Stoy Lab

Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/14931

In the Stoy Lab, we study the role of vegetation in the climate system. To do so we measure and model the exchange of water, heat, and trace gases like carbon dioxide and methane between the terrestrial surface and the atmosphere. Recent efforts seek to understand feedbacks between land management and precipitation processes.

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The structure of turbulence near a tall forest edge: The backward facing step flow analogy
(2000-09) Detto, Matteo; Katul, Gabriel G.; Siqueira, Mario B. S.; Juang, Jehn-Yih; Stoy, Paul C.
Flow disturbances near tall forest edges are receiving significant attention in diverse disciplines including ecology, forest management, meteorology, and fluid mechanics. Current theories suggest that near a forest edge, when the flow originates from a forest into a large clearing, the flow retains its forest canopy turbulence structure at the exit point. Here, we propose that this framework is not sufficiently general for dense forested edges and suggest that the flow shares several attributes with backward‐facing step (BFS) flow. Similar analogies, such as rotor‐like circulations, have been proposed by a number of investigators, though the consequences of such circulations on the primary terms in the mean momentum balance at the forest clearing edge have rarely been studied in the field. Using an array of three triaxial sonic anemometers positioned to measure horizontal and vertical gradients of the velocity statistics near a forest edge, we show that the flow structure is more consistent with an intermittent recirculation pattern, rather than a continuous rotor, whose genesis resembles the BFS flow. We also show that the lateral velocity variance, , is the moment that adjusts most slowly with downwind distance as the flow exits from the forest into the clearing. Surprisingly, the longitudinal and vertical velocity variances ( and ) at the forest edge were comparable in magnitude to their respective values at the center of a large grass‐covered forest clearing, suggesting rapid adjustment at the edge. Discussions on how the forest edge modifies the spectra and co‐spectra of momentum fluxes, effective mixing length, and static pressure are also presented.
Redefinition and global estimation of basal ecosystem respiration rate
(2001-10-13) Yuan, Wenping; Luo, Yiqi; Li, Shuguang; Yu, Guirui; Zhou, Tao; Bahn, Michael; Black, Andy T.; Desai, Ankur R.; Cescatti, Alessandro; Marcolla, Barbara; Jacobs, Cor; Chen, Jiquan; Aurela, Mika; Bernhofer, Christian; Gielen, Bert; Bohrer, Gil; Cook, David R.; Dragoni, Danilo; Dunn, Allison L.; Gianelle, Damiano; Grünwald, Thomas; Ibrom, Andreas; Leclerc, Monique Y.; Lindroth, Anders; Liu, Heping; Marchesini, Luca Belelli; Montagnani, Leonardo; Pita, Gabriel; Rodeghiero, Mirco; Rodrigues, Abel; Starr, Gregory; Stoy, Paul C.
Basal ecosystem respiration rate (BR), the ecosystem respiration rate at a given temperature, is a common and important parameter in empirical models for quantifying ecosystem respiration (ER) globally. Numerous studies have indicated that BR varies in space. However, many empirical ER models still use a global constant BR largely due to the lack of a functional description for BR. In this study, we redefined BR to be ecosystem respiration rate at the mean annual temperature. To test the validity of this concept, we conducted a synthesis analysis using 276 site-years of eddy covariance data, from 79 research sites located at latitudes ranging from ∼3°S to ∼70°N. Results showed that mean annual ER rate closely matches ER rate at mean annual temperature. Incorporation of site-specific BR into global ER model substantially improved simulated ER compared to an invariant BR at all sites. These results confirm that ER at the mean annual temperature can be considered as BR in empirical models. A strong correlation was found between the mean annual ER and mean annual gross primary production (GPP). Consequently, GPP, which is typically more accurately modeled, can be used to estimate BR. A light use efficiency GPP model (i.e., EC-LUE) was applied to estimate global GPP, BR and ER with input data from MERRA (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate resolution Imaging Spectroradiometer). The global ER was 103 Pg C yr −1, with the highest respiration rate over tropical forests and the lowest value in dry and high-latitude areas.
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.
