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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Air temperature and photosynthetically active photon flux density data from the Abisko Scientific Research center [dataset]
(2014-12) Stoy, Paul C.
Air temperature and photosynthetically active photon flux density data from the Abisko Scientific Research center courtesy of Annika Kristofferson. The Stoy Lab adheres to an open data policy. Data collected by the Stoy Lab are free to anyone to use with two caveats: 1. Coauthorship may be requested if intellectual input is provided. Intellectual input is defined in this case as an analysis that is critical to outcomes that could not otherwise be performed. 2. Graduate students operate the towers and analyze the data. They must be given the opportunity to be coauthors on your work. Please email paul dot stoy at gmail dot com with any questions. Further information is available from the Biosphere-Atmosphere Interactions Lab website https://sites.google.com/site/stoylab/home
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.
Applying information theory in the geosciences to quantify process uncertainty, feedback, scale
(2013-01-29) Ruddell, Benjamin L.; Brunsell, Nathaniel A.; Stoy, Paul C.
The geosciences are increasingly utilizing a systems approach to quantify spatial and temporal dynamics among multiple subsystems, their couplings, and their feedbacks. This systems approach demands novel strategies for experimentation and observation in the “natural laboratory” rather than in simple controlled experiments and thus relies heavily on Earth system observations and observation networks. Current and forthcoming examples of Earth system observatories include the Critical Zone Observatories (CZOs), the National Ecological Observatory Network (NEON), EarthScope, FLUXNET, National Water Information System/National Water‐Quality Assessment (NWIS/NAWQA), and others. These networks are designed to observe complex processes across a wide range of temporal and spatial scales to synthesize scientific understanding of the fundamental interactions across the interfaces of society, hydrology, ecology, atmospheric sciences, and geosciences.
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.
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).
Assessing interactions among changing climate, management, and disturbance in forests: a macrosystems approach
(2015-03) Becknell, Justin M.; Desai, Ankur R.; Dietze, Michael C.; Schultz, Courtney A.; Starr, Gregory; Stoy, Paul C.; Duffy, Paul A.; Franklin, Jerry F.; Pourmokhtarian, Afshin; Hall, Jaclyn; Binford, Michael W.; Boring, Lindsay R.; Staudhammer, Christina L.
Forests are experiencing simultaneous changes in climate, disturbance regimes, and management, all of which affect ecosystem function. Climate change is shifting ranges and altering forest productivity. Disturbance regimes are changing with the potential for novel interactions among disturbance types. In some areas, forest management practices are intensifying, whereas in other areas, lower-impact ecological methods are being used. Interactions among these changing factors are likely to alter ecosystem structure and function at regional to continental scales. A macrosystems approach is essential to assessing the broadscale impacts of these changes and quantify cross-scale interactions, emergent patterns, and feedbacks. A promising line of analysis is the assimilation of data with ecosystem models to scale processes to the macrosystem and generate projections based on alternative scenarios. Analyses of these projections can characterize the range of future variability in forest function and provide information to guide policy, industry, and science in a changing world.
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.
Biosphere-atmosphere exchange of CO2 in relation to climate: a cross-biome analysis across multiple time scales
(2009-10) Stoy, Paul C.; Richardson, Andrew D.; Baldocchi, Dennis D.; Katul, Gabriel G.; Stanovick, J.; Mahecha, M. D.; Reichstein, M.; Detto, Matteo; Law, Beverly E.; Wohlfahrt, Georg; Arriga, N.; Campos, J.; McCaughey, J. H.; Montagnani, Leonardo; Paw U, Kyaw Tha; Sevanto, S.; Williams, Mathew
The net ecosystem exchange of CO2 (NEE) varies at time scales from seconds to years and longer via the response of its components, gross ecosystem productivity (GEP) and ecosystem respiration (RE), to physical and biological drivers. Quantifying the relationship between flux and climate at multiple time scales is necessary for a comprehensive understanding of the role of climate in the terrestrial carbon cycle. Orthonormal wavelet transformation (OWT) can quantify the strength of the interactions between gappy eddy covariance flux and micrometeorological measurements at multiple frequencies while expressing time series variance in few energetic wavelet coefficients, offering a low-dimensional view of the response of terrestrial carbon flux to climatic variability. The variability of NEE, GEP and RE, and their co-variability with dominant climatic drivers, are explored with nearly one thousand site-years of data from the FLUXNET global dataset consisting of 253 eddy covariance research sites. The NEE and GEP wavelet spectra were similar among plant functional types (PFT) at weekly and shorter time scales, but significant divergence appeared among PFT at the biweekly and longer time scales, at which NEE and GEP were relatively less variable than climate. The RE spectra rarely differed among PFT across time scales as expected. On average, RE spectra had greater low frequency (monthly to interannual) variability than NEE, GEP and climate. CANOAK ecosystem model simulations demonstrate that "multi-annual" spectral peaks in flux may emerge at low (4+ years) time scales. Biological responses to climate and other internal system dynamics, rather than direct ecosystem response to climate, provide the likely explanation for observed multi-annual variability, but data records must be lengthened and measurements of ecosystem state must be made, and made available, to disentangle the mechanisms responsible for low frequency patterns in ecosystem CO2 exchange.
