Forests play a major role in the global carbon cycle. Previous studies on the capacity of forests to sequester atmospheric CO2 have mostly focused on carbon uptake, but the roles of carbon turnover time and its spatiotemporal changes remain poorly understood. Here, we used long-term inventory data (1955-2018) from 695 mature forest plots to quantify temporal trends in living vegetation carbon turnover time across tropical, temperate, and cold climate zones, and compared plot data to eight Earth system models (ESMs). Long-term plots consistently showed decreases in living vegetation carbon turnover time, likely driven by increased tree mortality across all major climate zones. Changes in living vegetation carbon turnover time were negatively correlated with CO2 enrichment in both forest plot data and ESM simulations. However, plot-based correlations between living vegetation carbon turnover time and climate drivers such as precipitation and temperature diverged from those of ESM simulations. Our analyses suggest that forest carbon sinks are likely to be constrained by a decrease in living vegetation carbon turnover time, and accurate projections of forest carbon sink dynamics will require an improved representation of tree mortality processes and their sensitivity to climate in ESMs.

Last modified

• 10/29/2024

Creator

• Anderegg, William R.L.
• Schraub, Marcus
• Yu, Kailiang
• Gessler, Arthur
• Penuelas, Josep
• Cailleret, Maxine
• Peng, Changhui
• Condit, Richard
• Ferretti, Marco
• Hubbell, Stephen P.
• Smith, William K.
• Sardans, Jordi
• Levanic, Tom
• Zhu, Kai
• Trugman, Anna T.

Subject

• Forestry

Language

• English

Identifier

• https://doi.org/doi:10.7278/S50D-D656-FSP2

Keyword

• tree mortality
• forest carbon stocks
• carbon turnover
• forest productivity
• cold climate zone
• tropical climate zone
• climate change
• carbon cycle
• temperate climate zone
• earth system models

Date created

• 2018–2019

Resource type

• Dataset

Source

• USGS

License

• CC BY NC - Allows others to use and share your data non-commercially and with attribution.