Kling George W.

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Kling
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George W.
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Author: Rastetter, Edward B. ×

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  • Article
    Nitrate is an important nitrogen source for Arctic tundra plants
    (National Academy of Sciences, 2018-03-27) Liu, Xue-Yan ; Koba, Keisuke ; Koyama, Lina A. ; Hobbie, Sarah E. ; Weiss, Marissa S. ; Inagaki, Yoshiyuki ; Shaver, Gaius R. ; Giblin, Anne E. ; Hobara, Satoru ; Nadelhoffer, Knute J. ; Sommerkorn, Martin ; Rastetter, Edward B. ; Kling, George W. ; Laundre, James A. ; Yano, Yuriko ; Makabe, Akiko ; Yano, Midori ; Liu, Cong-Qiang
    Plant nitrogen (N) use is a key component of the N cycle in terrestrial ecosystems. The supply of N to plants affects community species composition and ecosystem processes such as photosynthesis and carbon (C) accumulation. However, the availabilities and relative importance of different N forms to plants are not well understood. While nitrate (NO3−) is a major N form used by plants worldwide, it is discounted as a N source for Arctic tundra plants because of extremely low NO3− concentrations in Arctic tundra soils, undetectable soil nitrification, and plant-tissue NO3− that is typically below detection limits. Here we reexamine NO3− use by tundra plants using a sensitive denitrifier method to analyze plant-tissue NO3−. Soil-derived NO3− was detected in tundra plant tissues, and tundra plants took up soil NO3− at comparable rates to plants from relatively NO3−-rich ecosystems in other biomes. Nitrate assimilation determined by 15N enrichments of leaf NO3− relative to soil NO3− accounted for 4 to 52% (as estimated by a Bayesian isotope-mixing model) of species-specific total leaf N of Alaskan tundra plants. Our finding that in situ soil NO3− availability for tundra plants is high has important implications for Arctic ecosystems, not only in determining species compositions, but also in determining the loss of N from soils via leaching and denitrification. Plant N uptake and soil N losses can strongly influence C uptake and accumulation in tundra soils. Accordingly, this evidence of NO3− availability in tundra soils is crucial for predicting C storage in tundra.
  • Article
    Processing arctic eddy-flux data using a simple carbon-exchange model embedded in the ensemble Kalman filter
    (Ecological Society of America, 2010-07) Rastetter, Edward B. ; Williams, Mathew ; Griffin, Kevin L. ; Kwiatkowski, Bonnie L. ; Tomasky, Gabrielle ; Potosnak, Mark J. ; Stoy, Paul C. ; Shaver, Gaius R. ; Stieglitz, Marc ; Hobbie, John E. ; Kling, George W.
    Continuous time-series estimates of net ecosystem carbon exchange (NEE) are routinely made using eddy covariance techniques. Identifying and compensating for errors in the NEE time series can be automated using a signal processing filter like the ensemble Kalman filter (EnKF). The EnKF compares each measurement in the time series to a model prediction and updates the NEE estimate by weighting the measurement and model prediction relative to a specified measurement error estimate and an estimate of the model-prediction error that is continuously updated based on model predictions of earlier measurements in the time series. Because of the covariance among model variables, the EnKF can also update estimates of variables for which there is no direct measurement. The resulting estimates evolve through time, enabling the EnKF to be used to estimate dynamic variables like changes in leaf phenology. The evolving estimates can also serve as a means to test the embedded model and reconcile persistent deviations between observations and model predictions. We embedded a simple arctic NEE model into the EnKF and filtered data from an eddy covariance tower located in tussock tundra on the northern foothills of the Brooks Range in northern Alaska, USA. The model predicts NEE based only on leaf area, irradiance, and temperature and has been well corroborated for all the major vegetation types in the Low Arctic using chamber-based data. This is the first application of the model to eddy covariance data. We modified the EnKF by adding an adaptive noise estimator that provides a feedback between persistent model data deviations and the noise added to the ensemble of Monte Carlo simulations in the EnKF. We also ran the EnKF with both a specified leaf-area trajectory and with the EnKF sequentially recalibrating leaf-area estimates to compensate for persistent model-data deviations. When used together, adaptive noise estimation and sequential recalibration substantially improved filter performance, but it did not improve performance when used individually. The EnKF estimates of leaf area followed the expected springtime canopy phenology. However, there were also diel fluctuations in the leaf-area estimates; these are a clear indication of a model deficiency possibly related to vapor pressure effects on canopy conductance.
  • Article
    Ecosystem responses to climate change at a Low Arctic and a High Arctic long-term research site
    (Springer, 2017-01-23) Hobbie, John E. ; Shaver, Gaius R. ; Rastetter, Edward B. ; Cherry, Jessica E. ; Goetz, Scott J. ; Guay, Kevin C. ; Gould, William A. ; Kling, George W.
    Long-term measurements of ecological effects of warming are often not statistically significant because of annual variability or signal noise. These are reduced in indicators that filter or reduce the noise around the signal and allow effects of climate warming to emerge. In this way, certain indicators act as medium pass filters integrating the signal over years-to-decades. In the Alaskan Arctic, the 25-year record of warming of air temperature revealed no significant trend, yet environmental and ecological changes prove that warming is affecting the ecosystem. The useful indicators are deep permafrost temperatures, vegetation and shrub biomass, satellite measures of canopy reflectance (NDVI), and chemical measures of soil weathering. In contrast, the 18-year record in the Greenland Arctic revealed an extremely high summer air-warming of 1.3°C/decade; the cover of some plant species increased while the cover of others decreased. Useful indicators of change are NDVI and the active layer thickness.
  • 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.