Biotic interactions and biogeochemical processes in the soil environment
(2012-05-24) Subke, J.-A.; Carbone, M.S.; Khomik, M.; Stoy, Paul C.; Bahn, Michael
"Soils play a key role in the terrestrial carbon (C) cycle bystoring and emitting large quantities of C. The impact of abiotic conditions (mainly soil temperature and moisture) on soil C turnover is well documented, but unravelling the influence of these drivers across temporal and spatial scales remains an important challenge. Biotic factors, such as microbial abundance and diversity, macro-faunal food webs and below-ground plant (i.e. root) biomass and diversity, play an important role in controlling soil C storage and emission, but remain under-investigated. To better understand the soil processes underlying terrestrial C cycling, the interactions between plants (autotrophs) and soil organisms (heterotrophs) need to be addressed more explicitly and integrated with short- and long-term effects of abiotic drivers. This special issue presents recent advances in field, laboratory, and modelling studies on soil C dynamics, with a particular emphasis on those aiming to resolve abiotic and biotic influences. The manuscripts highlight three areas of investigation that we suggest are central to current and future progress in ecosystem C dynamic research: (1) novel interpretations of abiotic controls on soil CO2 efflux, (2) legacy effects of abiotic drivers of soil C dynamics, and (3) the interaction between plant C dynamics and soil biological processes."
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.
Causality and Persistence in Ecological Systems: A Nonparametric Spectral Granger Causality Approach
(2012-02-20) Detto, Matteo; Molini, Annalisa; Katul, Gabriel; Stoy, Paul C.; Palmroth, Sari; Baldocchi, Dennis
Directionality in coupling, defined as the linkage relating causes to their effects at a later time, can be used to explain the core dynamics of ecological systems by untangling direct and feedback relationships between the different components of the systems. Inferring causality from measured ecological variables sampled through time remains a formidable challenge further made difficult by the action of periodic drivers overlapping the natural dynamics of the system. Periodicity in the drivers can often mask the self-sustained oscillations originating from the autonomous dynamics. While linear and direct causal relationships are commonly addressed in the time domain, using the well-established machinery of Granger causality (G-causality), the presence of periodic forcing requires frequency-based statistics (e.g., the Fourier transform), able to distinguish coupling induced by oscillations in external drivers from genuine endogenous interactions. Recent nonparametric spectral extensions of G-causality to the frequency domain pave the way for the scale-by-scale decomposition of causality, which can improve our ability to link oscillatory behaviors of ecological networks to causal mechanisms. The performance of both spectral G-causality and its conditional extension for multivariate systems is explored in quantifying causal interactions within ecological networks. Through two case studies involving synthetic and actual time series, it is demonstrated that conditional G-causality outperforms standard G-causality in identifying causal links and their concomitant timescales.
