Plant profit maximization improves predictions of European forest responses to drought

Manon E.B. Sabot*, Martin G. De Kauwe, Andy J. Pitman, Belinda E. Medlyn, Anne Verhoef, Anna M. Ukkola, Gab Abramowitz

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

18 Citations (Scopus)

Abstract

Knowledge of how water stress impacts the carbon and water cycles is a key uncertainty in terrestrial biosphere models. We tested a new profit maximization model, where photosynthetic uptake of CO2 is optimally traded against plant hydraulic function, as an alternative to the empirical functions commonly used in models to regulate gas exchange during periods of water stress. We conducted a multi-site evaluation of this model at the ecosystem scale, before and during major droughts in Europe. Additionally, we asked whether the maximum hydraulic conductance in the soil–plant continuum kmax (a key model parameter which is not commonly measured) could be predicted from long-term site climate. Compared with a control model with an empirical soil moisture function, the profit maximization model improved the simulation of evapotranspiration during the growing season, reducing the normalized mean square error by c. 63%, across mesic and xeric sites. We also showed that kmax could be estimated from long-term climate, with improvements in the simulation of evapotranspiration at eight out of the 10 forest sites during drought. Although the generalization of this approach is contingent upon determining kmax, it presents a mechanistic trait-based alternative to regulate canopy gas exchange in global models.

Original languageEnglish
Pages (from-to)1638-1655
Number of pages18
JournalNew Phytologist
Volume226
Issue number6
DOIs
Publication statusPublished - 1 Jun 2020

Bibliographical note

Funding Information:
MEBS, MDK, AJP, AMU, and GA acknowledge support from the Australian Research Council Centre of Excellence for Climate Extremes (CE170100023). MEBS also acknowledges support from the UNSW Scientia PhD Scholarship Scheme. MDK acknowledges support from the ARC Discovery Grant (DP190101823) and the NSW Research Attraction and Acceleration Program. AV acknowledges support from the Natural Environment Research Council grants NE/N012488/1 and NE/L010488/1. This work used eddy covariance data acquired and shared by the FLUXNET community, including the following networks: AmeriFlux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada, GreenGrass, Integrated Carbon Observation System (ICOS), KoFlux, LBA, NECC, OzFlux-TERN, TCOS-Siberia, and USCCC. The ERA-Interim reanalysis data are provided by European Centre for Medium-Range Weather Forecasts and processed by LSCE. The FLUXNET eddy covariance data processing and harmonization was carried out by the European Fluxes Database Cluster, AmeriFlux Management Project and Fluxdata project of FLUXNET, with the support of the Carbon Dioxide Information Analysis Center and the ICOS Ecosystem Thematic Center, and the OzFlux, ChinaFlux, and AsiaFlux offices. We thank Brendan Choat for providing us with additional hydraulic trait data. We are grateful to John Sperry for his thorough comments of an earlier version of this paper?and, finally, we would like to thank Nicolas Martin-StPaul and three anonymous reviewers for their constructive comments.

Funding Information:
MEBS, MDK, AJP, AMU, and GA acknowledge support from the Australian Research Council Centre of Excellence for Climate Extremes (CE170100023). MEBS also acknowledges support from the UNSW Scientia PhD Scholarship Scheme. MDK acknowledges support from the ARC Discovery Grant (DP190101823) and the NSW Research Attraction and Acceleration Program. AV acknowledges support from the Natural Environment Research Council grants NE/N012488/1 and NE/L010488/1. This work used eddy covariance data acquired and shared by the FLUXNET community, including the following networks: AmeriFlux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet‐Canada, GreenGrass, Integrated Carbon Observation System (ICOS), KoFlux, LBA, NECC, OzFlux‐TERN, TCOS‐Siberia, and USCCC. The ERA‐Interim reanalysis data are provided by European Centre for Medium‐Range Weather Forecasts and processed by LSCE. The FLUXNET eddy covariance data processing and harmonization was carried out by the European Fluxes Database Cluster, AmeriFlux Management Project and Fluxdata project of FLUXNET, with the support of the Carbon Dioxide Information Analysis Center and the ICOS Ecosystem Thematic Center, and the OzFlux, ChinaFlux, and AsiaFlux offices. We thank Brendan Choat for providing us with additional hydraulic trait data. We are grateful to John Sperry for his thorough comments of an earlier version of this paper and, finally, we would like to thank Nicolas Martin‐StPaul and three anonymous reviewers for their constructive comments.

Publisher Copyright:
© 2020 The Authors. New Phytologist © 2020 New Phytologist Trust

Keywords

  • canopy gas exchange
  • hydraulic trait adjustments to climate
  • land surface models
  • plant optimality
  • plant profit maximization
  • plant trait coordination
  • vegetation drought responses

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