Browsing by Author "McCarthy, Heather R."

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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.
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.
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.
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.
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 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.
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.