Abstract
Stomata mediate fluxes of carbon and water between terrestrial plants and the atmosphere. These fluxes are governed by stomatal function and can be modulated in many Earth system models by an empirical parameter within the calculation of stomatal conductance, the stomatal slope (Formula presented.). Intuitively, (Formula presented.) represents the marginal water cost of carbon, relating it to the emergent plant property of water use efficiency. Observations show that (Formula presented.) can range widely across and within plant types in varying environments, and this distribution of (Formula presented.) is not captured within Earth system models which represent each plant type with a single (Formula presented.) value. Here we examine how (Formula presented.) influences photosynthesis using coupled Earth system model simulations by perturbing (Formula presented.) to observed (Formula presented.) and (Formula presented.) percentiles for each plant type. We find that high (Formula presented.) reduces photosynthesis nearly everywhere, while low (Formula presented.) has regionally dependent responses. Under fixed atmospheric conditions, low (Formula presented.) increases photosynthesis in the Amazon and central North America but decreases photosynthesis in boreal Canada. These responses reverse when the atmosphere responds interactively due to spatially differing sensitivity to increases in temperature and vapor pressure deficit. Choice of (Formula presented.) also influences photosynthetic response to changes in atmospheric carbon dioxide ((Formula presented.)), with lower and higher (Formula presented.) modifying total global response to elevated 2x preindustrial (Formula presented.) by +6.4% and −9.6%, respectively. Our work demonstrates that atmospheric feedbacks are critical for determining the photosynthetic response to (Formula presented.) assumptions and some regions are particularly sensitive to choice of (Formula presented.).
| Original language | English |
|---|---|
| Article number | e2025MS005177 |
| Journal | Journal of Advances in Modeling Earth Systems |
| Volume | 17 |
| Issue number | 11 |
| DOIs | |
| State | Published - Nov 2025 |
Funding
AXL was supported by National Science Foundation Graduate Research Fellowship (DGE‐2140004). CMZ was supported by the U.S. Department of Energy (DOE) Computational Science Graduate Fellowship (DE‐SC0020347). The DOE Office of Biological and Environmental Research Regional and Global Model Analysis (RGMA) Program supported ALSS, AXL, CMZ, BB, CJS, LRH, MH, GJK, ASC, and AEC (DE‐SC0021209). CDK acknowledges support by the DOE BER under contract DE‐AC02‐05Cc11231 through the RGMA Program (RUBISCO SFA) and the NGEE‐Tropics project. This material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the NSF under Cooperative Agreement No. 1852977. We would like to acknowledge high‐performance computing support from Cheyenne ( https://doi.org/10.5065/D6RX99HX ) and data storage resources provided by NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation. We thank all scientists, software engineers, and administrators who contributed to CESM2's development. We thank the editor, associate editor, and three reviewers for their constructive comments that have improved the clarity and content of our manuscript. AXL was supported by National Science Foundation Graduate Research Fellowship (DGE-2140004). CMZ was supported by the U.S. Department of Energy (DOE) Computational Science Graduate Fellowship (DE-SC0020347). The DOE Office of Biological and Environmental Research Regional and Global Model Analysis (RGMA) Program supported ALSS, AXL, CMZ, BB, CJS, LRH, MH, GJK, ASC, and AEC (DE-SC0021209). CDK acknowledges support by the DOE BER under contract DE-AC02-05Cc11231 through the RGMA Program (RUBISCO SFA) and the NGEE-Tropics project. This material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the NSF under Cooperative Agreement No. 1852977. We would like to acknowledge high-performance computing support from Cheyenne (https://doi.org/10.5065/D6RX99HX) and data storage resources provided by NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation. We thank all scientists, software engineers, and administrators who contributed to CESM2's development. We thank the editor, associate editor, and three reviewers for their constructive comments that have improved the clarity and content of our manuscript.
Keywords
- climate modeling
- ecosystem-climate interactions
- photosynthesis
- stomatal conductance
- temperature sensitivity
- water use efficiency