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Predicting soil carbon loss with warning

Citation

van Gestel, N and Shi, Z and van Groenigen, KJ and Osenberg, CW and Andresen, LC and Dukes, JS and Hovenden, MJ and Luo, Y and Michelsen, A and Pendall, E and Reich, PB and Schuur, EAG and Hungate, BA, Predicting soil carbon loss with warning, Nature, 554 pp. 104-108. ISSN 0028-0836 (2018) [Refereed Article]

Copyright Statement

Copyright 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.

Official URL: https://www.nature.com/articles/nature25745

DOI: doi:10.1038/nature25745

Abstract

Crowther et al. reported that the best predictor of surface soil carbon (top 10 cm) losses in response to warming is the size of the surface carbon stock in the soil (that is, carbon stocks in plots that have not been warmed), finding that soils that are high in soil carbon also lose more carbon under warming conditions. This relationship was based on a linear regression of soil carbon losses and soil carbon stocks in field warming studies, which was then used to project carbon losses over time and to generate a map of soil carbon vulnerability. However, a few extreme data points (high-leverage points) can strongly influence the slope of a regression line. Only 5 of the 49 sites analysed by Crowther et al.1 are in the upper half of the carbon stock range, which raises the possibility that the relationship they observed could be substantially altered by introducing data from sites with relatively high surface soil carbon stocks. There is a Reply to this Comment by Crowther, T. W. et al. Nature 554, 10.1038/nature25746 (2018).

Item Details

Item Type:Refereed Article
Keywords:soil, carbon, warming, global warming, global change, climate change
Research Division:Biological Sciences
Research Group:Other Biological Sciences
Research Field:Global Change Biology
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in the Environmental Sciences
UTAS Author:Hovenden, MJ (Associate Professor Mark Hovenden)
ID Code:124608
Year Published:2018
Funding Support:Australian Research Council (DP0984779)
Web of Science® Times Cited:11
Deposited By:Plant Science
Deposited On:2018-02-28
Last Modified:2019-02-28
Downloads:0

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