Assessing The Spatiotemporal Variability Of Leaf Functional Traits And Their Drivers Across Multiple Amazon Evergreen Forest Sites: A Stochastic Parameterization Approach With Land-Surface Modeling

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, ) 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 V-cmax25 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.Plain Language Summary We implemented a stochastic approach to evaluate the temporal variability of plant traits parameters at three tropical evergreen forest (TEF) sites in the Amazon. Consistent with previous findings, the maximum rate of carboxylation at 25 degrees C (Vcmax25) and leaf longevity were shown to be correlated with photosynthetically active radiation (PAR). We additionally found the stomatal conductance slope parameter (mp) to co-vary with seasonal PAR. The spatiotemporal differences in Vcmax25, as well as spatial differences in mp, indicated that straightforward spatial extensions of light-controlled parameterizations may not be possible. We built a regression equation to describe trait dynamics that includes not only PAR but also an autoregressive term to represent a time lag. Using the temporally dynamic trait parameters, we predicted the net ecosystem productivity (NEP) to be neutral or positive at the three TEF sites under a future climate scenario. In contrast, projections with standard static trait parameters showed most of the Amazonian TEF region having negative NEP. In addition, we approximated that at least a third of the radiation-limited TEF region in the Amazon could have positive NEP if dynamic traits were considered.