Starr Gregory

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Starr
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Gregory
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  • Article
    A robust calibration method for continental-scale soil water content measurements
    (American Society of Agronomy, 2018-05-24) Roberti, Joshua A. ; Ayres, Edward ; Loescher, Henry W. ; Tang, Jianwu ; Starr, Gregory ; Durden, David J. ; Smith, Derek E. ; de la Reguera, Elizabeth ; Morkeski, Kate ; McKlveen, Margot ; Benstead, Heidi ; SanClements, Michael D. ; Lee, Robert H. ; Gebremedhin, Gebremedhin ; Zulueta, Rommel C.
    Technological advances have allowed in situ monitoring of soil water content in an automated manner. These advances, along with an increase in large-scale networks monitoring soil water content, stress the need for a robust calibration framework that ensures that soil water content measurements are accurate and reliable. We have developed an approach to make consistent and comparable soil water content sensor calibrations across a continental-scale network in a production framework that incorporates a thorough accounting of uncertainties. More than 150 soil blocks of varying characteristics from 33 locations across the United States were used to generate soil-specific calibration coefficients for a capacitance sensor. We found that the manufacturer’s nominal calibration coefficients poorly fit the data for nearly all soil types. This resulted in negative (91% of samples) and positive (5% of samples) biases and a mean root mean square error (RMSE) of 0.123 cm3 cm−3 (1σ) relative to reference standard measurements. We derived soil-specific coefficients, and when used with the manufacturer’s nominal function, the biases were corrected and the mean RMSE dropped to ±0.017 cm3 cm−3 (±1σ). A logistic calibration function further reduced the mean RMSE to ±0.016 cm3 cm−3 (±1σ) and increased the range of soil moistures to which the calibration applied by 18% compared with the manufacturer’s function. However, the uncertainty of the reference standard was notable (±0.022 cm3 cm−3), and when propagated in quadrature with RMSE estimates, the combined uncertainty of the calibrated volumetric soil water content values increased to ±0.028 cm3 cm−3 regardless of the calibration function used.
  • Article
    Biomass offsets little or none of permafrost carbon release from soils, streams, and wildfire : an expert assessment
    (IOPScience, 2016-03-07) Abbott, Benjamin W. ; Jones, Jeremy B. ; Schuur, Edward A. G. ; Chapin, F. Stuart ; Bowden, William B. ; Bret-Harte, M. Syndonia ; Epstein, Howard E. ; Flannigan, Michael ; Harms, Tamara K. ; Hollingsworth, Teresa N. ; Mack, Michelle C. ; McGuire, A. David ; Natali, Susan M. ; Rocha, Adrian V. ; Tank, Suzanne E. ; Turetsky, Merritt R. ; Vonk, Jorien E. ; Wickland, Kimberly ; Aiken, George R. ; Alexander, Heather D. ; Amon, Rainer M. W. ; Benscoter, Brian ; Bergeron, Yves ; Bishop, Kevin ; Blarquez, Olivier ; Bond-Lamberty, Benjamin ; Breen, Amy L. ; Buffam, Ishi ; Cai, Yihua ; Carcaillet, Christopher ; Carey, Sean K. ; Chen, Jing M. ; Chen, Han Y. H. ; Christensen, Torben R. ; Cooper, Lee W. ; Cornelissen, Johannes H. C. ; de Groot, William J. ; DeLuca, Thomas Henry ; Dorrepaal, Ellen ; Fetcher, Ned ; Finlay, Jacques C. ; Forbes, Bruce C. ; French, Nancy H. F. ; Gauthier, Sylvie ; Girardin, Martin ; Goetz, Scott J. ; Goldammer, Johann G. ; Gough, Laura ; Grogan, Paul ; Guo, Laodong ; Higuera, Philip E. ; Hinzman, Larry ; Hu, Feng Sheng ; Hugelius, Gustaf ; JAFAROV, ELCHIN ; Jandt, Randi ; Johnstone, Jill F. ; Karlsson, Jan ; Kasischke, Eric S. ; Kattner, Gerhard ; Kelly, Ryan ; Keuper, Frida ; Kling, George W. ; Kortelainen, Pirkko ; Kouki, Jari ; Kuhry, Peter ; Laudon, Hjalmar ; Laurion, Isabelle ; Macdonald, Robie W. ; Mann, Paul J. ; Martikainen, Pertti ; McClelland, James W. ; Molau, Ulf ; Oberbauer, Steven F. ; Olefeldt, David ; Paré, David ; Parisien, Marc-André ; Payette, Serge ; Peng, Changhui ; Pokrovsky, Oleg ; Rastetter, Edward B. ; Raymond, Peter A. ; Raynolds, Martha K. ; Rein, Guillermo ; Reynolds, James F. ; Robards, Martin ; Rogers, Brendan ; Schädel, Christina ; Schaefer, Kevin ; Schmidt, Inger K. ; Shvidenko, Anatoly ; Sky, Jasper ; Spencer, Robert G. M. ; Starr, Gregory ; Striegl, Robert ; Teisserenc, Roman ; Tranvik, Lars J. ; Virtanen, Tarmo ; Welker, Jeffrey M. ; Zimov, Sergey A.
    As the permafrost region warms, its large organic carbon pool will be increasingly vulnerable to decomposition, combustion, and hydrologic export. Models predict that some portion of this release will be offset by increased production of Arctic and boreal biomass; however, the lack of robust estimates of net carbon balance increases the risk of further overshooting international emissions targets. Precise empirical or model-based assessments of the critical factors driving carbon balance are unlikely in the near future, so to address this gap, we present estimates from 98 permafrost-region experts of the response of biomass, wildfire, and hydrologic carbon flux to climate change. Results suggest that contrary to model projections, total permafrost-region biomass could decrease due to water stress and disturbance, factors that are not adequately incorporated in current models. Assessments indicate that end-of-the-century organic carbon release from Arctic rivers and collapsing coastlines could increase by 75% while carbon loss via burning could increase four-fold. Experts identified water balance, shifts in vegetation community, and permafrost degradation as the key sources of uncertainty in predicting future system response. In combination with previous findings, results suggest the permafrost region will become a carbon source to the atmosphere by 2100 regardless of warming scenario but that 65%–85% of permafrost carbon release can still be avoided if human emissions are actively reduced.
  • 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.