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PI-Submitted Research Highlights for
Terrestrial Ecosystem Science Program

A Roadmap for Improving the Representation of Photosynthesis in Earth System Models

Alistair Rogers
Brookhaven National Laboratory

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28 November 2016

An identification of the key model development activities, data needs, and improvements in process knowledge required to advance the representation of photosynthesis in next generation models.

The Science
A collaboration between modelers and plant physiologists compared the projected physiological responses of photosynthesis to key environmental drivers in seven terrestrial biosphere models (TBMs) that form the land components of major Earth System Models. The authors make twenty-one recommendations for the activities needed to improve process representation of photosynthesis in TBMs.

The Impact
It is a widely help assumption that the representation of photosynthesis in TBMs is settled science and that model uncertainty is driven largely by other processes downstream of carbon acquisition.  This paper demonstrates that model divergence in the physiological response of photosynthesis to key environmental drivers is high and likely a major source of model divergence.  This is critical because the response of the terrestrial biosphere to global change is driven by these same physiological responses and accurate representation of them should be an essential component of improved TBMs.  The paper lays out the steps needed to improve model representation of photosynthesis.

Summary
Accurate representation of photosynthesis in terrestrial biosphere models (TBMs) is essential for robust projections of global change. However, current representations vary markedly between TBMs, contributing uncertainty to projections of global carbon fluxes. Here we compared the representation of photosynthesis in seven TBMs by examining leaf and canopy level responses of photosynthetic CO2 assimilation (A) to key environmental variables: light, temperature, CO2 concentration, vapor pressure deficit and soil water content. We identified research areas where limited process knowledge prevents inclusion of physiological phenomena in current TBMs and research areas where data are urgently needed for model parameterization or evaluation. We provide a roadmap for new science needed to improve the representation of photosynthesis in the next generation of terrestrial biosphere and Earth system models.

Contacts (BER PM)
Daniel Stover and Jared DeForest
SC-23.1
Daniel.Stover@science.doe.gov (301-903-0289) and Jared.DeForest@science.doe.gov (301-903-1678)

(PI Contact)
Alistair Rogers
Brookhaven National Laboratory
arogers@bnl.gov

Funding
The New Phytologist Trust provided support of the 9th New Phytologist Workshop - Improving representation of photosynthesis in Earth System Models. AR and SPS were supported by the Next-Generation Ecosystem Experiments (NGEE Arctic and NGEE Tropics) projects that are supported by the Office of Biological and Environmental Research in the Department of Energy, Office of Science, and through the United States Department of Energy contract No. DE-SC00112704 to Brookhaven National Laboratory; DW acknowledges support from NSERC, CFI and an Ontario ERA award.  JSD received support from NSF (DEB-0955771).

Publications
Rogers A, Medlyn BE, Dukes JS (2014) Improving representation of photosynthesis in Earth System Models. New Phytologist. 204, 12-14 [DOI: 10.1111/nph.12972]

Rogers A, Medlyn BE, Dukes JS, Bonan G, et al. (2017) A Roadmap for Improving Representation of Photosynthesis in Earth System Models. New Phytologist. 231, 22-42 [DOI: 10.1111/nph.14283]


Summary of the main areas of scientific activity required to advance representation of photosynthesis in Earth system models.  Blue boxes show areas where fundamental research is required to advance understanding prior to incorporation into models.  Yellow boxes show areas where model refinement or development is required to improve process representation.  Green boxes highlight areas where data are needed to parameterize models or are required to evaluate alternative approaches.

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