Variability in net ecosystem exchange from hourly to inter-annual time scales at adjacent pine and hardwood forests: a wavelet analysis
(2005-07) Stoy, Paul C.; Katul, Gabriel G.; Siqueira, Mario B. S.; Juang, Jehn-Yih; McCarthy, Heather R.; Kim, Hyun-Seok; Oishi, A. Christopher; Oren, Ram
Orthonormal wavelet transformation (OWT) is a computationally efficient technique for quantifying underlying frequencies in nonstationary and gap-infested time series, such as eddy-covariance-measured net ecosystem exchange of CO2 (NEE). We employed OWT to analyze the frequency characteristics of synchronously measured and modeled NEE at adjacent pine (PP) and hardwood (HW) ecosystems. Wavelet cospectral analysis showed that NEE at PP was more correlated to light and vapor pressure deficit at the daily time scale, and NEE at HW was more correlated to leaf area index (LAI) and temperature, especially soil temperature, at seasonal time scales. Models were required to disentangle the impacts of environmental drivers on the components of NEE, ecosystem carbon assimilation (Ac) and ecosystem respiration (RE). Sensitivity analyses revealed that using air temperature rather than soil temperature in RE models improved the modeled wavelet spectral frequency response on time scales longer than 1 day at both ecosystems. Including LAI improved RE model fit on seasonal time scales at HW, and incorporating parameter variability improved the RE model response at annual time scales at both ecosystems. Resolving variability in canopy conductance, rather than leaf-internal CO2, was more important for modeling Ac at both ecosystems. The PP ecosystem was more sensitive to hydrologic variables that regulate canopy conductance: vapor pressure deficit on weekly time scales and soil moisture on seasonal to interannual time scales. The HW ecosystem was sensitive to water limitation on weekly time scales. A combination of intrinsic drought sensitivity and non-conservative water use at PP was the basis for this response. At both ecosystems, incorporating variability in LAI was required for an accurate spectral representation of modeled NEE. However, nonlinearities imposed by canopy light attenuation were of little importance to spectral fit. The OWT revealed similarities and differences in the scale-wise control of NEE by vegetation with implications for model simplification and improvement.
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.
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.
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.
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.
Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations
(2006-07) Heinsch, Faith A.; Zhao, Maosheng; Running, Steven W.; Kimball, John S.; Nemani, Ramakrishna R.; Davis, Kenneth J.; Cook, Bruce D.; Desai, Ankur R.; Ricciuto, Daniel M.; Law, Beverly E.; Oechel, Walter C.; Kwon, Hyojung; Wofsy, Steven C.; Dunn, Allison L.; Munger, J. William; Baldocchi, Dennis D.; Xu, Liukang; Hollinger, David Y.; Richardson, Andrew D.; Stoy, Paul C.; Siqueira, Mario B. S.; Monson, Russell K.; Burns, Sean P.; Flanagan, Lawrence B.; Bolstad, Paul V.; Luo, Hongyan
The Moderate Resolution Spectroradiometer (MODIS) sensor has provided near real-time estimates of gross primary production (GPP) since March 2000. We compare four years (2000 to 2003) of satellite-based calculations of GPP with tower eddy CO2 flux-based estimates across diverse land cover types and climate regimes. We examine the potential error contributions from meteorology, leaf area index (LAI)/fPAR, and land cover. The error between annual GPP computed from NASA's Data Assimilation Office's (DAO) and tower-based meteorology is 28%, indicating that NASA's DAO global meteorology plays an important role in the accuracy of the GPP algorithm. Approximately 62% of MOD15-based estimates of LAI were within the estimates based on field optical measurements, although remaining values overestimated site values. Land cover presented the fewest errors, with most errors within the forest classes, reducing potential error. Tower-based and MODIS estimates of annual GPP compare favorably for most biomes, although MODIS GPP overestimates tower-based calculations by 20%-30%. Seasonally, summer estimates of MODIS GPP are closest to tower data, and spring estimates are the worst, most likely the result of the relatively rapid onset of leaf-out. The results of this study indicate, however, that the current MODIS GPP algorithm shows reasonable spatial patterns and temporal variability across a diverse range of biomes and climate regimes. So, while continued efforts are needed to isolate particular problems in specific biomes, we are optimistic about the general quality of these data, and continuation of the MOD17 GPP product will likely provide a key component of global terrestrial ecosystem analysis, providing continuous weekly measurements of global vegetation production
Separating the effects of climate and vegetation on evapotranspiration along a successional chronosequence in the southeastern U.S.
