Browsing by Author "Katul, Gabriel G."

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Albedo estimates for land surface models and support for a new paradigm based on foliage nitrogen concentration
(2010-02) Hollinger, David Y.; Ollinger, S. V.; Richardson, Andrew D.; Meyers, T. P.; Dail, D. B.; Martin, M. E.; Scott, N. A.; Arkebauer, T. J.; Baldocchi, Dennis D.; Clark, K. L.; Curtis, P. S.; Desai, Ankur R.; Dragoni, Danilo; Goulden, Michael L.; Gu, Lianhong; Katul, Gabriel G.; Pallardy, S. G.; Paw U, Kyaw Tha; Schmid, H. P.; Stoy, Paul C.; Suyker, Andrew E.; Verma, Shashi B.
Vegetation albedo is a critical component of the Earth's climate system, yet efforts to evaluate and improve albedo parameterizations in climate models have lagged relative to other aspects of model development. Here, we calculated growing season albedos for deciduous and evergreen forests, crops, and grasslands based on over 40 site‐years of data from the AmeriFlux network and compared them with estimates presently used in the land surface formulations of a variety of climate models. Generally, the albedo estimates used in land surface models agreed well with this data compilation. However, a variety of models using fixed seasonal estimates of albedo overestimated the growing season albedo of northerly evergreen trees. In contrast, climate models that rely on a common two‐stream albedo submodel provided accurate predictions of boreal needle‐leaf evergreen albedo but overestimated grassland albedos. Inverse analysis showed that parameters of the two‐stream model were highly correlated. Consistent with recent observations based on remotely sensed albedo, the AmeriFlux dataset demonstrated a tight linear relationship between canopy albedo and foliage nitrogen concentration (for forest vegetation: albedo=0.01+0.071%N, r2=0.91; forests, grassland, and maize: albedo=0.02+0.067%N, r2=0.80). However, this relationship saturated at the higher nitrogen concentrations displayed by soybean foliage. We developed similar relationships between a foliar parameter used in the two‐stream albedo model and foliage nitrogen concentration. These nitrogen‐based relationships can serve as the basis for a new approach to land surface albedo modeling that simplifies albedo estimation while providing a link to other important ecosystem processes.
Are ecosystem carbon inputs and outputs coupled at short time scales? A case study from adjacent pine and hardwood forests using impulse-response analysis
(2007-06) Stoy, Paul C.; Palmroth, Sari; Oishi, A. Christopher; Siqueira, Mario B. S.; Juang, Jehn-Yih; Novick, Kimberly A.; Ward, Eric J.; Katul, Gabriel G.; Oren, Ram
A number of recent studies have attributed a large proportion of soil respiration (Rsoil) to recently photoassimilated carbon (C). Time lags (τPR) associated with these pulses of photosynthesis and responses of Rsoil have been found on time scales of hours to weeks for different ecosystems, but most studies find evidence for τPR on the order of 1–5 d. We showed that such time scales are commensurate with CO2 diffusion time scales from the roots to the soil surface, and may thus be independent from photosynthetic pulses. To further quantify the role of physical (i.e. edaphic) and biological (i.e. vegetative) controls on such lags, we investigated τPR at adjacent planted pine (PP) and hardwood (HW) forest ecosystems over six and four measurement years, respectively, using both autocorrelation analysis on automated soil surface flux measurements and their lagged cross‐correlations with drivers for and surrogates of photosynthesis. Evidence for τPR on the order of 1–3 d was identified in both ecosystems and using both analyses, but this lag could not be attributed to recently photoassimilated C because the same analysis yielded comparable lags at HW during leaf‐off periods. Future efforts to model ecosystem C inputs and outputs in a pulse–response framework must combine measurements of transport in the physical and biological components of terrestrial ecosystems.
