Preprints
https://doi.org/10.5194/gmd-2021-362
https://doi.org/10.5194/gmd-2021-362
Submitted as: model description paper
20 Dec 2021
Submitted as: model description paper | 20 Dec 2021
Status: a revised version of this preprint is currently under review for the journal GMD.

Forest fluxes and mortality response to drought: model description (ORCHIDEE-CAN-NHA, r7236) and evaluation at the Caxiuanã drought experiment

Yitong Yao1,, Emilie Joetzjer2,, Philippe Ciais1, Nicolas Viovy1, Fabio Cresto Aleina1, Jerome Chave3, Lawren Sack4, Megan Bartlett5, Patrick Meir6, Rosie Fisher7, and Sebastiaan Luyssaert8 Yitong Yao et al.
  • 1Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, 91191, France
  • 2Centre National de Recherche Meteorologique, Unite mixte de recherche 3589 Meteo-France/CNRS, 42 Avenue Gaspard Coriolis, Toulouse, 31100, France
  • 3Laboratoire Evolution et Diversité Biologique UMR 5174 CNRS, IRD, Université Paul Sabatier, Toulouse, 31062, France
  • 4Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California, 90095, USA
  • 5Department of Viticulture & Enology, University of California, Davis, California, 95616, USA
  • 6Research School of Biology, Australian National University, Canberra, ACT 2601 Australia
  • 7CICERO Centre for International Climate and Environmental Research, Oslo, Norway
  • 8Faculty of Science, Vrije Universiteit Amsterdam, Netherlands
  • These authors contributed equally to this work.

Abstract. Extreme drought events in Amazon forests are expected to become more frequent and more intense with climate change, threatening ecosystem function and carbon balance. Yet large uncertainties exist on the resilience of this ecosystem to drought. A better quantification of tree hydraulics and mortality processes is needed to anticipate future drought effects on Amazon forests. Most state-of-the-art dynamic global vegetation models are relatively poor in their mechanistic description of these complex processes. Here, we implement a mechanistic plant hydraulic module within the ORCHIDEE-CAN-NHA r7236 land surface model to simulate the percentage loss of conductance (PLC) and changes in water storage among organs via a representation of the water potentials and vertical water flows along the continuum from soil to roots, stems and leaves. The model was evaluated against observed seasonal variability in stand-scale sap flow, soil moisture and productivity under both control and drought setups at the Caxiuanã throughfall exclusion field experiment in eastern Amazonia between 2001 and 2008. A relationship between PLC and tree mortality is built in the model from two empirical parameters, the cumulated drought exposure duration that triggers mortality, and the mortality fraction in each day exceeding the exposure. Our model captures the large biomass drop in the year 2005 observed four years after throughfall reduction, and produces comparable annual tree mortality rates with observation over the study period. Our hydraulic architecture module provides promising avenues for future research in assimilating experimental data to parameterize mortality due to drought-induced xylem dysfunction. We also highlight that species-based (isohydric or anisohydric) hydraulic traits should be further tested to generalize the model performance in predicting the drought risks.

Yitong Yao et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-362', Anonymous Referee #1, 11 Mar 2022
    • AC1: 'Reply on RC1', Yitong Yao, 29 Jul 2022
  • RC2: 'Comment on gmd-2021-362', Anonymous Referee #2, 01 Apr 2022
    • AC2: 'Reply on RC2', Yitong Yao, 29 Jul 2022

Yitong Yao et al.

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Short summary
To facilitate more mechanistic modeling of drought effects on forest dynamics, our study implements a hydraulic module to simulate the vertical water flow, change in water storage and percentage loss of stem conductance (PLC). With the relationship between PLC and tree mortality, our model can successfully reproduce the large biomass drop observed under throughfall exclusion. Our hydraulic module provides promising avenues benefiting the prediction for mortality under future drought events.