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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.

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.

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.

Representation of surface roughness effects on aeolian sediment transport is a key source of uncertainty in wind erosion models. Drag partitioning schemes are used to account for roughness by scaling the soil entrainment threshold by the ratio of shear stress on roughness elements to that on the vegetated land surface. This approach does not explicitly account for the effects of roughness configuration, which may be important for sediment flux. Here we investigate the significance of roughness configuration for aeolian sediment transport, the ability of drag partitioning approaches to represent roughness configuration effects, and the implications for model accuracy. We use wind tunnel measurements of surface shear stress distributions to calculate sediment flux for a suite of roughness configurations, roughness densities, and wind velocities. Roughness configuration has a significant effect on sediment flux, influencing estimates by more than 1 order of magnitude. Measured and modeled drag partitioning approaches overestimate the predicted flux by 2 to 3 orders of magnitude. The drag partition is sensitive to roughness configuration, but current models cannot effectively represent this sensitivity. The effectiveness of drag partitioning approaches is also affected by estimates of the aerodynamic roughness height used to calculate wind shear velocity. Unless the roughness height is consistent with the drag partition, resulting fluxes can show physically implausible patterns. These results should make us question current assessments of the magnitude of vegetated dryland dust emissions. Representing roughness effects on surface shear stress distributions will reduce uncertainty in quantifying wind erosion, enabling better assessment of its impacts and management solutions.

Partitioning of CO2 exchange into canopy (FA) and soil (FR) flux components is essential to improve our understanding of ecosystem processes. The stable isotope C18OO can be used for flux partitioning, but this approach depends on the magnitude and consistency of the isotope disequilibrium (Deq), i.e., the difference between the isotope compositions of FR (δA) and FA (δR). In this study, high temporal resolution isotopic data were used (1) to test the suitability of existing steady state and nonsteady models to estimate H218O enrichment in a mixed forest canopy, (2) to investigate the temporal dynamics of δA using a big-leaf parameterization, and (3) to quantify the magnitude of the C18OO disequilibrium (Deq) in a temperate deciduous forest throughout the growing season and to determine the sensitivity of this variable to the CO2 hydration efficiency (θeq). A departure from steady state conditions was observed even at midday in this study, so the nonsteady state formulation provided better estimates of leaf water isotope composition. The dynamics of δR was mainly driven by changes in soil water isotope composition, caused by precipitation events. Large Deq values (up to 11‰) were predicted; however, the magnitude of the disequilibrium was variable throughout the season. The magnitude of Deq was also very sensitive to the hydration efficiencies in the canopy. For this temperate forest during most of the growing season, the magnitude of Deq was inversely proportional to θeq, due to the very negative δR signal, which is contrary to observations for other ecosystems investigated in previous studies.

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.

Analytical Lagrangian equations capable of predicting concentration profiles from known source distributions offer the opportunity to calculate source/sink distributions through inverted forms of these equations. Inverse analytical Lagrangian equations provide a practical means of estimating source profiles using concentration and turbulence measurements. Uncertainty concerning estimates of the essentially immeasurable Lagrangian length scale ( $${\mathcal{L}}$$ ), a key input, impedes the operational practicality of this method. The present study evaluates $${\mathcal{L}}$$ within a corn canopy by using field measurements to constrain an analytical Lagrangian equation. Measurements of net CO2 flux, soil-to-atmosphere CO2 flux, and in-canopy profiles of CO2 concentration provided the information required to solve for $${\mathcal{L}}$$ in a global optimization algorithm for 30-min time intervals. For days when the canopy was a strong CO2 sink, the optimization frequently located $${\mathcal{L}}$$ profiles that follow a convex shape. A constrained optimization then fit the profile shape to a smooth sigmoidal equation. Inputting the optimized $${\mathcal{L}}$$ profiles in the forward and inverse Lagrangian equations leads to strong correlations between measured and calculated concentrations and fluxes. Coefficients of the sigmoidal equation were specific to each 30-min period and did not scale with any measured variable. Plausible looking $${\mathcal{L}}$$ profiles were associated with negative bulk Richardson number values. Once the canopy senesced, a simple eddy diffusivity profile sufficed to relate concentrations and sources in the analytical Lagrangian equations.

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.