Biosphere-atmosphere exchange of CO2 in relation to climate: a cross-biome analysis across multiple time scales
(2009-10) Stoy, Paul C.; Richardson, Andrew D.; Baldocchi, Dennis D.; Katul, Gabriel G.; Stanovick, J.; Mahecha, M. D.; Reichstein, M.; Detto, Matteo; Law, Beverly E.; Wohlfahrt, Georg; Arriga, N.; Campos, J.; McCaughey, J. H.; Montagnani, Leonardo; Paw U, Kyaw Tha; Sevanto, S.; Williams, Mathew
The net ecosystem exchange of CO2 (NEE) varies at time scales from seconds to years and longer via the response of its components, gross ecosystem productivity (GEP) and ecosystem respiration (RE), to physical and biological drivers. Quantifying the relationship between flux and climate at multiple time scales is necessary for a comprehensive understanding of the role of climate in the terrestrial carbon cycle. Orthonormal wavelet transformation (OWT) can quantify the strength of the interactions between gappy eddy covariance flux and micrometeorological measurements at multiple frequencies while expressing time series variance in few energetic wavelet coefficients, offering a low-dimensional view of the response of terrestrial carbon flux to climatic variability. The variability of NEE, GEP and RE, and their co-variability with dominant climatic drivers, are explored with nearly one thousand site-years of data from the FLUXNET global dataset consisting of 253 eddy covariance research sites. The NEE and GEP wavelet spectra were similar among plant functional types (PFT) at weekly and shorter time scales, but significant divergence appeared among PFT at the biweekly and longer time scales, at which NEE and GEP were relatively less variable than climate. The RE spectra rarely differed among PFT across time scales as expected. On average, RE spectra had greater low frequency (monthly to interannual) variability than NEE, GEP and climate. CANOAK ecosystem model simulations demonstrate that "multi-annual" spectral peaks in flux may emerge at low (4+ years) time scales. Biological responses to climate and other internal system dynamics, rather than direct ecosystem response to climate, provide the likely explanation for observed multi-annual variability, but data records must be lengthened and measurements of ecosystem state must be made, and made available, to disentangle the mechanisms responsible for low frequency patterns in ecosystem CO2 exchange.
Carbon dioxide and water vapor exchange in a warm temperate grassland
(2004-01) Novick, Kimberly A.; Stoy, Paul C.; Katul, Gabriel G.; Ellsworth, D. S.; Siqueira, Mario B. S.; Juang, Jehn-Yih; Oren, Ram
Grasslands cover about 40% of the ice-free global terrestrial surface, but their contribution to local and regional water and carbon fluxes and sensitivity to climatic perturbations such as drought remains uncertain. Here, we assess the direction and magnitude of net ecosystem carbon exchange (NEE) and its components, ecosystem carbon assimilation (A c) and ecosystem respiration (R E), in a southeastern United States grassland ecosystem subject to periodic drought and harvest using a combination of eddy-covariance measurements and model calculations. We modeled A c and evapotranspiration (ET) using a big-leaf canopy scheme in conjunction with ecophysiological and radiative transfer principles, and applied the model to assess the sensitivity of NEE and ET to soil moisture dynamics and rapid excursions in leaf area index (LAI) following grass harvesting. Model results closely match eddy-covariance flux estimations on daily, and longer, time steps. Both model calculations and eddy-covariance estimates suggest that the grassland became a net source of carbon to the atmosphere immediately following the harvest, but a rapid recovery in LAI maintained a marginal carbon sink during summer. However, when integrated over the year, this grassland ecosystem was a net C source (97 g C m−2 a−1) due to a minor imbalance between large A c (−1,202 g C m−2 a−1) and R E (1,299 g C m−2 a−1) fluxes. Mild drought conditions during the measurement period resulted in many instances of low soil moisture (θ<0.2 m3m−3), which influenced A c and thereby NEE by decreasing stomatal conductance. For this experiment, low θ had minor impact on R E. Thus, stomatal limitations to A c were the primary reason that this grassland was a net C source. In the absence of soil moisture limitations, model calculations suggest a net C sink of −65 g C m−2 a−1 assuming the LAI dynamics and physiological properties are unaltered. These results, and the results of other studies, suggest that perturbations to the hydrologic cycle are key determinants of C cycling in grassland ecosystems.
Eco-hydrological controls on summertime convective rainfall triggers
(2007-01) Juang, Jehn-Yih; Katul, Gabriel G.; Porporato, Amilcare; Stoy, Paul C.; Siqueira, Mario B. S.; Detto, Matteo; Kim, Hyun-Seok; Oren, Ram
Triggers of summertime convective rainfall depend on numerous interactions and feedbacks, often compounded by spatial variability in soil moisture and its impacts on vegetation function, vegetation composition, terrain, and all the complex turbulent entrainment processes near the capping inversion. To progress even within the most restricted and idealized framework, many of the governing processes must be simplified and parameterized. In this work, a zeroth‐order representation of the dynamical processes that control convective rainfall triggers – namely land surface fluxes of heat and moisture – is proposed and used to develop a semianalytical model to explore how differential sensitivities of various ecosystems to soil moisture states modify convective rainfall triggers. The model is then applied to 4 years (2001–2004) of half‐hourly precipitation, soil moisture, environmental, and eddy‐covariance surface heat flux data collected at a mixed hardwood forest (HW), a maturing planted loblolly pine forest (PP), and an abandoned old field (OF) experiencing the same climatic and edaphic conditions. We found that the sensitivity of PP to soil moisture deficit enhances the trigger of convective rainfall relative to HW and OF, with enhancements of about 25% and 30% for dry moisture states, and 5% and 15% for moist soil moisture states, respectively. We discuss the broader implications of these findings on potential modulations of convective rainfall triggers induced by projected large‐scale changes in timberland composition within the Southeastern United States.
