Stoy Lab

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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.


Recent Submissions

Now showing 1 - 20 of 84
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    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.
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    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.
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    Interannual variability of ecosystem carbon exchange: From observation to prediction
    (2017-09) Niu, Shuli; Zheng, Fu; Yiqi, Luo; Stoy, Paul C.; Keenan, Trevor F.; Poulter, Benjamin; Zhang, Leiming; Piao, Shilong; Zhou, Xuhui; Zheng, Han; Han, Jiayin; Wang, Qiufeng; Yu, Guirui
    Aim Terrestrial ecosystems have sequestered, on average, the equivalent of 30% of anthropogenic carbon (C) emissions during the past decades, but annual sequestration varies from year to year. For effective C management, it is imperative to develop a predictive understanding of the interannual variability (IAV) of terrestrial net ecosystem C exchange (NEE). Location Global terrestrial ecosystems. Methods We conducted a comprehensive review to examine the IAV of NEE at global, regional and ecosystem scales. Then we outlined a conceptual framework for understanding how anomalies in climate factors impact ecological processes of C cycling and thus influence the IAV of NEE through biogeochemical regulation. Results The phenomenon of IAV in land NEE has been ubiquitously observed at global, regional and ecosystem scales. Global IAV is often attributable to either tropical or semi‐arid regions, or to some combination thereof, which is still under debate. Previous studies focus on identifying climate factors as driving forces of IAV, whereas biological mechanisms underlying the IAV of ecosystem NEE are less clear. We found that climate anomalies affect the IAV of NEE primarily through their differential impacts on ecosystem C uptake and respiration. Moreover, recent studies suggest that the carbon uptake period makes less contribution than the carbon uptake amplitude to IAV in NEE. Although land models incorporate most processes underlying IAV, their efficacy to predict the IAV in NEE remains low. Main conclusions To improve our ability to predict future IAV of the terrestrial C cycle, we have to understand biological mechanisms through which anomalies in climate factors cause the IAV of NEE. Future research needs to pay more attention not only to the differential effects of climate anomalies on photosynthesis and respiration but also to the relative importance of the C uptake period and amplitude in causing the IAV of NEE. Ultimately, we need multiple independent approaches, such as benchmark analysis, data assimilation and time‐series statistics, to integrate data, modelling frameworks and theory to improve our ability to predict future IAV in the terrestrial C cycle.
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    Land management and land-cover change have impacts of similar magnitude on surface temperature
    (2014-04) Luyssaert, Sebastiaan; Jammet, Mathilde; Stoy, Paul C.; Estel, Stephan; Pongratz, Julia; Ceschia, Eric; Churkina, Galina; Don, A.; Erb, K.; Ferlicoq, M.; Gielen, Bert; Grünwald, Thomas; Houghton, Richard A.; Klumpp, K.; Knohl, A.; Kolb, T.; Kuemmerle, T.; Laurila, T.; Lohila, A.; Loustau, Denis; Meyfroidt, P.; Moors, Eddy J.; Novick, Kimberly A.; Otto, Juliane; Pilegaard, Kim; Pio, C. A.; Rambal, Serge; Rebmann, C.; Ryder, J.; Suyker, Andrew E.; Varlagin, Andrej B.; Wattenbach, M.; Dolman, A. J.
    Anthropogenic changes to land cover (LCC) remain common, but continuing land scarcity promotes the widespread intensification of land management changes (LMC) to better satisfy societal demand for food, fibre, fuel and shelter1. The biophysical effects of LCC on surface climate are largely understood2,3,4,5, particularly for the boreal6 and tropical zones7, but fewer studies have investigated the biophysical consequences of LMC; that is, anthropogenic modification without a change in land cover type. Harmonized analysis of ground measurements and remote sensing observations of both LCC and LMC revealed that, in the temperate zone, potential surface cooling from increased albedo is typically offset by warming from decreased sensible heat fluxes, with the net effect being a warming of the surface. Temperature changes from LMC and LCC were of the same magnitude, and averaged 2 K at the vegetation surface and were estimated at 1.7 K in the planetary boundary layer. Given the spatial extent of land management (42–58% of the land surface) this calls for increasing the efforts to integrate land management in Earth System Science to better take into account the human impact on the climate8.
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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.