Characterizing the diurnal patterns of errors in the prediction of evapotranspiration by several land‐surface models: An NACP analysis
(2014-07) Mathany, Ashley M.; Bohrer, Gil; Stoy, Paul C.; Baker, Ian T.; Black, Andy T.; Desai, Ankur R.; Gough, Christopher M.; Ivanov, Valeriy Y.; Jassal, Rachhpal S.; Novick, Kimberly A.; Schäfer, Karina V.R.; Verbeeck, Hans
Land-surface models use different formulations of stomatal conductance and plant hydraulics, and it is unclear which type of model best matches the observed surface-atmosphere water flux. We use the North American Carbon Program data set of latent heat flux (LE) measurements from 25 sites and predictions from 9 models to evaluate models' ability to resolve subdaily dynamics of transpiration. Despite overall good forecast at the seasonal scale, the models have difficulty resolving the dynamics of intradaily hysteresis. The majority of models tend to underestimate LE in the prenoon hours and overestimate in the evening. We hypothesize that this is a result of unresolved afternoon stomatal closure due to hydrodynamic stresses. Although no model or stomata parameterization was consistently best or worst in terms of ability to predict LE, errors in model-simulated LE were consistently largest and most variable when soil moisture was moderate and vapor pressure deficit was moderate to limiting. Nearly all models demonstrate a tendency to underestimate the degree of maximum hysteresis which, across all sites studied, is most pronounced during moisture-limited conditions. These diurnal error patterns are consistent with models' diminished ability to accurately simulate the natural hysteresis of transpiration. We propose that the lack of representation of plant hydrodynamics is, in part, responsible for these error patterns.
Characterizing the performance of ecosystem models across time scales: A spectral analysis of the North American Carbon Program site‐level synthesis
(2011-12-20) Dietze, Michael C.; Vargas, Rodrigo; Richardson, Andrew D.; Stoy, Paul C.; Barr, Alan G.; Anderson, Ryan S.; M. Altaf Arain, M. Altaf; Baker, Ian T.; Blac, T. Andrew; Chen, Jing M.; Ciais, Philippe; Flanagan, Lawrence B.; Gough, Christopher M.; Grant, Robert F.; Hollinger, David Y.; Izaurralde, R. Cesar; Kucharik, Christopher J.; Lafleur, Peter; Liu, Shuguang; Lokupitiya, Erandathie; Luo, Yiqi; Munger, J. William; Peng, Changhui; Poulter, Benjamin; Price, David T.; Ricciuto, Daniel M.; Riley, William J.; Sahoo, Alok Kumar; Schaefer, Kevin; Suyker, Andrew E.; Tain, Hanqin; Tonitto, Christina; Verbeeck, Hans; Verma, Shashi B.; Weifeng, Wang; Weng, Ensheng
Ecosystem models are important tools for diagnosing the carbon cycle and projecting its behavior across space and time. Despite the fact that ecosystems respond to drivers at multiple time scales, most assessments of model performance do not discriminate different time scales. Spectral methods, such as wavelet analyses, present an alternative approach that enables the identification of the dominant time scales contributing to model performance in the frequency domain. In this study we used wavelet analyses to synthesize the performance of 21 ecosystem models at 9 eddy covariance towers as part of the North American Carbon Program's site-level intercomparison. This study expands upon previous single-site and single-model analyses to determine what patterns of model error are consistent across a diverse range of models and sites. To assess the significance of model error at different time scales, a novel Monte Carlo approach was developed to incorporate flux observation error. Failing to account for observation error leads to a misidentification of the time scales that dominate model error. These analyses show that model error (1) is largest at the annual and 20–120 day scales, (2) has a clear peak at the diurnal scale, and (3) shows large variability among models in the 2–20 day scales. Errors at the annual scale were consistent across time, diurnal errors were predominantly during the growing season, and intermediate-scale errors were largely event driven. Breaking spectra into discrete temporal bands revealed a significant model-by-band effect but also a nonsignificant model-by-site effect, which together suggest that individual models show consistency in their error patterns. Differences among models were related to model time step, soil hydrology, and the representation of photosynthesis and phenology but not the soil carbon or nitrogen cycles. These factors had the greatest impact on diurnal errors, were less important at annual scales, and had the least impact at intermediate time scales.
Climate controls over the net carbon uptake period and amplitude of net ecosystem production in temperate and boreal ecosystems
(2017-09) Fu, Zheng; Stoy, Paul C.; Luo, Yiqi; Chen, Jiquan; Sun, Jian; Montagnani, Leonardo; Wohlfahrt, Georg; Rahman, Abdullah F.; Rambal, Serge; Bernhofer, Christian; Wang, Jinsong; Shirkey, Gabriela; Niu, Shuli
The seasonal and interannual variability of the terrestrial carbon cycle is regulated by the interactions of climate and ecosystem function. However, the key factors and processes determining the interannual variability of net ecosystem productivity (NEP) in different biomes are far from clear. Here, we quantified yearly anomalies of seasonal and annual NEP, net carbon uptake period (CUP), and the maximum daily NEP (NEPmax) in response to climatic variables in 24 deciduous broadleaf forest (DBF), evergreen forest (EF), and grassland (GRA) ecosystems that include at least eight years of eddy covariance observations. Over the 228 site-years studied, interannual variations in NEP were mostly explained by anomalies of CUP and NEPmax. CUP was determined by spring and autumn net carbon uptake phenology, which were sensitive to annual meteorological variability. Warmer spring temperatures led to an earlier start of net carbon uptake activity and higher spring and annual NEP values in DBF and EF, while warmer autumn temperatures in DBF, higher autumn radiation in EF, and more summer and autumn precipitation in GRA resulted in a later ending date of net carbon uptake and associated higher autumn and annual NEP. Anomalies in NEPmax s were determined by summer precipitation in DBF and GRA, and explained more than 50% of variation in summer NEP anomalies for all the three biomes. Results demonstrate the role of meteorological variability in controlling CUP and NEPmax, which in turn help describe the seasonal and interannual variability of NEP.