The Effects of Elevated Atmospheric CO2 and Nitrogen Amendments on Subsurface CO2 Production and Concentration Dynamics in a Maturing Pine Forest
(2009-05) Daly, Edoardo; Palmroth, Sari; Stoy, Paul C.; Siqueira, Mario B. S.; Oishi, A. Christopher; Juang, Jehn-Yih; Oren, Ram; Porporato, Amilcare; Katul, Gabriel G.
Profiles of subsurface soil CO2 concentration, soil temperature, and soil moisture, and throughfall were measured continuously during the years 2005 and 2006 in 16 locations at the free air CO2 enrichment facility situated within a temperate loblolly pine (Pinus taeda L.) stand. Sampling at these locations followed a 4 by 4 replicated experimental design comprised of two atmospheric CO2 concentration levels (ambient [CO2]a, ambient + 200 ppmv, [CO2]e) and two soil nitrogen (N) deposition levels (ambient, ambient + fertilization at 11.2 gN m−2 year−1). The combination of these measurements permitted indirect estimation of below ground CO2 production and flux profiles in the mineral soil. Adjacent to the soil CO2 profiles, direct (chamber-based) measurements of CO2 fluxes from the soil–litter complex were simultaneously conducted using the automated carbon efflux system. Based on the measured soil CO2 profiles, neither [CO2]e nor N fertilization had a statistically significant effect on seasonal soil CO2, CO2 production, and effluxes from the mineral soil over the study period. Soil moisture and temperature had different effects on CO2 concentration depending on the depth. Variations in CO2 were mostly explained by soil temperature at deeper soil layers, while water content was an important driver at the surface (within the first 10 cm), where CO2 pulses were induced by rainfall events. The soil effluxes were equal to the CO2 production for most of the time, suggesting that the site reached near steady-state conditions. The fluxes estimated from the CO2 profiles were highly correlated to the direct measurements when the soil was neither very dry nor very wet. This suggests that a better parameterization of the soil CO2 diffusivity is required for these soil moisture extremes.
Energy, water, and carbon fluxes in a loblolly pine stand: Results from uniform and gappy canopy models with comparisons to eddy flux data
(2009-12) Song, Conghe; Katul, Gabriel G.; Oren, Ram; Band, Lawrence E.; Tague, Christina L.; Stoy, Paul C.; McCarthy, Heather R.
This study investigates the impacts of canopy structure specification on modeling net radiation (Rn), latent heat flux (LE) and net photosynthesis (An) by coupling two contrasting radiation transfer models with a two‐leaf photosynthesis model for a maturing loblolly pine stand near Durham, North Carolina, USA. The first radiation transfer model is based on a uniform canopy representation (UCR) that assumes leaves are randomly distributed within the canopy, and the second radiation transfer model is based on a gappy canopy representation (GCR) in which leaves are clumped into individual crowns, thereby forming gaps between the crowns. To isolate the effects of canopy structure on model results, we used identical model parameters taken from the literature for both models. Canopy structure has great impact on energy distribution between the canopy and the forest floor. Comparing the model results, UCR produced lower Rn, higher LE and higher An than GCR. UCR intercepted more shortwave radiation inside the canopy, thus producing less radiation absorption on the forest floor and in turn lower Rn. There is a higher degree of nonlinearity between An estimated by UCR and by GCR than for LE. Most of the difference for LE and An between UCR and GCR occurred around noon, when gaps between crowns can be seen from the direction of the incident sunbeam. Comparing with eddy‐covariance measurements in the same loblolly pine stand from May to September 2001, based on several measures GCR provided more accurate estimates for Rn, LE and An than UCR. The improvements when using GCR were much clearer when comparing the daytime trend of LE and An for the growing season. Sensitivity analysis showed that UCR produces higher LE and An estimates than GCR for canopy cover ranging from 0.2 to 0.8. There is a high degree of nonlinearity in the relationship between UCR estimates for An and those of GCR, particularly when canopy cover is low, and suggests that simple scaling of UCR parameters cannot compensate for differences between the two models. LE from UCR and GCR is also nonlinearly related when canopy cover is low, but the nonlinearity quickly disappears as canopy cover increases, such that LE from UCR and GCR are linearly related and the relationship becomes stronger as canopy cover increases. These results suggest the uniform canopy assumption can lead to underestimation of Rn, and overestimation of LE and An. Given the potential in mapping regional scale forest canopy structure with high spatial resolution optical and Lidar remote sensing plotforms, it is possible to use GCR for up‐scaling ecosystem processes from flux tower measurements to heterogeneous landscapes, provided the heterogeneity is not too extreme to modify the flow dynamics.
