Journal
GLOBAL CHANGE BIOLOGY
Volume 24, Issue 1, Pages 35-54Publisher
WILEY
DOI: 10.1111/gcb.13910
Keywords
carbon cycle; demographics; dynamic global vegetation models; Earth System Model; ecosystem; vegetation
Funding
- Division of Atmospheric and Geospace Sciences
- Biological and Environmental Research
- NASA Terrestrial Ecology [NNX14AH65G]
- United States Department of Energy [DE-SC0012704]
- National Science Foundation
- FAPESP [2015/07227-6]
- U.S. National Science Foundation Hydrological Science [1521238]
- USDA [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) [DE-SC0014363]
- Direct For Biological Sciences
- Div Of Biological Infrastructure [1458021] Funding Source: National Science Foundation
- Directorate For Geosciences
- Division Of Earth Sciences [1521238] Funding Source: National Science Foundation
- NASA [682497, NNX14AH65G] Funding Source: Federal RePORTER
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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.
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