Drought-Induced Carbon Allocation Shifts Decrease Legacy Carbon Uptake in French Guiana
Matthew Albert Worden, Stanford University, mworden@stanford.edu (Presenter)
Caroline Alexa Famiglietti, Stanford University, cfamigli@stanford.edu
Paul A Levine, JPL, paul.a.levine@jpl.nasa.gov
Shuang Ma, Jet Propulsion Laboratory / Caltech, shuang.ma@jpl.nasa.gov
Alexis Anthony Bloom, Jet Propulsion Lab, California Institute of Technology, abloom@jpl.nasa.gov
Damien Bonal, INRAE, damien.bonal@inrae.fr
Clément Stahl, UMR EcoFoG, clement.stahl@ecofog.gf
Alexandra G Konings, Stanford University, konings@stanford.edu
Drought not only cause instantaneous reductions in carbon uptake but can also have long-lasting effects on carbon fluxes through drought-induced changes to leaf area, root water uptake capacity, and soil carbon pools. Carbon allocation shifts have been suggested as one of many factors contributing to the legacy effects of drought on carbon fluxes, alongside other influences such as pest infestations and tree mortality due to hydraulic failure. However, the magnitude and impact of these allocation shifts on carbon fluxes and pools remain poorly understood. This is compounded by the fact that such shifts are difficult to measure in situ. In this study, we used data from a wet tropical flux tower site in French Guiana (Guyaflux) to first demonstrate that drought-induced carbon allocation shifts can be reliably inferred through assimilation of Net Biome Exchange (NBE) observations and other data streams in a carbon cycle model-data fusion system. We then investigated how these shifts influenced the duration and magnitude of drought's effects on NBE during and after drought. To do this, we integrated a dynamic carbon allocation scheme into the CArbon DAta MOdel fraMework (CARDAMOM) data assimilation system, which optimizes parameters and carbon cycle states based on multiple observational data streams of carbon fluxes and pools. To examine drought effects, we ran simulations of our constrained model with drought meteorology replaced by its climatological average. Our results showed that, compared to a static allocation scheme such as those typically implemented in land surface models, dynamic allocation increases average recovery magnitude by approximately a factor of 2 [1.13 (25th %) - 2.9 (75th %)]. Additionally, the dynamic model extended the average recovery time by approximately 6 months [3 (25th %) - 9 (75th %)]. The allocation shifts derived from our study influenced the post-drought period by altering foliage and fine root pools, which subsequently modulate gross primary productivity and heterotrophic respiration for up to 10 years following the drought event.
Poster: Poster_Worden_1-53_88_35.pdf
Associated Project(s):
Poster Location ID: 1-53
Presentation Type: Poster
Session: Poster Session 1
Session Date: Tue (May 9) 5:00-7:00 PM
CCE Program: TE