Environmental and biological controls on seasonal patterns of isoprene above a rain forest in central Amazonia
(2018-06) Wei, Dandan; Fuentes, Jose D.; Gerken, Tobias; Chamecki, Marcelo; Trowbridge, Amy M.; Stoy, Paul C.; Katul, Gabriel G.; Fisch, Gilberto; Acevedo, Otavio; Manzi, Antonio O.; Randow, Celso von; Nascimento dos Santos, Rosa Maria
The Amazon rain forest is a major global isoprene source, but little is known about its seasonal ambient concentration patterns. To investigate the environmental and phenological controls over isoprene seasonality, we measured isoprene mixing ratios, concurrent meteorological data, and leaf area indices from April 2014 to January 2015 above a rain forest in the central Amazon, Brazil. Daytime median isoprene mixing ratios varied throughout the year by a factor of two. The isoprene seasonal pattern was not solely driven by sunlight and temperature. Leaf age and quantity also contributed to the seasonal variations of isoprene concentrations, suggesting leaf phenology was a crucial variable needed to correctly estimate isoprene emissions. A zero-dimensional model incorporating the estimated emissions, atmospheric boundary layer dynamics, and air chemistry was used to assess the contributions of each process on the variability of isoprene. Surface deposition was an important sink mechanism and accounted for 78% of the nighttime loss of isoprene. Also, chemical reactions destroyed isoprene and during 6:00 to 18:00 h local time 56, 77, 69, and 69% of the emitted isoprene was chemically consumed in June, September, December, and January, respectively. Entrainment fluxes from the residual layer contributed 34% to the early-morning above-canopy isoprene mixing ratios. Sensitivity analysis showed that hydroxyl radical (HO) recycling and segregation of isoprene–HO played relatively lesser roles (up to 16%) in regulating ambient isoprene levels. Nitric oxide (NO) levels dominated isoprene chemical reaction pathways associated with consumption and production of HO under low-NO and high volatile organic compound (VOC) conditions. While surface deposition and oxidative processes altered isoprene levels, the relative importance of these factors varied seasonally with leaf phenology playing a more important role.
Estimating the uncertainty in annual net ecosystem carbon exchange: Spatial variation in turbulent fluxes and sampling errors in eddy-covariance measurements
(2006-04) Oren, Ram; Hsieh, Cheng-I.; Stoy, Paul C.; Albertson, John; McCarthy, Heather R.; Harrell, Peter; Katul, Gabriel G.
Above forest canopies, eddy covariance (EC) measurements of mass (CO2, H2O vapor) and energy exchange, assumed to represent ecosystem fluxes, are commonly made at one point in the roughness sublayer (RSL). A spatial variability experiment, in which EC measurements were made from six towers within the RSL in a uniform pine plantation, quantified large and dynamic spatial variation in fluxes. The spatial coefficient of variation (CV) of the scalar fluxes decreased with increasing integration time, stabilizing at a minimum that was independent of further lengthening the averaging period (hereafter a ‘stable minimum’). For all three fluxes, the stable minimum (CV=9–11%) was reached at averaging times (τp) of 6–7 h during daytime, but higher stable minima (CV=46–158%) were reached at longer τp (>12 h) during nighttime. To the extent that decreasing CV of EC fluxes reflects reduction in micrometeorological sampling errors, half of the observed variability at τp=30 min is attributed to sampling errors. The remaining half (indicated by the stable minimum CV) is attributed to underlying variability in ecosystem structural properties, as determined by leaf area index, and perhaps associated ecosystem activity attributes. We further assessed the spatial variability estimates in the context of uncertainty in annual net ecosystem exchange (NEE). First, we adjusted annual NEE values obtained at our long‐term observation tower to account for the difference between this tower and the mean of all towers from this experiment; this increased NEE by up to 55 g C m−2 yr−1. Second, we combined uncertainty from gap filling and instrument error with uncertainty because of spatial variability, producing an estimate of variability in annual NEE ranging from 79 to 127 g C m−2 yr−1. This analysis demonstrated that even in such a uniform pine plantation, in some years spatial variability can contribute ∼50% of the uncertainty in annual NEE estimates.
