水保所知识产出(1956---)知识库

Soil respiration (R S ), the soil-to-atmosphere CO 2 flux that is a major compo-
nent of the global carbon cycle, is strongly influenced by local soil temperature
(T soil ) and water content (SWC). Regional to global-scale R S modelling thus
requires this information at local scales, but few high-quality, wall-to-wall
(global) T soil and SWC data exist. As a result, such modelling efforts commonly
use air temperature (T air ) and monthly precipitation (P m ) as surrogate predic-
tors, but their site-scale accuracy and potential bias are unknown. Here, we
used monthly data from 880 sites across a wide variety of different environ-
mental conditions (i.e., climate, ecosystem type, elevation, vegetation leaf habit
and drainage conditions) to determine the suitability of T air as a surrogate for
T soil , and data from 507 sites to examine the suitability of P m as a surrogate for
SWC. Site-specific linear and second-order exponential non-linear models were
compared using model evaluation metrics (i.e., slope, p-value of slope, root
mean square error [RMSE], index of agreement and model efficiency). We
found that T soil and T air are highly correlated and explain similar R S variability.
In contrast, P m is not a good surrogate for SWC, even though P m explains a
similar amount of R S variability to SWC. The wide variability in the site-
specific relationships between R S and SWC means that no single relationship
can be used for large-scale modelling. The results from this study support the
use of T air in continental-to-global scale R S models, and highlight the urgent
need for continental-to-global scale SWC datasets for the modelling and evalu-
ation of future soil carbon dynamics under global climate change.