Field-warmed soil carbon changes imply high 21st-century modeling uncertainty
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Published:2018-06-18
Issue:12
Volume:15
Page:3659-3671
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ISSN:1726-4189
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Container-title:Biogeosciences
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language:en
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Short-container-title:Biogeosciences
Author:
Todd-Brown Katherine,Zheng Bin,Crowther Thomas W.
Abstract
Abstract. The feedback between planetary warming and soil carbon loss has been the
focus of considerable scientific attention in recent decades, due to its
potential to accelerate anthropogenic climate change. The soil carbon
temperature sensitivity is traditionally estimated from short-term
respiration measurements – either from laboratory incubations that are
artificially manipulated or from field measurements that cannot distinguish
between plant and microbial respiration. To address these limitations of
previous approaches, we developed a new method to estimate soil temperature
sensitivity (Q10) of soil carbon directly from warming-induced changes
in soil carbon stocks measured in 36 field experiments across the world.
Variations in warming magnitude and control organic carbon percentage
explained much of field-warmed organic carbon percentage
(R2 = 0.96), revealing Q10 across sites of 2.2 [1.6, 2.7]
95 % confidence interval (CI). When these field-derived Q10 values
were extrapolated over the 21st century using a post hoc correction of 20
Coupled Model Intercomparison Project Phase 5 (CMIP5) Earth system model
outputs, the multi-model mean soil carbon stock changes shifted from the
previous value of 88 ± 153 Pg carbon (weighted mean ± 1 SD) to
19 ± 155 Pg carbon with a Q10-driven 95 % CI of
248 ± 191 to −95 ± 209 Pg carbon. On average, incorporating
the field-derived Q10 values into Earth system model simulations led to
reductions in the projected amount of carbon sequestered in the soil over the
21st century. However, the considerable parameter uncertainty led to
extremely high variability in soil carbon stock projections within each
model; intra-model uncertainty driven by the field-derived Q10 was as
great as that between model variation. This study demonstrates that data
integration should capture the variation of the system, as well as mean
trends.
Funder
Pacific Northwest National Laboratory
Publisher
Copernicus GmbH
Subject
Earth-Surface Processes,Ecology, Evolution, Behavior and Systematics
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