Benchmarking and parameter sensitivity of physiological and vegetation dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama

Charles D. Koven, Ryan G. Knox, Rosie A. Fisher, Rosie A. Fisher, Jeffrey Q. Chambers, Jeffrey Q. Chambers, Bradley O. Christoffersen, Stuart J. Davies, Matteo Detto, Matteo Detto, Michael C. Dietze, Boris Faybishenko, Jennifer Holm, Maoyi Huang, Marlies Kovenock, Lara M. Kueppers, Lara M. Kueppers, Gregory Lemieux, Elias Massoud, Nathan G. McDowellHelene C. Muller-Landau, Helene C. Muller-Landau, Jessica F. Needham, Richard J. Norby, Thomas Powell, Alistair Rogers, Shawn P. Serbin, Jacquelyn K. Shuman, Abigail L.S. Swann, Abigail L.S. Swann, Charuleka Varadharajan, Anthony P. Walker, S. Joseph Wright, Chonggang Xu

Research output: Contribution to journalArticlepeer-review

127 Scopus citations

Abstract

Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include (a) the number of competing PFTs present in any simulation and (b) parameters that govern disturbance and height-based light competition. While singlePFT simulations are roughly consistent with observations of productivity at Barro Colorado Island, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e., the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early-and late-successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional-dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not and to better understand the relationships between these two types of model parameters to quantify sources of uncertainty in VDMs.

Original languageEnglish
Pages (from-to)3017-3044
Number of pages28
JournalBiogeosciences
Volume17
Issue number11
DOIs
StatePublished - Jun 15 2020

Funding

Financial support. This research has been supported by the US De- Acknowledgements. This research was supported as part of the Next-Generation Ecosystem Experiments – Tropics, funded by the US Department of Energy, Office of Science, Office of Biological and Environmental Research. Charles D. Koven also acknowledges support from the DOE Early Career Research Program. LBNL is managed and operated by the Regents of the University of California under prime contract no. DE-AC02-05CH11231. Alistair Rogers and Shawn P. Serbin were also supported through the United States Department of Energy contract no. DE-SC0012704 to Brookhaven National Laboratory. Michael C. Dietze was supported by NSF 1458021. Oak Ridge National Laboratory is operated by UT–Battelle, LLC, under contract no. DE-AC05-00OR22725 with the US Department of Energy. Pacific Northwest National Laboratory is operated by the DOE by the Battelle Memorial Institute under contract DE-AC05-76RL01830. Matteo Detto was supported by the Carbon Mitigation Initiative at Princeton University.

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