Vegetation demographics in Earth System Models: A review of progress and priorities

Rosie A. Fisher, Charles D. Koven, William R.L. Anderegg, Bradley O. Christoffersen, Michael C. Dietze, Caroline E. Farrior, Jennifer A. Holm, George C. Hurtt, Ryan G. Knox, Peter J. Lawrence, Jeremy W. Lichstein, Marcos Longo, Ashley M. Matheny, David Medvigy, Helene C. Muller-Landau, Thomas L. Powell, Shawn P. Serbin, Hisashi Sato, Jacquelyn K. Shuman, Benjamin SmithAnna T. Trugman, Toni Viskari, Hans Verbeeck, Ensheng Weng, Chonggang Xu, Xiangtao Xu, Tao Zhang, Paul R. Moorcroft

Research output: Contribution to journalReview articlepeer-review

246 Scopus citations

Abstract

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). 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. Here, 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 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.

Original languageEnglish (US)
Pages (from-to)35-54
Number of pages20
JournalGlobal change biology
Volume24
Issue number1
DOIs
StatePublished - Jan 2018

Bibliographical note

Funding Information:
The outline for this manuscript was identified during a workshop focused on VDM implementation in ESMs held at the National Center for Atmospheric Research in January 2016. NCAR is sponsored by the National Science Foundation. CDK, BC, RK, JH, TP, JS, CX, & SPS were supported by the Next-Generation Ecosystem Experiments (NGEE Tropics) project that is supported by the Office of Biological and Environmental Research in the Department of Energy, Office of Science. TV and SPS were supported by NASA Terrestrial Ecology grant NNX14AH65G and through the United States Department of Energy contract No. DE-SC0012704 to Brookhaven National Laboratory. ATT was partially supported by a National Science Foundation Graduate scholarship. BS acknowledges support from the Strategic Research Fellowship Area MERGE. ML was funded by FAPESP (grant 2015/07227-6)” AMM was supported by U.S. National Science Foundation Hydrological Science grant 1521238. GH acknowledges the support of NASA. JL and TZ were funded by USDA agreements 11-JV-112423-059 and 16-JV-11242306-050. DM acknowledges support from the US Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science (TES) Program under award number DE-SC0014363. HV was supported by the ERC starting grant 637643 (TREECLIMBERS).

Funding Information:
Number: DE-SC0012704; National Science Foundation; FAPESP, Grant/Award Number: 2015/07227-6; U.S. National Science Foundation Hydrological Science, Grant/ Award Number: 1521238; USDA, Grant/ Award Number: 11-JV-112423-059, 16-JV- 11242306-050; US Department of Energy, Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Science (TES), Grant/Award Number: DE-SC0014363

Publisher Copyright:
© 2017 John Wiley & Sons Ltd

Keywords

  • Earth System Model
  • carbon cycle
  • demographics
  • dynamic global vegetation models
  • ecosystem
  • vegetation

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