Modelling water fluxes in plants : from tissues to biosphere

© 2019 The Authors. New Phytologist © 2019 New Phytologist Trust.

Détails bibliographiques
Publié dans:The New phytologist. - 1984. - 222(2019), 3 vom: 21. Mai, Seite 1207-1222
Auteur principal: Mencuccini, Maurizio (Auteur)
Autres auteurs: Manzoni, Stefano, Christoffersen, Bradley
Format: Article en ligne
Langue:English
Publié: 2019
Accès à la collection:The New phytologist
Sujets:Journal Article Research Support, Non-U.S. Gov't Review hydraulics mechanistic models modelling prediction scaling water relations water transport plus... xylem Water 059QF0KO0R
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520 |a Contents Summary 1207 I. Introduction 1207 II. A brief history of modelling plant water fluxes 1208 III. Main components of plant water transport models 1208 IV. Stand-scale water fluxes and coupling to climate and soil 1213 V. Water fluxes in terrestrial biosphere models and feedbacks to community dynamics 1215 VI. Outstanding challenges in modelling water fluxes in the soil-plant-atmosphere continuum 1217 Acknowledgements 1218 References 1218 SUMMARY: Models of plant water fluxes have evolved from studies focussed on understanding the detailed structure and functioning of specific components of the soil-plant-atmosphere (SPA) continuum to architectures often incorporated inside eco-hydrological and terrestrial biosphere (TB) model schemes. We review here the historical evolution of this field, examine the basic structure of a simplified individual-based model of plant water transport, highlight selected applications for specific ecological problems and conclude by examining outstanding issues requiring further improvements in modelling vegetation water fluxes. We particularly emphasise issues related to the scaling from tissue-level traits to individual-based predictions of water transport, the representation of nonlinear and hysteretic behaviour in soil-xylem hydraulics and the need to incorporate knowledge of hydraulics within broader frameworks of plant ecological strategies and their consequences for predicting community demography and dynamics 
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