1. Physiological trait networks enhance understanding of crop growth and water use in contrasting environments
- Author
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Sean M. Gleason, Dave M. Barnard, Timothy R. Green, Scott Mackay, Diane R. Wang, Elizabeth A. Ainsworth, Jon Altenhofen, Timothy J. Brodribb, Hervé Cochard, Louise H. Comas, Mark Cooper, Danielle Creek, Kendall C. DeJonge, Sylvain Delzon, Felix B. Fritschi, Graeme Hammer, Cameron Hunter, Danica Lombardozzi, Carlos D. Messina, Troy Ocheltree, Bo Maxwell Stevens, Jared J. Stewart, Vincent Vadez, Joshua Wenz, Ian J. Wright, Kevin Yemoto, Huihui Zhang, Water Management and Systems Research (WMSR), United States Department of Agriculture (USDA), University at Buffalo [SUNY] (SUNY Buffalo), State University of New York (SUNY), Purdue University [West Lafayette], University of Tasmania [Hobart, Australia] (UTAS), Laboratoire de Physique et Physiologie Intégratives de l’Arbre en environnement Fluctuant (PIAF), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Clermont Auvergne (UCA), Queensland Alliance for Agriculture and Food Innovation (QAAFI), University of Queensland [Brisbane], Biodiversité, Gènes & Communautés (BioGeCo), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of Missouri [Columbia] (Mizzou), University of Missouri System, Colorado State University [Fort Collins] (CSU), National Center for Atmospheric Research [Boulder] (NCAR), University of Florida [Gainesville] (UF), International Crops Research Institute for the Semi-Arid Tropics [Inde] (ICRISAT), Consultative Group on International Agricultural Research [CGIAR] (CGIAR), and Macquarie University
- Subjects
photosynthesis ,Physiology ,stomata ,Water ,food and beverages ,Plant Science ,plant growth ,xylem ,maize ,process simulation ,crop improvement ,Droughts ,Plant Leaves ,Soil ,breeding ,Plant Stomata ,hydraulic traits ,[SDE]Environmental Sciences ,water potential ,Edible Grain ,Ecosystem - Abstract
Plant function arises from a complex network of structural and physiological traits. Explicit representation of these traits, as well as their connections with other biophysical processes, is required to advance our understanding of plant-soil-climate interactions. We used the Terrestrial Regional Ecosystem Exchange Simulator (TREES) to evaluate physiological trait networks in maize. Net primary productivity (NPP) and grain yield were simulated across five contrasting climate scenarios. Simulations achieving high NPP and grain yield in high precipitation environments featured trait networks conferring high water use strategies: deep roots, high stomatal conductance at low water potential (“risky” stomatal regulation), high xylem hydraulic conductivity, and high maximal leaf area index. In contrast, high NPP and grain yield was achieved in dry environments with low late-season precipitation via water conserving trait networks: deep roots, high embolism resistance, and low stomatal conductance at low leaf water potential (“conservative” stomatal regulation). We suggest that our approach, which allows for the simultaneous evaluation of physiological traits and their interactions (i.e., networks), has potential to improve crop growth predictions in different environments. In contrast, evaluating single traits in isolation of other coordinated traits does not appear to be an effective strategy for predicting plant performance.Summary statementOur process-based model uncovered two beneficial but contrasting trait networks for maize which can be understood by their integrated effect on water use/conservation. Modification of multiple, physiologically aligned, traits were required to bring about meaningful improvements in NPP and yield.
- Published
- 2022