A Comparison of Methods Reveals that Enhanced Diffusion Helps Explain Cold-Season Soil CO 2 Efflux in a Lodgepole Pine Ecosystem
(2016-01) Rains, F. Aaron; Stoy, Paul C.; Welch, Christopher M.; Montagne, Cliff; McGlynn, Brian L.
Wintertime respiration contributes significantly to the annual loss of carbon from terrestrial ecosystems to the atmosphere, but the magnitude and physical transport mechanisms of this flux through snow remain unclear. Here, we quantify wintertime soil CO2 efflux in a Lodgepole pine (Pinus contorta Dougl.) forest by comparing chamber, flux gradient, and subcanopy eddy covariance measurements. CO2 efflux estimates from the flux gradient system deviated from the eddy covariance measurements during early and late winter but were only ca. 25% lower than eddy covariance measurements during the main snow accumulation period in mid-winter. During the snow-covered period, the flux gradient carbon efflux estimate (15 g C m− 2) was ca. three-fold less than eddy covariance measurements (49 g C m− 2). An analysis of the relationship between friction velocity and eddy covariance-measured CO2 efflux lends support to the notion that advection through snow is an important transport mechanism for trace gasses. A spectral Granger causality analysis indicates that the wind speed time series contributes information to the subnivean CO2 concentration time series during the melt period at time scales greater than 10 hours. All three methodologies indicate that wintertime respiration is a major contributor to the annual carbon budget: the sum of eddy covariance-measured CO2 efflux during the snow-covered period was 1/3 of that during the snow-free period of 2011 (ca. 140 g C m− 2). Future studies should incorporate adjustments for advection when using snow flux gradient systems to avoid underestimating the often-underappreciated contribution of the cold season to ecosystem CO2 efflux.
Controls on seasonal patterns of maximum ecosystem carbon uptake and canopy-scale photosynthetic light response: contributions from both temperature and photoperiod
(2014-02-14) Stoy, Paul C.; Trowbridge, Amy M.; Bauerle, William L.
Most models of photosynthetic activity assume that temperature is the dominant control over physiological processes. Recent studies have found, however, that photoperiod is a better descriptor than temperature of the seasonal variability of photosynthetic physiology at the leaf scale. Incorporating photoperiodic control into global models consequently improves their representation of the seasonality and magnitude of atmospheric CO2 concentration. The role of photoperiod versus that of temperature in controlling the seasonal variability of photosynthetic function at the canopy scale remains unexplored. We quantified the seasonal variability of ecosystem-level light response curves using nearly 400 site years of eddy covariance data from over eighty Free Fair-Use sites in the FLUXNET database. Model parameters describing maximum canopy CO2uptake and the initial slope of the light response curve peaked after peak temperature in about 2/3 of site years examined, emphasizing the important role of temperature in controlling seasonal photosynthetic function. Akaike’s Information Criterion analyses indicated that photoperiod should be included in models of seasonal parameter variability in over 90 % of the site years investigated here, demonstrating that photoperiod also plays an important role in controlling seasonal photosynthetic function. We also performed a Granger causality analysis on both gross ecosystem productivity (GEP) and GEP normalized by photosynthetic photon flux density (GEP n ). While photoperiod Granger-caused GEP and GEP n in 99 and 92 % of all site years, respectively, air temperature Granger-caused GEP in a mere 32 % of site years but Granger-caused GEP n in 81 % of all site years. Results demonstrate that incorporating photoperiod may be a logical step toward improving models of ecosystem carbon uptake, but not at the expense of including enzyme kinetic-based temperature constraints on canopy-scale photosynthesis.
