Physiological trait networks enhance understanding of crop growth and water use in contrasting environments

Authors: Gleason, Sean; Barnard, David; Green, Timothy; MACKAY, DAVID - University At Buffalo; WANG, DIANE - Purdue University; Ainsworth, Elizabeth - Lisa; ALTENHOFEN, JON - Northern Colorado Water Conservancy District; Banks, Garrett; BRODRIBB, TIMOTHY - University Of Tasmania; COCHARD, HERVÉ - Inrae; Comas, Louise; COOPER, MARK - University Of Queensland; CREEK, DANIELLE - Inrae; DeJonge, Kendall; DELZON, SYLVAIN - Inrae; FRITSCHI, FELIX - University Of Missouri; HAMMER, GRAEME - University Of Queensland; Hunter, Cameron; LOMBARDOZZI, DANICA - National Center For Atmospheric Research (NCAR); MESSINA, CARLOS - Corteva Agriscience; OCHELTREE, TROY - Colorado State University; Stevens, Bo; STEWART, JARED - US Department Of Agriculture (USDA); VADEZ, VINCENT - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India; Wenz, Joshua; WRIGHT, IAN - Macquarie University; Zhang, Huihui

Submitted to: Plant, Cell & Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/20/2022
Publication Date: 6/23/2022
Citation: Gleason, S.M., Barnard, D.M., Green, T.R., Mackay, D.S., Wang, D.R., Ainsworth, E.A., Altenhofen, J., Banks, G.T., Brodribb, T.J., Cochard, H., Comas, L.H., Cooper, M., Creek, D., DeJonge, K.C., Delzon, S., Fritschi, F.B., Hammer, G., Hunter, C., Lombardozzi, D., Messina, C.D., Ocheltree, T., Stevens, B.M., Stewart, J.J., Vadez, V., Wenz, J.A., Wright, I.J., Zhang, H. 2022. Physiological trait networks enhance understanding of crop growth and water use in contrasting environments. Plant, Cell & Environment. 45(9):2554-2572. https://doi.org/10.1111/pce.14382.
DOI: https://doi.org/10.1111/pce.14382

Interpretive Summary: Plant functioning arises from a complex network of structural and physiological traits (trait "networks"). For example, photosynthesis depends on the uptake (through roots), transport (through xylem), and exchange (through stomata) of water for atmospheric CO2. These coordinated processes are the outcome of closely linked root, xylem, and stomatal traits. In this study we used a plant growth model (the Terrestrial Regional Ecosystem Exchange Simulator; TREES) that was parameterized with measured plant traits relating to water access, water transport, and the exchange of water for CO2. Our goal was to determine if models such as TREES have potential to identify beneficial trait networks in maize grown in contrasting environments. We uncovered two trait networks likely to confer improved performance when water limits plant growth (particularly late-season growth) vs when water is non-limiting. These two trait networks can be understood by their aggregate effect on water use and water conservation. The efficacy of these trait networks arose from climate differences among sites (precipitation amount, precipitation timing, VPD, temperature, and soil texture), aka “envirotype”. This outcome suggests that, although site-specific climates need to be carefully considered when choosing/designing crop species for a given location, that at least in many instances we might expect similar trait networks to improve performance when water limits plant growth versus when it does not.

Technical Abstract: Plant functioning 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 functioning and to predict plant-soil-climate interactions. We used a modified version of the Terrestrial Regional Ecosystem Exchange Simulator (TREES) to evaluate physiological trait networks in maize. Maize net primary productivity (NPP) and grain yield were simulated across five environments with contrasting growing season precipitation, vapor pressure deficit, and temperature. Simulations of high precipitation environments favored (higher NPP & grain yield) trait networks conferring high water use strategies: deep roots (often), high xylem hydraulic conductivity, “risky” stomatal regulation (high stomatal conductance at low leaf water potential), and high maximal leaf area index. In contrast, environments with low late season precipitation (during reproductive development) favored trait networks conferring water conservation: deep roots, high embolism resistance, and “conservative” stomatal regulation (low stomatal conductance at low leaf water potential). As such, the trait networks conferring improved performance in scenarios with high water availability were nearly the opposite of the trait networks conferring improved performance in the dry scenarios. Water conserving trait networks were improved by including traits facilitating fast early season root growth, particularly when deep soil water was available later in the season. Our results indicate that evaluating single traits in isolation of other biologically aligned traits is not an effective strategy for predicting plant performance. Rather, an approach that allows for the evaluation of physiological traits and their interactions (i.e., networks) has potential to improve crop growth predictions in different environments. Such an approach should aim to identify a range of trait combinations contributing to superior yield as well as climate variation among years and among target sites.