(2006-11) Stoy, Paul C.; Katul, Gabriel G.; Siqueira, Mario B. S.; Juang, Jehn-Yih; Novick, Kimberly A.; McCarthy, Heather R.; Oishi, A. Christopher; Uebelherr, Joshua M.; Kim, Hyun-Seok; Kim, Ram
We combined Eddy‐covariance measurements with a linear perturbation analysis to isolate the relative contribution of physical and biological drivers on evapotranspiration (ET) in three ecosystems representing two end‐members and an intermediate stage of a successional gradient in the southeastern US (SE). The study ecosystems, an abandoned agricultural field [old field (OF)], an early successional planted pine forest (PP), and a late‐successional hardwood forest (HW), exhibited differential sensitivity to the wide range of climatic and hydrologic conditions encountered over the 4‐year measurement period, which included mild and severe droughts and an ice storm. ET and modeled transpiration differed by as much as 190 and 270 mm yr−1, respectively, between years for a given ecosystem. Soil water supply, rather than atmospheric demand, was the principal external driver of interannual ET differences. ET at OF was sensitive to climatic variability, and results showed that decreased leaf area index (L) under mild and severe drought conditions reduced growing season (GS) ET (ETGS) by ca. 80 mm compared with a year with normal precipitation. Under wet conditions, higher intrinsic stomatal conductance (gs) increased ETGS by 50 mm. ET at PP was generally larger than the other ecosystems and was highly sensitive to climate; a 50 mm decrease in ETGS due to the loss of L from an ice storm equaled the increase in ET from high precipitation during a wet year. In contrast, ET at HW was relatively insensitive to climatic variability. Results suggest that recent management trends toward increasing the land‐cover area of PP‐type ecosystems in the SE may increase the sensitivity of ET to climatic variability.
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.
Linking flux network measurements to continental scale simulations: Ecosystem gas exchange capacity along a European transect under non-water-stressed conditions
(2007-01) Owen, Katherine E.; Tenhunen, John; Reichstein, Markus; Wang, Quan; Falge, Eva; Geyer, Ralf; Xiao, Xiangming; Stoy, Paul C.; Ammann, Christof; Arain, M. Altaf; Aubinet, Marc; Aurela, Mika; Bernhofer, Christian; Chojnicki, Bogdan H.; Granier, Andre; Gruenwald, Thomas; Hadley, Julian; Heinesch, Bernard; Hollinger, David Y.; Knohl, Alexander; Kutsch, Werner L.; Lohila, Annalea; Meyers, Tilden P.; Moors, Eddy J.; Moureaux, Christine; Pilegaard, Kim; Saigusa, Nobuko; Verma, Shashi B.; Vesala, Timo; Vogel, Chris
This paper examines long‐term eddy covariance data from 18 European and 17 North American and Asian forest, wetland, tundra, grassland, and cropland sites under non‐water‐stressed conditions with an empirical rectangular hyperbolic light response model and a single layer two light‐class carboxylase‐based model. Relationships according to ecosystem functional type are demonstrated between empirical and physiological parameters, suggesting linkages between easily estimated parameters and those with greater potential for process interpretation. Relatively sparse documentation of leaf area index dynamics at flux tower sites is found to be a major difficulty in model inversion and flux interpretation. Therefore, a simplification of the physiological model is carried out for a subset of European network sites with extensive ancillary data. The results from these selected sites are used to derive a new parameter and means for comparing empirical and physiologically based methods across all sites, regardless of ancillary data. The results from the European analysis are then compared with results from the other Northern Hemisphere sites and similar relationships for the simplified process‐based parameter were found to hold for European, North American, and Asian temperate and boreal climate zones. This parameter is useful for bridging between flux network observations and continental scale spatial simulations of vegetation/atmosphere carbon dioxide exchange.
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.
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.
Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes
(2007-04) Yuan, Wenping; Liu, Shuguang; Zhou, Guangsheng; Zhou, Guoyi; Tieszen, Larry L.; Baldocchi, Dennis D.; Bernhofer, Christian; Gholz, Henry; Goldstein, Allen H.; Goulden, Michael L.; Hollinger, David Y.; Hu, Yueming; Law, Beverly E.; Stoy, Paul C.; Vesala, Timo; Wofsy, Steven C.
The quantitative simulation of gross primary production (GPP) at various spatial and temporal scales has been a major challenge in quantifying the global carbon cycle. We developed a light use efficiency (LUE) daily GPP model from eddy covariance (EC) measurements. The model, called EC-LUE, is driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux (used to calculate moisture stress). The EC-LUE model relies on two assumptions: First, that the fraction of absorbed PAR (fPAR) is a linear function of NDVI; Second, that the realized light use efficiency, calculated from a biome-independent invariant potential LUE, is controlled by air temperature or soil moisture, whichever is most limiting. The EC-LUE model was calibrated and validated using 24,349 daily GPP estimates derived from 28 eddy covariance flux towers from the AmeriFlux and EuroFlux networks, covering a variety of forests, grasslands and savannas. The model explained 85% and 77% of the observed variations of daily GPP for all the calibration and validation sites, respectively. A comparison with GPP calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS) indicated that the EC-LUE model predicted GPP that better matched tower data across these sites. The realized LUE was predominantly controlled by moisture conditions throughout the growing season, and controlled by temperature only at the beginning and end of the growing season. The EC-LUE model is an alternative approach that makes it possible to map daily GPP over large areas because (1) the potential LUE is invariant across various land cover types and (2) all driving forces of the model can be derived from remote sensing data or existing climate observation networks.
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.
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.
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.
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"
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.