An evaluation of methods for partitioning eddy covariance-measured net ecosystem exchange into photosynthesis and respiration
(2006-12) Stoy, Paul C.; Katul, Gabriel G.; Siqueira, Mario B. S.; Juang, Jehn-Yih; Novick, Kimberly A.; Uebelherr, Joshua M.; Oren, Ram
We measured net ecosystem CO2 exchange (NEE) using the eddy covariance (EC) technique for 4 years at adjoining old field (OF), planted pine (PP) and hardwood forest (HW) ecosystems in the Duke Forest, NC. To compute annual sums of NEE and its components – gross ecosystem productivity (GEP) and ecosystem respiration (RE) – different ‘flux partitioning’ models (FPMs) were tested and the resulting C flux estimates were compared against published estimates from C budgeting approaches, inverse models, physiology-based forward models, chamber respiration measurements, and constraints on assimilation based on sapflux and evapotranspiration measurements. Our analyses demonstrate that the more complex FPMs, particularly the ‘non-rectangular hyperbolic method’, consistently produced the most reasonable C flux estimates. Of the FPMs that use nighttime data to estimate RE, one that parameterized an exponential model over short time periods generated predictions that were closer to expected flux values. To explore how much ‘new information’ was injected into the data by the FPMs, we used formal information theory methods and computed the Shannon entropy for: (1) the probability density, to assess alterations to the flux measurement distributions, and (2) the wavelet energy spectra, to assess alterations to the internal autocorrelation within the NEE time series. Based on this joint analysis, gap-filling had little impact on the IC of daytime data, but gap-filling significantly altered nighttime data in both the probability and wavelet spectral domains.
Hydrologic and atmospheric controls on convective precipitation events in a southeastern US mosaic landscape
(2007-03) Juang, Jehn-Yih; Porporato, Amilcare; Stoy, Paul C.; Siqueira, Mario B. S.; Oishi, A. Christopher; Detto, Matteo; Kim, Hyun-Seok; Katul, Gabriel G.
The pathway to summertime convective precipitation remains a vexing research problem because of the nonlinear feedback between soil moisture content and the atmosphere. Understanding this feedback is important to the southeastern U. S. region, given the high productivity of the timberland area and the role of summertime convective precipitation in maintaining this productivity. Here we explore triggers of convective precipitation for a wide range of soil moisture states and air relative humidity in a mosaic landscape primarily dominated by hardwood forests, pine plantations, and abandoned old field grassland. Using half‐hourly sensible heat flux, micrometeorological, hydrological time series measurements collected at adjacent HW, PP, and OF ecosystems, and a simplified mixed layer slab model, we developed a conditional sampling scheme to separate convective from nonconvective precipitation events in the observed precipitation time series. The series analyzed (2001–2004) includes some of the wettest and driest periods within the past 57 years. We found that convective precipitation events have significantly larger intensities (mean of 2.1 mm per 30 min) when compared to their nonconvective counterparts (mean of 1.1 mm per 30 min). Interestingly, the statistics of convective precipitation events, including total precipitation, mean intensity, and maximum intensity, are statistically different when convective precipitation is triggered by moist and dry soil conditions but are robust in duration. Using the data, we also showed that a “boundary line” emerges such that for a given soil moisture state, air relative humidity must exceed a defined minimum threshold before convective precipitation is realized.
Investigating a Hierarchy of Eulerian Closure Models for Scalar Transfer Inside Forested Canopies
(2008-04) Juang, Jehn-Yih; Katul, Gabriel G.; Siqueira, Mario B. S.; Stoy, Paul C.; McCarthy, Heather R.
Modelling the transfer of heat, water vapour, and CO2 between the biosphere and the atmosphere is made difficult by the complex two-way interaction between leaves and their immediate microclimate. When simulating scalar sources and sinks inside canopies on seasonal, inter-annual, or forest development time scales, the so-called well-mixed assumption (WMA) of mean concentration (i.e. vertically constant inside the canopy but dynamically evolving in time) is often employed. The WMA eliminates the need to model how vegetation alters its immediate microclimate, which necessitates formulations that utilize turbulent transport theories. Here, two inter-related questions pertinent to the WMA for modelling scalar sources, sinks, and fluxes at seasonal to inter-annual time scales are explored: (1) if the WMA is to be replaced so as to resolve this two-way interaction, how detailed must the turbulent transport model be? And (2) what are the added predictive skills gained by resolving the two-way interaction vis-à-vis other uncertainties such as seasonal variations in physiological parameters. These two questions are addressed by simulating multi-year mean scalar concentration and eddy-covariance scalar flux measurements collected in a Loblolly pine (P. taeda L.) plantation near Durham, North Carolina, U.S.A. using turbulent transport models ranging from K-theory (or