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    Separation of Net Ecosystem Exchange into Assimilation and Respiration Using a Light Response Curve Approach: Critical Issues and Global Evaluation
    (2010-01) Lasslop, Gitta; Reichstein, Markus; Papale, Dario; Richardson, Andrew D.; Arneth, Almut; Barr, Alan G.; Stoy, Paul C.; Wohlfahrt, Georg
    The measured net ecosystem exchange (NEE) of CO2 between the ecosystem and the atmosphere reflects the balance between gross CO2 assimilation [gross primary production (GPP)] and ecosystem respiration (Reco). For understanding the mechanistic responses of ecosystem processes to environmental change it is important to separate these two flux components. Two approaches are conventionally used: (1) respiration measurements made at night are extrapolated to the daytime or (2) light–response curves are fit to daytime NEE measurements and respiration is estimated from the intercept of the ordinate, which avoids the use of potentially problematic nighttime data. We demonstrate that this approach is subject to biases if the effect of vapor pressure deficit (VPD) modifying the light response is not included. We introduce an algorithm for NEE partitioning that uses a hyperbolic light response curve fit to daytime NEE, modified to account for the temperature sensitivity of respiration and the VPD limitation of photosynthesis. Including the VPD dependency strongly improved the model's ability to reproduce the asymmetric diurnal cycle during periods with high VPD, and enhances the reliability of Reco estimates given that the reduction of GPP by VPD may be otherwise incorrectly attributed to higher Reco. Results from this improved algorithm are compared against estimates based on the conventional nighttime approach. The comparison demonstrates that the uncertainty arising from systematic errors dominates the overall uncertainty of annual sums (median absolute deviation of GPP: 47 g C m−2 yr−1), while errors arising from the random error (median absolute deviation: ∼2 g C m−2 yr−1) are negligible. Despite site‐specific differences between the methods, overall patterns remain robust, adding confidence to statistical studies based on the FLUXNET database. In particular, we show that the strong correlation between GPP and Reco is not spurious but holds true when quasi‐independent, i.e. daytime and nighttime based estimates are compared.
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    Productivity, Respiration, and Light-Response Parameters of World Grassland and Agroecosystems Derived From Flux-Tower Measurements
    (2010-01) Gilmanov, Tagir G.; Aires, Luis M. I.; Barcza, Zoltan; Baron, Vern S.; Belelli, Luca; Beringer, Jason; Billesbach, David; Bonal, Damien; Bradford, James A.; Ceschia, Eric; Cook, D.; Corradi, Chiara A. R.; Frank, Albert B.; Gianelle, Damiano; Gimeno, Cristina; Gruenwald, Thomas; Guo, Haiqiang; Hanan, Niall; Haszpra, Laszlo; Heilman, J.; Jacobs, Adrie F. G.; Jones, Mike B.; Johnson, Douglas A.; Kiely, Gerard K.; Li, Shenggong; Magliulo, Vincenzo; Moors, Eddy; Nagy, Zoltan; Nasyrov, M.; Owensby, Clenton E.; Pintér, Krisztina; Pio, Casimiro; Reichstein, Markus; Sanz-Sanchez, Maria José; Scott, Russell L.; Soussana, Jean-Francois; Stoy, Paul C.; Svejcar, T.; Tuba, Zoltán; Zhou, Guangsheng
    Grasslands and agroecosystems occupy one-third of the terrestrial area, but their contribution to the global carbon cycle remains uncertain. We used a set of 316 site-years of CO2 exchange measurements to quantify gross primary productivity, respiration, and light-response parameters of grasslands, shrublands/savanna, wetlands, and cropland ecosystems worldwide. We analyzed data from 72 global flux-tower sites partitioned into gross photosynthesis and ecosystem respiration with the use of the light-response method (Gilmanov, T. G., D. A. Johnson, and N. Z. Saliendra. 2003. Growing season CO2 fluxes in a sagebrush-steppe ecosystem in Idaho: Bowen ratio/energy balance measurements and modeling. Basic and Applied Ecology 4:167–183) from the RANGEFLUX and WORLDGRASSAGRIFLUX data sets supplemented by 46 sites from the FLUXNET La Thuile data set partitioned with the use of the temperature-response method (Reichstein, M., E. Falge, D. Baldocchi, D. Papale, R. Valentini, M. Aubinet, P. Berbigier, C. Bernhofer, N. Buchmann, M. Falk, T. Gilmanov, A. Granier, T. Grünwald, K. Havránková, D. Janous, A. Knohl, T. Laurela, A. Lohila, D. Loustau, G. Matteucci, T. Meyers, F. Miglietta, J. M. Ourcival, D. Perrin, J. Pumpanen, S. Rambal, E. Rotenberg, M. Sanz, J. Tenhunen, G. Seufert, F. Vaccari, T. Vesala, and D. Yakir. 2005. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. Global Change Biology 11:1424–1439). Maximum values of the quantum yield (α=75 mmol · mol−1), photosynthetic capacity (Amax=3.4 mg CO2 · m−2 · s−1), gross photosynthesis (Pg,max=116 g CO2 · m−2 · d−1), and ecological light-use efficiency (εecol=59 mmol · mol−1) of managed grasslands and high-production croplands exceeded those of most forest ecosystems, indicating the potential of nonforest ecosystems for uptake of atmospheric CO2. Maximum values of gross primary production (8 600 g CO2 · m−2 · yr−1), total ecosystem respiration (7 900 g CO2 · m−2 · yr−1), and net CO2 exchange (2 400 g CO2 · m−2 · yr−1) were observed for intensively managed grasslands and high-yield crops, and are comparable to or higher than those for forest ecosystems, excluding some tropical forests. On average, 80% of the nonforest sites were apparent sinks for atmospheric CO2, with mean net uptake of 700 g CO2 · m−2 · yr−1 for intensive grasslands and 933 g CO2 · m−2 · d−1 for croplands. However, part of these apparent sinks is accumulated in crops and forage, which are carbon pools that are harvested, transported, and decomposed off site. Therefore, although agricultural fields may be predominantly sinks for atmospheric CO2, this does not imply that they are necessarily increasing their carbon stock.
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    Upscaling as ecological information transfer: A simple framework with application to arctic ecosystem carbon exchange
    (2009-06) Stoy, Paul C.; Williams, Mathew; Prieto-Blanco, Ana; Huntley, Brian; Baxter, Robert; Lewis, Philip
    Transferring ecological information across scale often involves spatial aggregation, which alters information content and may bias estimates if the scaling process is nonlinear. Here, a potential solution, the preservation of the information content of fine-scale measurements, is highlighted using modeled net ecosystem exchange (NEE) of an Arctic tundra landscape as an example. The variance of aggregated normalized difference vegetation index (NDVI), measured from an airborne platform, decreased linearly with log(scale), resulting in a linear relationship between log(scale) and the scale-wise modeled NEE estimate. Preserving three units of information, the mean, variance and skewness of fine-scale NDVI observations, resulted in upscaled NEE estimates that deviated less than 4% from the fine-scale estimate. Preserving only the mean and variance resulted in nearly 23% NEE bias, and preserving only the mean resulted in larger error and a change in sign from CO2 sink to source. Compressing NDVI maps by 70–75% using wavelet thresholding with the Haar and Coiflet basis functions resulted in 13% NEE bias across the study domain. Applying unique scale-dependent transfer functions between NDVI and leaf area index (LAI) decreased, but did not remove, bias in modeled flux in a smaller expanse using handheld NDVI observations. Quantifying the parameters of statistical distributions to preserve ecological information reduces bias when upscaling and makes possible spatial data assimilation to further reduce errors in estimates of ecological processes across scale.
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    Artificial drainage and associated carbon fluxes (CO2/CH4) in tundra ecosystems
    (2009-11) Merbold, L.; Kutsch, Werner L.; Kolle, O.; Zimov, S. A.; Corradi, C.; Stoy, Paul C.; Schulze, E.-D.
    Ecosystem flux measurements using the eddy covariance (EC) technique were undertaken in 4 subsequent years during summer for a total of 562 days in an arctic wet tundra ecosystem, located near Cherskii, Far‐Eastern Federal District, Russia. Methane (CH4) emissions were measured using permanent chambers. The experimental field is characterized by late thawing of permafrost soils in June and periodic spring floods. A stagnant water table below the grass canopy is fed by melting of the active layer of permafrost and by flood water. Following 3 years of EC measurements, the site was drained by building a 3 m wide drainage channel surrounding the EC tower to examine possible future effects of global change on the tundra tussock ecosystem. Cumulative summertime net carbon fluxes before experimental alteration were estimated to be about +15 g C m−2 (i.e. an ecosystem C loss) and +8 g C m−2 after draining the study site. When taking CH4 as another important greenhouse gas into account and considering the global warming potential (GWP) of CH4 vs. CO2, the ecosystem had a positive GWP during all summers. However CH4 emissions after drainage decreased significantly and therefore the carbon related greenhouse gas flux was much smaller than beforehand (475 ± 253 g C‐CO2‐e m−2 before drainage in 2003 vs. 23 ± 26 g C‐CO2‐e m−2 after drainage in 2005).