A data-driven analysis of energy balance closure across FLUXNET research sites: The role of landscape scale heterogeneity
(2013-04-15) Stoy, Paul C.; Mauder, Matthias; Foken, Thomas; Marcolla, Barbara; Boegh, Eva; Ibrom, Andreas; Arain, M. Altaf
The energy balance at most surface-atmosphere flux research sites remains unclosed. The mechanisms underlying the discrepancy between measured energy inputs and outputs across the global FLUXNET tower network are still under debate. Recent reviews have identified exchange processes and turbulent motions at large spatial and temporal scales in heterogeneous landscapes as the primary cause of the lack of energy balance closure at some intensively-researched sites, while unmeasured storage terms cannot be ruled out as a dominant contributor to the lack of energy balance closure at many other sites. We analyzed energy balance closure across 173 ecosystems in the FLUXNET database and explored the relationship between energy balance closure and landscape heterogeneity using MODIS products and GLOBEstat elevation data. Energy balance closure per research site (CEB,s) averaged 0.84 ± 0.20, with best average closures in evergreen broadleaf forests and savannas (0.91–0.94) and worst average closures in crops, deciduous broadleaf forests, mixed forests and wetlands (0.70–0.78). Half-hourly or hourly energy balance closure on a percent basis increased with friction velocity (u*) and was highest on average under near-neutral atmospheric conditions. CEB,s was significantly related to mean precipitation, gross primary productivity and landscape-level enhanced vegetation index (EVI) from MODIS, and the variability in elevation, MODIS plant functional type, and MODIS EVI. A linear model including landscape-level variability in both EVI and elevation, mean precipitation, and an interaction term between EVI variability and precipitation had the lowest Akaike's information criterion value. CEB,s in landscapes with uniform plant functional type approached 0.9 and CEB,s in landscapes with uniform EVI approached 1. These results suggest that landscape-level heterogeneity in vegetation and topography cannot be ignored as a contributor to incomplete energy balance closure at the flux network level, although net radiation measurements, biological energy assimilation, unmeasured storage terms, and the importance of good practice including site selection when making flux measurements should not be discounted. Our results suggest that future research should focus on the quantitative mechanistic relationships between energy balance closure and landscape-scale heterogeneity, and the consequences of mesoscale circulations for surface-atmosphere exchange measurements.
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.
Downward transport of ozone rich air & implications for atmospheric chemistry in the Amazon rainforest
(2016-01) Gerken, Tobias; Wei, Dandan; Chase, Randy J.; Fuentes, Jose D.; Schumacher, Courtney; Machado, Luiz A.; Andreoli, Rita V.; Chamecki, Marcelo; Ferreira de Souza, Rodrigo A.; Freire, Livia S.; Jardine, Angela B.; Manzi, Antonio O.; Nascimento dos Santos, Rosa M.; von Randow, Celso; dos Santos Costa, Patricia; Stoy, Paul C.; Tota, Julio; Trowbridge, Amy M.
From April 2014 to January 2015, ozone (O3) dynamics were investigated as part of GoAmazon 2014/5 project in the central Amazon rainforest of Brazil. Just above the forest canopy, maximum hourly O3 mixing ratios averaged 20 ppbv (parts per billion on a volume basis) during the June–September dry months and 15 ppbv during the wet months. Ozone levels occasionally exceeded 75 ppbv in response to influences from biomass burning and regional air pollution. Individual convective storms transported O3-rich air parcels from the mid-troposphere to the surface and abruptly enhanced the regional atmospheric boundary layer by as much as 25 ppbv. In contrast to the individual storms, days with multiple convective systems produced successive, cumulative ground-level O3 increases. The magnitude of O3 enhancements depended on the vertical distribution of O3 within storm downdrafts and origin of downdrafts in the troposphere. Ozone mixing ratios remained enhanced for > 2 h following the passage of storms, which enhanced chemical processing of rainforest-emitted isoprene and monoterpenes. Reactions of isoprene and monoterpenes with O3 are modeled to generate maximum hydroxyl radical formation rates of 6 × 106 radicals cm−3s−1. Therefore, one key conclusion of the present study is that downdrafts of convective storms are estimated to transport enough O3 to the surface to initiate a series of reactions that reduce the lifetimes of rainforest-emitted hydrocarbons.
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.