Analysis Synthesizes Global Carbon Research To Refine Future Modeling
- Science Theme:
- Providing Clean Air and Water
- Science Topic
- Estimating and monitoring carbon stocks and greenhouse gas fluxes
Accurately predicting how ecosystems will absorb and release carbon amid changing climatic conditions is an iterative process. Small scale laboratory experiments can lend insights into predictive models that can be tested, verified, or refuted in outdoor settings. As the body of knowledge increases and technological advances allow for wider-scale and more accurate testing, predictive models can continue to be refined and improved.
An international collaborative of researchers, including a scientist with the Northern Research Station, has recently analyzed more than 1,000 large-scale ecosystem studies in an attempt to inform the next iteration of carbon cycling modeling.
Fifty-nine researchers from nine countries conducted a meta-analysis of 1,119 experiments conducted on four major terrestrial ecosystem types: forests, grasslands, wetlands, and deserts. Meta-analysis is a statistical method of isolating variables across different experiments to make statistically reliable comparisons and conclusions.
While the individual experiments themselves might have been manipulating variables such as temperature, precipitation, or nitrogen deposition, all the experiments had components measuring how these variables influenced the absorption or release of carbon. The studies also had to be at least three years in duration and occur in an unmanaged outdoor ecosystem within one of the four major terrestrial ecosystem types.
Results supported an expected pattern of increased temperatures, precipitation, concentrated levels of atmospheric carbon dioxide, and nitrogen deposition correlating with increased rates of carbon processing aboveground. Belowground, the absorption of carbon by roots decreased with increased precipitation and nitrogen deposition, but increased under drier conditions and elevated levels of atmospheric carbon dioxide.
More important than the trend of results was the quantitative effects measured. These measurements will be used by modelers to refine the predicted effects of various climatic changes or conditions. It also helps establish the upper limits of expected carbon outputs, as these changes aren’t infinite. The end result is a better understanding of how terrestrial ecosystems are responding to changing climatic conditions, which hopefully will lead to more accurate computer modeling to help land managers anticipate and mitigate effects.
Song, Jian; Wan, Shiqiang; Piao, Shilong; Knapp, Alan K.; Classen, Aimée T.; Vicca, Sara; Ciais, Philippe; Hovenden, Mark J.; Leuzinger, Sebastian; Beier, Claus; Kardol, Paul; Xia, Jianyang; Liu, Qiang; Ru, Jingyi; Zhou, Zhenxing; Luo, Yiqi; Guo, Dali; Adam Langley, J.; Zscheischler, Jakob; Dukes, Jeffrey S.; Tang, Jianwu; Chen, Jiquan; Hofmockel, Kirsten S.; Kueppers, Lara M.; Rustad, Lindsey; Liu, Lingli; Smith, Melinda D.; Templer, Pamela H.; Quinn Thomas, R.; Norby, Richard J.; Phillips, Richard P.; Niu, Shuli; Fatichi, Simone; Wang, Yingping; Shao, Pengshuai; Han, Hongyan; Wang, Dandan; Lei, Lingjie; Wang, Jiali; Li, Xiaona; Zhang, Qian; Li, Xiaoming; Su, Fanglong; Liu, Bin; Yang, Fan; Ma, Gaigai; Li, Guoyong; Liu, Yanchun; Liu, Yinzhan; Yang, Zhongling; Zhang, Kesheng; Miao, Yuan; Hu, Mengjun; Yan, Chuang; Zhang, Ang; Zhong, Mingxing; Hui, Yan; Li, Ying; Zheng, Mengmei. 2019. A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change. Nature Ecology & Evolution. 3(9): 1309-1320. https://doi.org/10.1038/s41559-019-0958-3.
Vicca, S.; Bahn, M.; Estiarte, M.; van Loon, E. E.; Vargas, R.; Alberti, G.; Ambus, P.; Arain, M. A.; Beier, C.; Bentley, L. P.; Borken, W.; Buchmann, N.; Collins, S. L.; de Dato, G.; Dukes, J. S.; Escolar, C.; Fay, P.; Guidolotti, G.; Hanson, P. J.; Kahmen, A.; Kröel-Dulay, G.; Ladreiter-Knauss, T.; Larsen, K. S.; Lellei-Kovacs, E.; Lebrija-Trejos, E.; Maestre, F. T.; Marhan, S.; Marshall, M.; Meir, P.; Miao, Y.; Muhr, J.; Niklaus, P. A.; Ogaya, R.; Peñuelas, J.; Poll, C.; Rustad, L. E.; Savage, K.; Schindlbacher, A.; Schmidt, I. K.; Smith, A. R.; Sotta, E. D.; Suseela, V.; Tietema, A.; van Gestel, N.; van Straaten, O.; Wan, S.; Weber, U.; Janssens, I. A. 2014. Can current moisture responses predict soil CO2 efflux under altered precipitation regimes? A synthesis of manipulation experiments. Biogeosciences. 11(11): 2991-3013. https://doi.org/10.5194/bg-11-2991-2014.
- Lindsey Rustad, USDA Forest Service Northern Research Station, Research Ecologist
- Auckland University of Technology (New Zealand)
- Binzhou University (China)
- Boston University Chinese Academy of Social Sciences (China)
- Colorado State University
- Commonwealth Scientific and Industrial Research Organization (Australia)
- Duke University
- East China Normal University (China)
- Hebei University (China)
- Henan University (China)
- Indiana University
- Last modified: January 5, 2021