Most earth system models fail to capture the seasonality of carbon fluxes in radiation-limited tropical evergreen forests (TEF) in the Amazon. Kim et al. (2012, https://doi.org/10.1111/j.1365-2486.2011.02629.x) first statistically incorporated a light-controlled phenology module into an ecosystem model to improve carbon flux simulations at one TEF site. However, it is not clear how their approach can be extended to other TEF sites with different climatic conditions. Here we evaluated temporal variability in plant functional traits at three different TEF sites using a data-conditioned stochastic parameterization method. We showed that previously studied links—between seasonal photosynthetically active radiation (PAR) and the traits Vcmax25 and leaf longevity—occur across sites. We further determined that seasonal PAR could similarly drive variations in the stomatal conductance slope parameter. Differences found in temporal trait estimates among sites indicate that dynamic trait parameters cannot be applied uniformly over space, but it may be possible to extrapolate them based on climatic factors. Motivated by recent observations that physiological capacity develops as leaves mature, we built new regression models for predicting traits that not only include PAR but also an autoregressive lag term to capture observed physiological delays behind PAR-driven phenology shifts. With our stochastic parameterization, we predicted the three sites to be carbon neutral or carbon sinks under the RCP 8.5 future climate scenario. In contrast, projections using standard static trait parameters show most of the Amazonian TEF region becoming a carbon source. We further approximated that variable traits may allow at least a third of the radiation-limited TEF region in the Amazon to serve as a future net carbon sink.
Bibliographical noteFunding Information:
This study was supported by funding from NSF (NSF-1724781). Supercomputing resources were provided by the Minnesota Supercomputing Institute (MSI) at the University of Minnesota-Twin Cities and the Cheyenne cluster at NCAR. This study utilized data from the TRY initiative on plant traits (http://www.try-db.org). The TRY initiative and database are hosted, developed and maintained by J. Kattge and G. B?nisch (Max Planck Institute for Biogeochemistry, Jena, Germany).
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