Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

© 2017, Springer International Publishing AG, part of Springer Nature. Tropical forests are the most carbon (C)-rich ecosystems on Earth, containing 25–40% of global terrestrial C stocks. While large-scale quantification of aboveground biomass in tropical forests has improved recently, soil C dynamics remain one of the largest sources of uncertainty in Earth system models, which inhibits our ability to predict future climate. Globally, soil texture and climate predict ≤ 30% of the variation in soil C stocks, so ecosystem models often predict soil C using measures of aboveground plant growth. However, this approach can underestimate tropical soil C stocks, and has proven inaccurate when compared with data for soil C in data-rich northern ecosystems. By quantifying soil organic C stocks to 1 m depth for 48 humid tropical forest plots across gradients of rainfall and soil fertility in Panama, we show that soil C does not correlate with common predictors used in models, such as plant biomass or litter production. Instead, a structural equation model including base cations, soil clay content, and rainfall as exogenous factors and root biomass as an endogenous factor predicted nearly 50% of the variation in tropical soil C stocks, indicating a strong indirect effect of base cation availability on tropical soil C storage. Including soil base cations in C cycle models, and thus emphasizing mechanistic links among nutrients, root biomass, and soil C stocks, will improve prediction of climate-soil feedbacks in tropical forests.

Original publication

DOI

10.1007/s10533-017-0416-8

Type

Journal article

Journal

Biogeochemistry

Publication Date

01/01/2018

Volume

137

Pages

253 - 266