first-order closure) to third-order closure schemes. The multi-layer model calculations with these closure schemes were contrasted with model calculations employing the WMA. These comparisons suggested that (i) among the three scalars, sensible heat flux predictions are most biased with respect to eddy-covariance measurements when using the WMA, (ii) first-order closure schemes are sufficient to reproduce the seasonal to inter-annual variations in scalar fluxes provided the canonical length scale of turbulence is properly specified, (iii) second-order closure models best agree with measured mean scalar concentration (and temperature) profiles inside the canopy as well as scalar fluxes above the canopy, (iv) there are no clear gains in predictive skills when using third-order closure schemes over their second-order closure counterparts. At inter-annual time scales, biases in modelled scalar fluxes incurred by using the WMA exceed those incurred when correcting for the seasonal amplitude in the maximum carboxylation capacity (V cmax, 25) provided its mean value is unbiased. The role of local thermal stratification inside the canopy and possible computational simplifications in decoupling scalar transfer from the generation of the flow statistics are also discussed. “The tree, tilting its leaves to capture bullets of light; inhaling, exhaling; its many thousand stomata breathing, creating the air”. Ruth Stone, 2002, In the Next Galaxy"
Modeling nighttime ecosystem respiration from measured CO2 concentration and air temperature profiles using inverse methods
(2006-03) Juang, Jehn-Yih; Katul, Gabriel G.; Siqueira, Mario B. S.; Stoy, Paul C.; Palmroth, Sari; McCarthy, Heather R.; Kim, Hyun-Seok; Oren, Ram
A major challenge for quantifying ecosystem carbon budgets from micrometeorological methods remains nighttime ecosystem respiration. An earlier study utilized a constrained source optimization (CSO) method using inverse Lagrangian dispersion theory to infer the two components of ecosystem respiration (aboveground and forest floor) from measured mean CO2 concentration profiles within the canopy. This method required measurements of within‐canopy mean velocity statistics and did not consider local thermal stratification. We propose a Eulerian version of the CSO method (CSOE) to account for local thermal stratification within the canopy for momentum and scalars using higher‐order closure principles. This method uses simultaneous mean CO2concentration and air temperature profiles within the canopy and velocity statistics above the canopy as inputs. The CSOE was tested at a maturing loblolly pine plantation over a 3‐year period with a mild drought (2001), a severe drought (2002), and a wet year (2003). Annual forest floor efflux modeled with CSOE averaged 111 g C m−2 less than that estimated using chambers during these years (2001: 1224 versus 1328 gCm−2; 2002: 1127 versus 1230 gCm−2; 2003: 1473 versus 1599 gCm−2). The modeled ecosystem respiration exceeded estimates from eddy covariance measurements (uncorrected for storage fluxes) by at least 25%, even at high friction velocities. Finally, we showed that the CSOEannual nighttime respiration values agree well with independent estimates derived from the intercept of the ecosystem light‐response curve from daytime eddy covariance CO2flux measurements.
A multi-site analysis of random error in tower-based measurements of carbon and energy fluxes
(2006-01) Richardson, Andrew D.; Hollinger, David Y.; Burba, George G.; Davis, Kenneth J.; Lawrence B., Flanagan; Katul, Gabriel G.; Munger, J. William; Ricciuto, Daniel M.; Stoy, Paul C.; Suyker, Andrew E.; Verma, Shashi B.; Wofsy, Steven C.
Measured surface-atmosphere fluxes of energy (sensible heat, H, and latent heat, LE) and CO2 (FCO2) represent the “true” flux plus or minus potential random and systematic measurement errors. Here, we use data from seven sites in the AmeriFlux network, including five forested sites (two of which include “tall tower” instrumentation), one grassland site, and one agricultural site, to conduct a cross-site analysis of random flux error. Quantification of this uncertainty is a prerequisite to model-data synthesis (data assimilation) and for defining confidence intervals on annual sums of net ecosystem exchange or making statistically valid comparisons between measurements and model predictions. We differenced paired observations (separated by exactly 24 h, under similar environmental conditions) to infer the characteristics of the random error in measured fluxes. Random flux error more closely follows a double-exponential (Laplace), rather than a normal (Gaussian), distribution, and increase as a linear function of the magnitude of the flux for all three scalar fluxes. Across sites, variation in the random error follows consistent and robust patterns in relation to environmental variables. For example, seasonal differences in the random error for H are small, in contrast to both LE and FCO2, for which the random errors are roughly three-fold larger at the peak of the growing season compared to the dormant season. Random errors also generally scale with Rn (H and LE) and PPFD (FCO2). For FCO2 (but not H or LE), the random error decreases with increasing wind speed. Data from two sites suggest that FCO2 random error may be slightly smaller when a closed-path, rather than open-path, gas analyzer is used.
