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Title: Vegetation Demographics in Earth System Models: a review of progress and priorities

Abstract

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). Furthermore, these developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. We review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We also argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [2];  [7];  [2];  [1];  [8];  [9];  [10];  [11];  [12];  [2];  [13];  [14];  [1];  [15] more »;  [16];  [17];  [18];  [19];  [4];  [20];  [8];  [21] « less
  1. National Center for Atmospheric Research, Boulder, CO (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. Univ. of Utah, Salt Lake City, UT (United States). Dept. of Biology
  4. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  5. Boston Univ., MA (United States). Dept. of Earth and Environment
  6. Univ. of Texas, Austin, TX (United States). Dept. of Integrative Biology
  7. Univ. of Maryland, College Park, MD (United States). Dept. of Geographic Sciences
  8. Univ. of Florida, Gainesville, FL (United States). Dept. of Biology
  9. Embrapa Agricultural Informatics, Campinas SP (Brazil)
  10. Univ. of Texas, Austin, TX (United States). Dept. of Geological Sciences
  11. Univ. of Notre Dame, IN (United States). Dept. of Biological Sciences
  12. Smithsonian Tropical Research Inst., Panama (Republic of Panama)
  13. Brookhaven National Lab. (BNL), Upton, NY (United States). Environmental and Climate Sciences Dept.
  14. Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama (Japan)
  15. Lund Univ. (Sweden). Dept. of Physical Geography and Ecosystem Science
  16. Princeton Univ., NJ (United States). Program in Atmospheric and Oceanic Sciences
  17. Smithsonian Tropical Research Institute, Apartado Postal, 0843-03092 Panamá, República de Panamá
  18. Ghent Univ., Gent (Belgium). Dept. of Applied Ecology and Environmental Biology
  19. Columbia Univ., New York, NY (United States). Center for Climate Systems Research
  20. Princeton Univ., NJ (United States). Dept. of Geosciences
  21. Harvard Univ., Cambridge, MA (United States). Dept. of Organismic and Evolutionary Biology
Publication Date:
Research Org.:
Brookhaven National Laboratory (BNL), Upton, NY (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1392227
Alternate Identifier(s):
OSTI ID: 1402525; OSTI ID: 1439230
Report Number(s):
BNL-114231-2017-JA
Journal ID: ISSN 1354-1013; R&D Project: 21087; YN0100000
Grant/Contract Number:  
SC0012704; SC0014363; AC02-05CH11231
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Global Change Biology
Additional Journal Information:
Journal Volume: 24; Journal Issue: 1; Journal ID: ISSN 1354-1013
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; demographics; earth system model; vegetation; DGVM; ecosystem; carbon cycle

Citation Formats

Fisher, Rosie A., Koven, Charles D., Anderegg, William R. L., Christoffersen, Bradley O., Dietze, Michael C., Farrior, Caroline, Holm, Jennifer A., Hurtt, George, Knox, Ryan G., Lawrence, Peter J., Lichststein, Jeremy W., Longo, Marcos, Matheny, Ashley M., Medvigy, David, Muller-Landau, Helene C., Powell, Thomas L., Serbin, Shawn P., Sato, Hisashi, Shuman, Jacquelyn, Smith, Benjamin, Trugman, Anna T., Viskari, Toni, Verbeeck, Hans, Weng, Ensheng, Xu, Chonggang, Xu, Xiangtao, Zhang, Tao, and Moorcroft, Paul. Vegetation Demographics in Earth System Models: a review of progress and priorities. United States: N. p., 2017. Web. doi:10.1111/gcb.13910.
Fisher, Rosie A., Koven, Charles D., Anderegg, William R. L., Christoffersen, Bradley O., Dietze, Michael C., Farrior, Caroline, Holm, Jennifer A., Hurtt, George, Knox, Ryan G., Lawrence, Peter J., Lichststein, Jeremy W., Longo, Marcos, Matheny, Ashley M., Medvigy, David, Muller-Landau, Helene C., Powell, Thomas L., Serbin, Shawn P., Sato, Hisashi, Shuman, Jacquelyn, Smith, Benjamin, Trugman, Anna T., Viskari, Toni, Verbeeck, Hans, Weng, Ensheng, Xu, Chonggang, Xu, Xiangtao, Zhang, Tao, & Moorcroft, Paul. Vegetation Demographics in Earth System Models: a review of progress and priorities. United States. doi:10.1111/gcb.13910.
Fisher, Rosie A., Koven, Charles D., Anderegg, William R. L., Christoffersen, Bradley O., Dietze, Michael C., Farrior, Caroline, Holm, Jennifer A., Hurtt, George, Knox, Ryan G., Lawrence, Peter J., Lichststein, Jeremy W., Longo, Marcos, Matheny, Ashley M., Medvigy, David, Muller-Landau, Helene C., Powell, Thomas L., Serbin, Shawn P., Sato, Hisashi, Shuman, Jacquelyn, Smith, Benjamin, Trugman, Anna T., Viskari, Toni, Verbeeck, Hans, Weng, Ensheng, Xu, Chonggang, Xu, Xiangtao, Zhang, Tao, and Moorcroft, Paul. Mon . "Vegetation Demographics in Earth System Models: a review of progress and priorities". United States. doi:10.1111/gcb.13910. https://www.osti.gov/servlets/purl/1392227.
@article{osti_1392227,
title = {Vegetation Demographics in Earth System Models: a review of progress and priorities},
author = {Fisher, Rosie A. and Koven, Charles D. and Anderegg, William R. L. and Christoffersen, Bradley O. and Dietze, Michael C. and Farrior, Caroline and Holm, Jennifer A. and Hurtt, George and Knox, Ryan G. and Lawrence, Peter J. and Lichststein, Jeremy W. and Longo, Marcos and Matheny, Ashley M. and Medvigy, David and Muller-Landau, Helene C. and Powell, Thomas L. and Serbin, Shawn P. and Sato, Hisashi and Shuman, Jacquelyn and Smith, Benjamin and Trugman, Anna T. and Viskari, Toni and Verbeeck, Hans and Weng, Ensheng and Xu, Chonggang and Xu, Xiangtao and Zhang, Tao and Moorcroft, Paul},
abstractNote = {Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). Furthermore, these developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. We review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We also argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.},
doi = {10.1111/gcb.13910},
journal = {Global Change Biology},
number = 1,
volume = 24,
place = {United States},
year = {Mon Sep 18 00:00:00 EDT 2017},
month = {Mon Sep 18 00:00:00 EDT 2017}
}

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