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    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).
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    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.
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    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.
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    Using information theory to determine optimum pixel size and shape for ecological studies: Aggregating land surface characteristics in arctic ecosystems
    (2009-03) Stoy, Paul C.; Williams, Mathew; Bell, Robert A.; Spadavecchia, Luke; Prieto-Blanco, Ana; Evans, J. G.; van Wijk, Mark T.
    Quantifying vegetation structure and function is critical for modeling ecological processes, and an emerging challenge is to apply models at multiple spatial scales. Land surface heterogeneity is commonly characterized using rectangular pixels, whose length scale reflects that of remote sensing measurements or ecological models rather than the spatial scales at which vegetation structure and function varies. We investigated the ‘optimum’ pixel size and shape for averaging leaf area index (LAI) measurements in relatively large (85 m2 estimates on a 600 × 600-m2 grid) and small (0.04 m2 measurements on a 40 × 40-m2 grid) patches of sub-Arctic tundra near Abisko, Sweden. We define the optimum spatial averaging operator as that which preserves the information content (IC) of measured LAI, as quantified by the normalized Shannon entropy (E S,n) and Kullback–Leibler divergence (D KL), with the minimum number of pixels. Based on our criterion, networks of Voronoi polygons created from triangulated irregular networks conditioned on hydrologic and topographic indices are often superior to rectangular shapes for averaging LAI at some, frequently larger, spatial scales. In order to demonstrate the importance of information preservation when upscaling, we apply a simple, validated ecosystem carbon flux model at the landscape level before and after spatial averaging of land surface characteristics. Aggregation errors are minimal due to the approximately linear relationship between flux and LAI, but large errors of approximately 45% accrue if the normalized difference vegetation index (NDVI) is averaged without preserving IC before conversion to LAI due to the nonlinear NDVI-LAI transfer function.
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    Assessing Self-Organization of Plant communities—A Thermodynamic Approach
    (2009-03) Lin, Hua; Cao, Min; Stoy, Paul C.; Zhang, Yiping
    Thermodynamics is a powerful tool for the study of system development and has the potential to be applied to studies of ecological complexity. Here, we develop a set of thermodynamic indicators including energy capture and energy dissipation to quantify plant community self-organization. The study ecosystems included a tropical seasonal rainforest, an artificial tropical rainforest, a rubber plantation, and two Chromolaena odorata (L.) R.M. King & H. Robinson communities aged 13 years and 1 year. The communities represent a complexity transect from primary vegetation, to transitional community, economic plantation, and fallows and are typical for Xishuangbanna, southwestern China. The indicators of ecosystem self-organization are sensitive to plant community type and seasonality, and demonstrate that the tropical seasonal rainforest is highly self-organized and plays an important role in local environmental stability via the land surface thermal regulation. The rubber plantation is at a very low level of self-organization as quantified by the thermodynamic indicators, especially during the dry season. The expansion of the area of rubber plantation and shrinkage of tropical seasonal rainforest would likely induce local surface warming and a larger daily temperature range.
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    Fine-Root Respiration in a Loblolly Pine (Pinus taeda L.) Forest Exposed to Elevated CO2 and N Fertilization
    (2008-10) Drake, John E.; Stoy, Paul C.; Jackson, Robert B.; DeLucia, Evan H.
    Forest ecosystems release large amounts of carbon to the atmosphere from fine‐root respiration (Rr), but the control of this flux and its temperature sensitivity (Q10) are poorly understood. We attempted to: (1) identify the factors limiting this flux using additions of glucose and an electron transport uncoupler (carbonyl cyanide m‐chlorophenylhydrazone); and (2) improve yearly estimates of Rr by directly measuring its Q10in situ using temperature‐controlled cuvettes buried around intact, attached roots. The proximal limits of Rr of loblolly pine (Pinus taeda L.) trees exposed to free‐air CO2 enrichment (FACE) and N fertilization were seasonally variable; enzyme capacity limited Rr in the winter, and a combination of substrate supply and adenylate availability limited Rr in summer months. The limiting factors of Rr were not affected by elevated CO2 or N fertilization. Elevated CO2 increased annual stand‐level Rr by 34% whereas the combination of elevated CO2 and N fertilization reduced Rr by 40%. Measurements of in situ Rr with high temporal resolution detected diel patterns that were correlated with canopy photosynthesis with a lag of 1 d or less as measured by eddy covariance, indicating a dynamic link between canopy photosynthesis and root respiration. These results suggest that Rr is coupled to daily canopy photosynthesis and increases with carbon allocation below ground.