Multiscale model intercomparisons of CO2 and H2O exchange in a maturing southeastern U.S. pine forest
(2006-07) Siqueira, Mario B. S.; Katul, Gabriel G.; Sampson, D. A.; Stoy, Paul C.; Juang, Jehn-Yih; McCarthy, Heather R.; Oren, Ram
We compared four existing process‐based stand‐level models of varying complexity (physiological principles in predicting growth, photosynthesis and evapotranspiration, biogeochemical cycles, and stand to ecosystem carbon and evapotranspiration simulator) and a new nested model with 4 years of eddy‐covariance‐measured water vapor (LE) and CO2 (Fc) fluxes at a maturing loblolly pine forest. The nested model resolves the ‘fast’ CO2and H2O exchange processes using canopy turbulence theories and radiative transfer principles whereas slowly evolving processes were resolved using standard carbon allocation methods modified to improve leaf phenology. This model captured most of the intraannual variations in leaf area index (LAI), net ecosystem exchange (NEE), and LE for this stand in which maximum LAI was not at a steady state. The model comparisons suggest strong linkages between carbon production and LAI variability, especially at seasonal time scales. This linkage necessitates the use of multilayer models to reproduce the seasonal dynamics of LAI, NEE, and LE. However, our findings suggest that increasing model complexity, often justified for resolving faster processes, does not necessarily translate into improved predictive skills at all time scales. Additionally, none of the models tested here adequately captured drought effects on water and CO2 fluxes. Furthermore, the good performance of some models in capturing flux variability on interannual time scales appears to stem from erroneous LAI dynamics and from sensitivity to droughts that injects unrealistic flux variability at longer time scales.
Nocturnal Evapotranspiration in Eddy-Covariance Records from Three Co-Located Ecosystems in the Southeastern U.S.: Implications for Annual Fluxes
(2009-09) Novick, Kimberly A.; Oren, Ram; Stoy, Paul C.; Siqueira, Mario B. S.; Katul, Gabriel G.
Nocturnal evapotranspiration (ETN) is often assumed to be negligible in terrestrial ecosystems, reflecting the common assumption that plant stomata close at night to prevent water loss from transpiration. However, recent evidence across a wide range of species and climate conditions suggests that significant transpiration occurs at night, frustrating efforts to estimate total annual evapotranspiration (ET) from conventional methods such as the eddy-covariance technique. Here, the magnitude and variability of ETN is explored in multiple years of eddy-covariance measurements from three adjacent ecosystems in the Southeastern U.S.: an old grass field, a planted pine forest, and a late-successional hardwood forest. After removing unreliable data points collected during periods of insufficient turbulence, observed ETN averaged 8–9% of mean daytime evapotranspiration (ETD). ETN was driven primarily by wind speed and vapor pressure deficit and, in the two forested ecosystems, a qualitative analysis suggests a significant contribution from nocturnal transpiration. To gapfill missing data, we investigated several methodologies, including process-based multiple non-linear regression, relationships between daytime and nighttime ET fluxes, marginal distribution sampling, and multiple imputation. The utility of the gapfilling procedures was assessed by comparing simulated fluxes to reliably measured fluxes using randomly generated gaps in the data records, and by examining annual sums of ET from the different gapfilling techniques. The choice of gapfilling methodology had a significant impact on estimates of annual ecosystem water use and, in the most extreme cases, altered the annual estimate of ET by over 100 mm year−1, or ca. 15%. While no single gapfiling methodology appeared superior for treating data from all three sites, marginal distribution sampling generally performed well, producing flux estimates with a site average bias error of <10%, and a mean absolute error close to the random measurement error of the dataset (12.2 and 9.8 W m−2, respectively).
On the spectrum of soil moisture in a shallow-rooted uniform pine forest: from hourly to inter-annual scales
(2007-05) Katul, Gabriel G.; Porporato, Amilcare; Daly, Edoardo; Oishi, A. Christopher; Kim, Hyun-Seok; Stoy, Paul C.; Juang, Jehn-Yih; Siqueira, Mario B. S.
The spectrum of soil moisture content at scales ranging from 1 hour to 8 years is analyzed for a site whose hydrologic balance is primarily governed by precipitation (p), and evapotranspiration (ET). The site is a uniformly planted loblolly pine stand situated in the southeastern United States and is characterized by a shallow rooting depth (RL) and a near‐impervious clay pan just below RL. In this setup, when ET linearly increases with increasing root zone soil moisture content (θ), an analytical model can be derived for the soil moisture content energy spectrum (Es(f), where f is frequency) that predicts the soil moisture “memory” (taken as the integral timescale) as β1−1 ≈ ηRL/ETmax, where ETmax is the maximum measured hourly ET and η is the soil porosity. The spectral model suggests that Es(f) decays at f−2−α at high f but almost white (i.e., f0) at low f, where α is the power law exponent of the rainfall spectrum at high f (α ≈ 0.75 for this site). The rapid Es(f) decay at high f makes the soil moisture variance highly imbalanced in the Fourier domain, thereby permitting much of the soil moisture variability to be described by a limited number of Fourier modes. For the 8‐year data collected here, 99.6% of the soil moisture variance could be described by less than 0.4% of its Fourier modes. A practical outcome of this energy imbalance in the frequency domain is that the diurnal cycle in ET can be ignored if β1−1 (estimated at 7.6 days from the model) is much larger than 12 hours. The model, however, underestimates the measured Es(f) at very low frequencies (f ≪ β1) and its memory, estimated from the data at 42 days. This underestimation is due to seasonality in ETmax and to a partial decoupling between ET and soil moisture at low frequencies.
