Abstract
Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process-based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet.
Original language | English |
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Pages (from-to) | 6453-6477 |
Number of pages | 25 |
Journal | Global Change Biology |
Volume | 29 |
Issue number | 23 |
DOIs | |
State | Published - Dec 2023 |
Funding
This manuscript was a product of a Long-Term Ecological Research (LTER) synthesis group funded by NSF EF-0553768 and DEB-1545288 through the LTER Network Communications Office and the National Center for Ecological Analysis and Synthesis. Support was provided to KRW by DOE DE-SC0019037 and NSF DEB-1856383. Many thanks to Elijan Masango and Beau Kindling for their assistance in collecting the plant structural measurements in Kruger National Park for Figure 3. We also thank Xiulin Gao, Daniel Griffith, and anonymous reviewers for constructive feedback on previous versions of this manuscript. This manuscript has been co‐authored by UT‐Battelle, LLC under contract no. DE‐AC05‐00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non‐exclusive, paid‐up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe‐public‐access‐plan ). This manuscript was a product of a Long‐Term Ecological Research (LTER) synthesis group funded by NSF EF‐0553768 and DEB‐1545288 through the LTER Network Communications Office and the National Center for Ecological Analysis and Synthesis. Support was provided to KRW by DOE DE‐SC0019037 and NSF DEB‐1856383. Many thanks to Elijan Masango and Beau Kindling for their assistance in collecting the plant structural measurements in Kruger National Park for Figure 3 . We also thank Xiulin Gao, Daniel Griffith, and anonymous reviewers for constructive feedback on previous versions of this manuscript.
Funders | Funder number |
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Long-Term Ecological Research | |
National Science Foundation | DEB-1545288, EF-0553768 |
U.S. Department of Energy | DE‐SC0019037, DEB‐1856383 |
UT-Battelle |
Keywords
- biogeochemistry
- ecology
- ecophysiology
- plant competition
- plant growth
- process-based models
- vegetation demographic models