Temperature Dependence of Plant Photosynthesis at the Global Scale

The Science

An international team of ecologists developed a robust quantitative global model that represents the acclimation and adaptation of the photosynthetic temperature response. The model is capable of predicting observed global variation in the response of photosynthesis to temperature enabling improved prediction of the response of global ecosystems to a warming climate.

The Impact

In order to predict the response of ecosystems to a warming planet it is critical to understand—and model—the response of photosynthesis to temperature. This study used a large global dataset ranging from the Arctic to the tropics to gain critical new understanding, and to develop a model capable of predicting the response of photosynthesis to temperature across the planet.

Summary

To predict the response of ecosystems to a warming planet, it is critical to understand—and represent in models—the response of photosynthesis to temperature. An international research team developed new mathematical functions to represent the photosynthetic temperature response in terrestrial biosphere models (TBMs) to account for both acclimation to growth temperature and adaptation to climate of origin, using a global database that contains more than 140 species. They found acclimation to growth temperature to be the principal driver of the photosynthetic temperature response, and they observed only a few modest effects of adaptation to temperature at the climate of origin. The observed variation of temperature optimum for leaf net photosynthesis was primarily explained by the photosynthetic biochemical component processes rather than stomatal or respiratory processes. The new temperature response functions presented in this study capture the observed temperature optima across biomes with higher degree of accuracy than previously proposed algorithms and span a much larger range of growth temperature.

Principal Investigator

Alistair Rogers
Brookhaven National Laboratory
[email protected]

Program Manager

Daniel Stover
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
[email protected]

Funding

This research was supported by a Western Sydney University Ph.D. scholarship to DK. AR  was supported by the Next-Generation Ecosystem Experiments (NGEE)–Arctic project, which is funded by the Office of Biological and Environmental Research (BER), within the U.S. Department of Energy (DOE) Office of Science, through contract number DE-SC0012704 to Brookhaven National Laboratory (BNL). KYC was supported by an Australian Research Council DECRA (DE160101484). DAW acknowledges a Natural Sciences and Engineering Research Council (NSERC) of Canada Discovery grant and funding from the Hawkesbury Institute Research Exchange Program. JU, LT, and GW were supported by the Swedish strategic research area Biodiversity and Ecosystem Services in a Changing Climate (BECC; www.becc.lu.se). JQC was supported by the NGEE–Tropics project, which is funded by DOE BER. MDK was supported by the Australian Research Council Centre of Excellence for Climate Extremes (CE170100023). MS was supported by an Earl S. Tupper postdoctoral fellowship. AMJ and JMW were supported by DOE BER under Contract No. DEAC05-00OR22725. MAC was supported by DOE grant DE- 705 SC-0011806 and the U.S. Department of Agriculture Forest Service 13-JV-11120101-03. Several of the Eucalyptus datasets included in this study were supported by the Australian Commonwealth Department of the Environment or Department of Agriculture, and the Australian Research Council (including DP140103415).

References