AI Article Synopsis

  • - This study focuses on how elevated atmospheric CO levels (eCO) affect plant carbon assimilation and water usage, impacting global carbon and water cycles.
  • - Researchers use a land surface model called QUINCY to simulate the effects of increasing CO on plant physiology and to develop a statistical method for detecting these effects amid natural variations in ecosystems.
  • - Findings show that eCO effects on carbon productivity can be detected at lower CO increases compared to their effects on water use, with stronger signals in forest ecosystems than in grasslands, providing insight for future observational studies.

Article Abstract

Elevated atmospheric CO (eCO ) influences the carbon assimilation rate and stomatal conductance of plants, thereby affecting the global cycles of carbon and water. Yet, the detection of these physiological effects of eCO in observational data remains challenging, because natural variations and confounding factors (e.g., warming) can overshadow the eCO effects in observational data of real-world ecosystems. In this study, we aim at developing a method to detect the emergence of the physiological CO effects on various variables related to carbon and water fluxes. We mimic the observational setting in ecosystems using a comprehensive process-based land surface model QUINCY to simulate the leaf-level effects of increasing atmospheric CO concentrations and their century-long propagation through the terrestrial carbon and water cycles across different climate regimes and biomes. We then develop a statistical method based on the signal-to-noise ratio to detect the emergence of the eCO effects. The eCO effect on gross primary productivity (GPP) emerges at relatively low CO increase (∆[CO ] ~ 20 ppm) where the leaf area index is relatively high. Compared to GPP, the eCO effect causing reduced transpiration water flux (normalized to leaf area) emerges only at relatively high CO increase (∆[CO ] >> 40 ppm), due to the high sensitivity to climate variability and thus lower signal-to-noise ratio. In general, the response to eCO is detectable earlier for variables related to the carbon cycle than the water cycle, when plant productivity is not limited by climatic constraints, and stronger in forest-dominated rather than in grass-dominated ecosystems. Our results provide a step toward when and where we expect to detect physiological CO effects in in-situ flux measurements, how to detect them and encourage future efforts to improve the understanding and quantification of these effects in observations of terrestrial carbon and water dynamics.

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http://dx.doi.org/10.1111/gcb.16397DOI Listing

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