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    Topographic controls on the leaf area index and plant functional type of a Fennoscandian tundra ecosystem
    (2008-11) Spadavecchia, Luke; Williams, Mathew; Bell, Robert; Stoy, Paul C.; Huntley, Brian; van Wijk, Mark T.
    Leaf area index (LAI) is an emergent property of vascular plants closely linked to primary production and surface energy balance. LAI can vary by an order of magnitude among Arctic tundra communities and is closely associated with plant functional type. 2. We examined topographic controls on vegetation type and LAI distribution at two different scales in an Arctic tundra ecosystem in northern Sweden. ‘Micro-scale’ measurements were made at 0.2-m resolution over a 40 m × 40 m domain, while ‘macro-scale’ data were collected at approximately 10-m resolution over a 500 m × 500 m domain. Tundra LAI varied from 0.1–3.6 at the micro-scale resolution, and from 0.1–1.6 at the macro-scale resolution. 3. The correlation between dominant vascular species and LAI at the micro-scale ( r 2 = 0.40) was greater than the correlation between dominant vegetation and LAI at the macro-scale ( r 2 = 0.14).At the macro-scale, LAI was better explained by topographic parameters and spatial auto-correlation (pseudo r 2 = 0.32) than it was at the micro-scale ( r 2 = 0.16). Exposure and elevation were significantly but weakly correlated with LAI at the micro-scale, while on the macro-scale the most significant explanatory topographic variable was elevation ( r 2 = 0.12). 4. The distribution of plant communities at both scales was significantly associated with topography. Shrub communities, dominated by Betula nana , were associated with low elevation sites at both scales, while more exposed and/or high elevation sites were dominated by cryptogams. 5. Synthesis. Dominant vegetation, topography and LAI were linked at both scales of investigation but, for explaining LAI, topography became more important and dominant vegetation less important at the coarser scale. The explanatory power of dominant species/functional type for LAI variation was weaker at coarser scales, because communities often contained more than one functional type at 10 m resolution. The data suggest that remotely sensed topography can be combined with remotely sensed optical measurements to generate a useful tool for LAI mapping in Arctic environments.
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    Estimating Components of Forest Evapotranspiration: A Footprint Approach for Scaling Sap Flux Measurements
    (2008-10) Oishi, A. Christopher; Oren, Ram; Stoy, Paul C.
    Forest evapotranspiration (ET) estimates that include scaled sap flux measurements often underestimate eddy covariance (EC)-measured latent heat flux (LE). We investigated potential causes for this bias using 4 years of coupled sap flux and LE measurements from a mature oak-hickory forest in North Carolina, USA. We focused on accuracy in sap flux estimates from heat dissipation probes by investigating nocturnal water uptake, radial pattern in flux rates, and sensor-to-stand scaling. We also produced empirical functions describing canopy interception losses (measured as the difference between precipitation and throughfall) and soil evaporation (based on wintertime eddy covariance fluxes minus wintertime water losses through bark), and added these components to the scaled sap flux to estimate stand evapotranspiration (ETS). We show that scaling based on areas in which the leaf area index of predominant species deviates from that of the EC footprint can lead to either higher or lower estimate of ETS than LE (i.e. there is no bias). We found that accounting for nocturnal water uptake increased the estimate of growing season transpiration by an average of 22%, with inter-annual standard deviation of 4%. Annual ETSestimate that included sap flux corrected for nocturnal flux and scaled to the EC footprint were similar to LE estimates (633 ± 26 versus 604 ± 19 mm, respectively). At monthly or shorter time scales, ETS was higher than LE at periods of low flux, similar at periods of moderate flux, and lower at periods of high flux, indicating potential shortcomings of both methods. Nevertheless, this study demonstrates that accounting for the effects of nocturnal flux on the baseline signal was essential for eliminating much of the bias between EC-based and component-based estimates of ET, but the agreement between these estimates is greatly affected by the scaling procedure.
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    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"
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    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.
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    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.
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