The relationship between reference canopy conductance and simplified hydraulic architecture
(2009-06) Novick, Kimberly A.; Oren, Ram; Stoy, Paul C.; Juang, Jehn-Yih; Siqueira, Mario B. S.; Katul, Gabriel G.
Terrestrial ecosystems are dominated by vascular plants that form a mosaic of hydraulic conduits to water movement from the soil to the atmosphere. Together with canopy leaf area, canopy stomatal conductance regulates plant water use and thereby photosynthesis and growth. Although stomatal conductance is coordinated with plant hydraulic conductance, governing relationships across species has not yet been formulated at a practical level that can be employed in large-scale models. Here, combinations of published conductance measurements obtained with several methodologies across boreal to tropical climates were used to explore relationships between canopy conductance rates and hydraulic constraints. A parsimonious hydraulic model requiring sapwood-to-leaf area ratio and canopy height generated acceptable agreement with measurements across a range of biomes (r2 = 0.75) . The results suggest that, at long time scales, the functional convergence among ecosystems in the relationship between water-use and hydraulic architecture eclipses inter-specific variation in physiology and anatomy of the transport system. Prognostic applicability of this model requires independent knowledge of sapwood-to-leaf area. In this study, we did not find a strong relationship between sapwood-to-leaf area and physical or climatic variables that are readily determinable at coarse scales, though the results suggest that climate may have a mediating influence on the relationship between sapwood-to-leaf area and height. Within temperate forests, canopy height alone explained a large amount of the variance in reference canopy conductance (r2 = 0.68) and this relationship may be more immediately applicable in the terrestrial ecosystem models.
Role of vegetation in determining carbon sequestration along ecological succession in the southeastern United States
(2008-06) Stoy, Paul C.; Katul, Gabriel G.; Siqueira, Mario B. S.; Juang, Jehn-Yih; Novick, Kimberly A.; McCarthy, Heather R.; Oishi, A. Christopher; Oren, Ram
Vegetation plays a central role in controlling terrestrial carbon (C) exchange, but quantifying its impacts on C cycling on time scales of ecological succession is hindered by a lack of long‐term observations. The net ecosystem exchange of carbon (NEE) was measured for several years in adjacent ecosystems that represent distinct phases of ecological succession in the southeastern USA. The experiment was designed to isolate the role of vegetation – apart from climate and soils – in controlling biosphere–atmosphere fluxes of CO2 and water vapor. NEE was near zero over 5 years at an early successional old‐field ecosystem (OF). However, mean annual NEE was nearly equal, approximately −450 g C m−2 yr−1, at an early successional planted pine forest (PP) and a late successional hardwood forest (HW) due to the sensitivity of the former to drought and ice storm damage. We hypothesize that these observations can be explained by the relationships between gross ecosystem productivity (GEP), ecosystem respiration (RE) and canopy conductance, and long‐term shifts in ecosystem physiology in response to climate to maintain near‐constant ecosystem‐level water‐use efficiency (EWUE). Data support our hypotheses, but future research should examine if GEP and RE are causally related or merely controlled by similar drivers. At successional time scales, GEP and RE observations generally followed predictions from E. P. Odum's ‘Strategy of Ecosystem Development’, with the surprising exception that the relationship between GEP and RE resulted in large NEE at the late successional HW. A practical consequence of this research suggests that plantation forestry may confer no net benefit over the conservation of mature forests for C sequestration.
Separating the effects of albedo from eco-physiological changes on surface temperature along a successional chronosequence in the southeastern US.
(2007-11) Juang, Jehn-Yih; Katul, Gabriel G.; Siqueira, Mario B. S.; Stoy, Paul C.; Novick, Kimberly A.
In the southeastern United States (SE), the conversion of abandoned agricultural land to forests is the dominant feature of land‐cover change. However, few attempts have been made to quantify the impact of such conversion on surface temperature. Here, this issue is explored experimentally and analytically in three adjacent ecosystems (a grass‐covered old‐field, OF, a planted pine forest, PP, and a hardwood forest, HW) representing a successional chronosequence in the SE. The results showed that changes in albedo alone can warm the surface by 0.9°C for the OF‐to‐PP conversion, and 0.7°C for the OF‐to‐HW conversion on annual time scales. However, changes in eco‐physiological and aerodynamic attributes alone can cool the surface by 2.9 and 2.1°C, respectively. Both model and measurements consistently suggest a stronger over‐all surface cooling for the OF‐to‐PP conversion, and the reason is attributed to leaf area variations and its impacts on boundary layer conductance.