Plant profit maximization improves predictions of European forest responses to drought
© 2020 The Authors. New Phytologist © 2020 New Phytologist Trust.
| Publié dans: | The New phytologist. - 1979. - 226(2020), 6 vom: 16. Juni, Seite 1638-1655 |
|---|---|
| Auteur principal: | |
| Autres auteurs: | , , , , , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2020
|
| Accès à la collection: | The New phytologist |
| Sujets: | Journal Article Research Support, Non-U.S. Gov't canopy gas exchange hydraulic trait adjustments to climate land surface models plant optimality plant profit maximization plant trait coordination vegetation drought responses Water |
| Résumé: | © 2020 The Authors. New Phytologist © 2020 New Phytologist Trust. 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 |
|---|---|
| Description: | Date Completed 14.05.2021 Date Revised 14.05.2021 published: Print-Electronic CommentIn: New Phytol. 2020 Jun;226(6):1535-1538. doi: 10.1111/nph.16548. - PMID 32259286 Citation Status MEDLINE |
| ISSN: | 1469-8137 |
| DOI: | 10.1111/nph.16376 |