Stuart-Haëntjens Ellen

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Stuart-Haëntjens
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Ellen
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  • Article
    Representativeness of eddy-covariance flux footprints for areas surrounding AmeriFlux sites
    (Elsevier, 2021-02-14) Chu, Housen ; Luo, Xiangzhong ; Ouyang, Zutao ; Chan, W. Stephen ; Dengel, Sigrid ; Biraud, Sebastien ; Torn, Margaret S. ; Metzger, Stefan ; Kumar, Jitendra ; Arain, M. Altaf ; Arkebauer, Tim J. ; Baldocchi, Dennis D. ; Bernacchi, Carl ; Billesbach, Dave ; Black, T. Andrew ; Blanken, Peter D. ; Bohrer, Gil ; Bracho, Rosvel ; Brown, Shannon ; Brunsell, Nathaniel A. ; Chen, Jiquan ; Chen, Xingyuan ; Clark, Kenneth ; Desai, Ankur R. ; Duman, Tomer ; Durden, David J. ; Fares, Silvano ; Forbrich, Inke ; Gamon, John ; Gough, Christopher M. ; Griffis, Timothy ; Helbig, Manuel ; Hollinger, David ; Humphreys, Elyn ; Ikawa, Hiroki ; Iwata, Hiroki ; Ju, Yang ; Knowles, John F. ; Knox, Sara H. ; Kobayashi, Hideki ; Kolb, Thomas ; Law, Beverly ; Lee, Xuhui ; Litvak, Marcy ; Liu, Heping ; Munger, J. William ; Noormets, Asko ; Novick, Kim ; Oberbauer, Steven F. ; Oechel, Walter ; Oikawa, Patty ; Papuga, Shirley A. ; Pendall, Elise ; Prajapati, Prajaya ; Prueger, John ; Quinton, William L. ; Richardson, Andrew D. ; Russell, Eric S. ; Scott, Russell L. ; Starr, Gregory ; Staebler, Ralf ; Stoy, Paul C. ; Stuart-Haëntjens, Ellen ; Sonnentag, Oliver ; Sullivan, Ryan C. ; Suyker, Andy ; Ueyama, Masahito ; Vargas, Rodrigo ; Wood, Jeffrey D. ; Zona, Donatella
    Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use.
  • Article
    A new coupled biogeochemical modeling approach provides accurate predictions of methane and carbon bioxide fluxes across diverse tidal wetlands
    (American Geophysical Union, 2024-10-13) Oikawa, Patty Y. ; Sihi, Debjani ; Forbrich, Inke ; Fluet-Chouinard, Etienne ; Najarro, Michael ; Thomas, Olaoluwalotobi ; Shahan, Julie ; Arias-Ortiz, Ariane ; Russell, Sarah ; Knox, Sara H. ; McNicol, Gavin ; Wolfe, Jaxine ; Windham-Myers, Lisamarie ; Stuart-Haentjens, Ellen ; Bridgham, Scott D. ; Needelman, Brian A. ; Vargas, Rodrigo ; Schäfer, Karina ; Ward, Eric J. ; Megonigal, J. Patrick ; Holmquist, James R.
    Tidal wetlands provide valuable ecosystem services, including storing large amounts of carbon. However, the net exchanges of carbon dioxide (CO2) and methane (CH4) in tidal wetlands are highly uncertain. While several biogeochemical models can operate in tidal wetlands, they have yet to be parameterized and validated against high-frequency, ecosystem-scale CO2 and CH4 flux measurements across diverse sites. We paired the Cohort Marsh Equilibrium Model (CMEM) with a version of the PEPRMT model called PEPRMT-Tidal, which considers the effects of water table height, sulfate, and nitrate availability on CO2 and CH4 emissions. Using a model-data fusion approach, we parameterized the model with three sites and validated it with two independent sites, with representation from the three marine coasts of North America. Gross primary productivity (GPP) and ecosystem respiration (Reco) modules explained, on average, 73% of the variation in CO2 exchange with low model error (normalized root mean square error (nRMSE) <1). The CH4 module also explained the majority of variance in CH4 emissions in validation sites (R2 = 0.54; nRMSE = 1.15). The PEPRMT-Tidal-CMEM model coupling is a key advance toward constraining estimates of greenhouse gas emissions across diverse North American tidal wetlands. Further analyses of model error and case studies during changing salinity conditions guide future modeling efforts regarding four main processes: (a) the influence of salinity and nitrate on GPP, (b) the influence of laterally transported dissolved inorganic C on Reco, (c) heterogeneous sulfate availability and methylotrophic methanogenesis impacts on surface CH4 emissions, and (d) CH4 responses to non-periodic changes in salinity.