Global photosynthetic capacity jointly determined by enzyme kinetics and eco-evo-environmental drivers

Simple item page
dc.creatorYan, Zhengbing
dc.creatorDetto, Matteo
dc.creatorGuo, Zhengfei
dc.creatorSmith, Nicholas G. (TTU)
dc.creatorWang, Han
dc.creatorAlbert, Loren P.
dc.creatorXu, Xiangtao
dc.creatorLin, Ziyu
dc.creatorLiu, Shuwen
dc.creatorZhao, Yingyi
dc.creatorChen, Shuli
dc.creatorBonebrake, Timothy C.
dc.creatorWu, Jin
dc.date.accessioned2024-03-18T18:46:07Z
dc.date.available2024-03-18T18:46:07Z
dc.date.issued2024
dc.description© 2024 cc-by
dc.description.abstractAccurate understanding of global photosynthetic capacity (i.e. maximum RuBisCO carboxylation rate, Vc, max) variability is critical for improved simulations of terrestrial ecosystem photosynthesis metabolisms and carbon cycles with climate change, but a holistic understanding and assessment remains lacking. Here we hypothesized that Vc, max was dictated by both factors of temperature-associated enzyme kinetics (capturing instantaneous ecophysiological responses) and the amount of activated RuBisCO (indexed by Vc, max standardized at 25 ℃, Vc, max25), and compiled a comprehensive global dataset (n = 7339 observations from 428 sites) for hypothesis testing. The photosynthesis data were derived from leaf gas exchange measurements using portable gas exchange systems. We found that a semi-empirical statistical model considering both factors explained 78% of global Vc, max variability, followed by 55% explained by enzyme kinetics alone. This statistical model outperformed the current theoretical optimality model for predicting global Vc, max variability (67%), primarily due to its poor characterization on global Vc, max25 variability (3%). Further, we demonstrated that, in addition to climatic variables, belowground resource constraint on photosynthetic machinery built-up that directly structures the biogeography of Vc, max25 was a key missing mechanism for improving the theoretical modelling of global Vc, max variability. These findings improve the mechanistic understanding of global Vc, max variability and provide an important basis to benchmark process-based models of terrestrial photosynthesis and carbon cycling under climate change.
dc.identifier.citationYan, Z., Detto, M., Guo, Z., Smith, N.G., Wang, H., Albert, L.P., Xu, X., Lin, Z., Liu, S., Zhao, Y., Chen, S., Bonebrake, T.C., & Wu, J.. 2024. Global photosynthetic capacity jointly determined by enzyme kinetics and eco-evo-environmental drivers. Fundamental Research. https://doi.org/10.1016/j.fmre.2023.12.011
dc.identifier.urihttps://doi.org/10.1016/j.fmre.2023.12.011
dc.identifier.urihttps://hdl.handle.net/2346/97751
dc.language.isoeng
dc.subjectBelowground resource constraint
dc.subjectClimate
dc.subjectEco-evolutionary optimality
dc.subjectEcophysiology
dc.subjectEnzyme kinetics
dc.subjectGlobal carbon cycling
dc.subjectLeaf photosynthetic capacity
dc.subjectLeaf traits
dc.titleGlobal photosynthetic capacity jointly determined by enzyme kinetics and eco-evo-environmental drivers
dc.typeArticle

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
smith_article.pdf
Size:
2.45 MB
Format:
Adobe Portable Document Format
Description:
Main article with TTU Libraries cover page
Download

Collections

Faculty Research