Articles | Volume 19, issue 2
https://doi.org/10.5194/bg-19-541-2022
https://doi.org/10.5194/bg-19-541-2022
Research article
 | 
28 Jan 2022
Research article |  | 28 Jan 2022

Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model–data fusion framework

Stephanie G. Stettz, Nicholas C. Parazoo, A. Anthony Bloom, Peter D. Blanken, David R. Bowling, Sean P. Burns, Cédric Bacour, Fabienne Maignan, Brett Raczka, Alexander J. Norton, Ian Baker, Mathew Williams, Mingjie Shi, Yongguang Zhang, and Bo Qiu

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Latest update: 25 Feb 2024
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Short summary
Uncertainty in the response of photosynthesis to temperature poses a major challenge to predicting the response of forests to climate change. In this paper, we study how photosynthesis in a mountainous evergreen forest is limited by temperature. This study highlights that cold temperature is a key factor that controls spring photosynthesis. Including the cold-temperature limitation in an ecosystem model improved its ability to simulate spring photosynthesis.
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