Articles | Volume 19, issue 2
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

Data sets

Datasets for Study on Cold Temperature Limitation on GPP in an Evergreen Forest Stephanie Stettz

AmeriFlux BASE US-NR1 Niwot Ridge Forest (LTER NWT1), Ver. 18-5, AmeriFlux AMP Peter D. Blanken, Russel K. Monson, Sean P. Burns, David R. Bowling, and Andrew A. Turnipseed

Model code and software

CARDAMOM code Y. Yang, A. A. Bloom, S. Ma, P. Levine, A. Norton, N. C. Parazoo, J. T. Reager, J. Worden, G. R. Quetin, T. L. Smallman, M. Williams, L. Xu, and S. Saatchi

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.
Final-revised paper