Understanding of the atmosphere/forest canopy exchange of volatile organic compounds (VOCs) requires insight into deposition, emission, and chemical reactions of VOCs below the canopy. Currently, uncertainties in canopy processes, such as stomatal uptake, deposition, and sub-canopy chemistry, make it difficult to derive biogenic VOC emission inventories from canopy VOC concentration gradients. Between 18 July and 9 August 2009, VOCs were measured with proton-transfer-reaction mass spectrometry (PTR-MS) at 6 heights between 1 and 6 m beneath a 23 m high mixed-forest canopy. Measured VOCs included methanol, isoprene, acetone, methacrolein + methyl vinyl ketone (MACR+MVK), monoterpenes and sesquiterpenes. There are pronounced differences in the behaviour of isoprene and its by-products and that of the terpenes. Non-terpene fluxes are predominantly downward. In contrast, the terpene fluxes are significantly upward. A 1-dimensional canopy model was used to compare results to measurements with and without surface deposition of isoprene and MACR+MVK and emissions of monoterpenes and sesquiterpenes. Results suggest deposition velocities of 27 mm s−1 for isoprene and 12 mm s−1 for MACR+MVK and daytime surface emission rates of 63 μg m−2 h−1 for monoterpenes. The modelled isoprene surface deposition is approximately 2% of the canopy top isoprene emissions and the modelled emissions of monoterpenes comprise approximately 15 to 27% of the canopy-top monoterpene emissions to the atmosphere. These results suggest that surface monoterpene emissions are significant for forest canopy/atmosphere exchange for this mixed forest location and surface uptake is relatively small for all the species measured in this study.

Soil temperature can influence the functioning of roots in many ways. If soil moisture and nutrient availability are adequate, rates of root length extension and root mortality increase with increasing soil temperature, at least up to an optimal temperature for root growth, which seems to vary among taxa. Root growth and root mortality are highly seasonal in perennial plants, with a flush of growth in spring and significant mortality in the fall. At present we do not understand whether root growth phenology responds to the same temperature cues that are known to control shoot growth. We also do not understand whether the flush of root growth in the spring depends on the utilization of stored nonstructural carbohydrates, or if it is fueled by current photosynthate. Root respiration increases exponentially with temperature, but Q10 values range widely from c. 1.5 to > 3.0. Significant questions yet to be resolved are: whether rates of root respiration acclimate to soil temperature, and what mechanisms control acclimation if it occurs. Limited data suggest that fine roots depend heavily on the import of new carbon (C) from the canopy during the growing season. We hypothesize that root growth and root respiration are tightly linked to whole-canopy assimilation through complex source–sink relationships within the plant. Our understanding of how the whole plant responds to dynamic changes in soil temperature, moisture and nutrient availability is poor, even though it is well known that multiple growth-limiting resources change simultaneously through time during a typical growing season. We review the interactions between soil temperature and other growth-limiting factors to illustrate how simple generalizations about temperature and root functioning can be misleading.

Summary 1 Due to a unique set of circumstances, we were able to excavate an entire spruce (Picea) forest in Michigan’s Upper Peninsula, USA, which was buried in the early Holocene (9928 2133 uncalibrated 14 C years BP). Trees ranged from 50cm in diameter, and dominants were approximately 9m tall. The stand was multi-aged, with a maximum tree age of 145years. Well-preserved stem cross-sections (n=140) were recovered and the entire stand was mapped. 2 Stand reconstruction combined with pollen and sediment analysis revealed a pure spruce forest in the sandy lowlands surrounded by hills dominated by pine, oak and birch. These results are consistent with the idea that topography and substrate played an important role in determining forest composition during Holocene plant migrations. 3 Very rapid climate fluctuations were occurring 10000BP. The extensive spruce forests that once dominated much of interior North America were being replaced by subboreal and temperate conifer and hardwood species migrating northward. During this dynamic period in the Earth’s history, patterns of plant community change are usually inferred from the study of pollen assemblages, and lack of detailed stand level information has prevented the direct comparison of the composition, age, structure and growth rates of Holocene forests with those that exist today. 4 Our findings that the age-class distribution, size, spatial distribution of trees and radial growth rates of white spruce (Picea glauca) can be remarkably similar between the two time periods suggest that forest population and growth processes responsible for today’s advancing tree-lines appear to have been at work 10000years ago.

[1] Surface roughness aids to ameliorate wind erosion by extracting a portion of the wind's momentum thereby reducing the quantity of stress on the surface. This paper evaluates the effect of different spatial arrangements of surface roughness on the partition of average drag forces and distribution of stress at the surface. A new tiered force balance was used in a wind tunnel to independently and simultaneously measure the drag on arrays of roughness elements and the drag on the intervening surface. In addition, Irwin sensors recorded point measurements of surface shear stress within the arrays. Roughness arrays consisted of small cylinders in four different spatial arrangements, one being staggered and three being simplifications of natural roughness configurations, at four roughness densities. Results from the tiered force balance and Irwin sensors indicate that the roughness configuration has a small impact on the average (R) and maximum (R″) drag partition. The protection of the surface increased with roughness density regardless of the roughness arrangement. Point measurements of shear stress revealed that the roughness configuration had a small impact on the distribution of shear stress at the surface, and that the maximum shear stress scaled to the average shear stress. Drag partition measurements were compared to the ratios predicted by the Raupach et al. (1993) model and a good degree of agreement was found for all configurations when using measured values of the β and m parameter.