The Science

Trees adjust their leaf area based on their traits and environmental conditions, which has enormous impacts on global carbon fluxes. A research team from the University of Utah used first principles to predict leaf area adjustment in response to global change.

The Impact

The team provided and tested methods for improving carbon cycle predictions through advancing model predictions of leaf area. Tree‐level carbon allocation to leaves should be derived from first principles using mechanistic plant hydraulic processes in vegetation models.

Summary

Forest leaf area has enormous impacts on the carbon cycle because it mediates both forest productivity and resilience to climate extremes. Trees are capable of adjusting to changes in environment, yet many vegetation models use fixed carbon allocation schemes independent of environment, which introduces uncertainty in predictions. A team of researchers developed an optimization‐based model in which tree carbon allocation to leaves is an emergent property of environment and plant traits. A combination of meta‐analysis, observational datasets, and model predictions show strong evidence that optimal hydraulic–carbon coupling explains observed patterns in leaf allocation.

Principal Investigator

Anna T. Trugman
University of Utah, School of Biological Sciences
a.trugman@utah.edu

Program Manager

Daniel Stover
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
daniel.stover@science.doe.gov

Funding

USDA National Institute of Food and Agriculture, Grant/Award Number: 2018‐ 67012‐28020 and 2018‐67019‐27850; National Science Foundation, Grant/
Award Number: 1714972 and 1802880; German Research Foundation, Grant/Award Number: RU 1657/2‐1, SCHM 2736/2‐1 and YA 274/1‐1 ; David and Lucille Packard Foundation; University of Utah Global Change and Sustainability Center; Next‐ Generation Ecosystem Experiments‐Tropics; Biological and Environmental Research; German Federal Ministry of Education and Research; Helmholtz Association

References