological method, we tested this hypothesis in a 3-year field experiment with a perennial grass-legume mixture and an annual corn monoculture. Given that N2 O emissions are strongly dependent on the method of fertilizer application, two manure application options commonly used by farmers for each crop were studied: injection vs. broadcast application for the perennial; fall vs. spring application for the annual. Across the 3 years, lower N2 O emissions (P