Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Global photosynthetic capacity is optimized to the environment

Loading...
Thumbnail Image

Authors

Smith, Nicholas G.
Keenan, Trevor
Prentice, I. Colin
Wang, Han
Wright, Ian J.
Niinemets, U.
Crous, Kristine Y.
Domingues, Tomas F.
Guerrieri, Rossella
Ishida, F. Yoko

Journal Title

Journal ISSN

Volume Title

Publisher

Blackwell Publishing Ltd

Abstract

Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (Vcmax), to simulate carbon assimilation and typically rely on empirical estimates, including an assumed dependence on leaf nitrogen determined from soil fertility. In contrast, new theory, based on biochemical coordination and co‐optimization of carboxylation and water costs for photosynthesis, suggests that optimal Vcmax can be predicted from climate alone, irrespective of soil fertility. Here, we develop this theory and find it captures 64% of observed variability in a global, field‐measured Vcmax dataset for C3 plants. Soil fertility indices explained substantially less variation (32%). These results indicate that environmentally regulated biophysical constraints and light availability are the first‐order drivers of global photosynthetic capacity. Through acclimation and adaptation, plants efficiently utilize resources at the leaf level, thus maximizing potential resource use for growth and reproduction. Our theory offers a robust strategy for dynamically predicting photosynthetic capacity in ESMs.

Description

Citation

Source

Ecology Letters

Book Title

Entity type

Access Statement

Open Access

License Rights

Creative Commons License Attribution 4.0 International (CC BY 4.0)

Restricted until