 |
| Titel |
Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks |
| VerfasserIn |
U. Mishra, W. J. Riley |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1726-4170
|
| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 12, no. 13 ; Nr. 12, no. 13 (2015-07-02), S.3993-4004 |
| Datensatznummer |
250118008
|
| Publikation (Nr.) |
 copernicus.org/bg-12-3993-2015.pdf |
|
|
|
|
|
| Zusammenfassung |
| The spatial heterogeneity of land surfaces affects energy, moisture, and
greenhouse gas exchanges with the atmosphere. However, representing the
heterogeneity of terrestrial hydrological and biogeochemical processes in
Earth system models (ESMs) remains a critical scientific challenge. We
report the impact of spatial scaling on environmental controls, spatial
structure, and statistical properties of soil organic carbon (SOC) stocks
across the US state of Alaska. We used soil profile observations and
environmental factors such as topography, climate, land cover types, and
surficial geology to predict the SOC stocks at a 50 m spatial scale.
These spatially heterogeneous estimates provide a data set with reasonable
fidelity to the observations at a sufficiently high resolution to examine
the environmental controls on the spatial structure of SOC stocks. We
upscaled both the predicted SOC stocks and environmental variables from
finer to coarser spatial scales (s = 100, 200, and 500 m and 1, 2, 5, and
10 km) and generated various statistical properties of SOC stock estimates.
We found different environmental factors to be statistically significant
predictors at different spatial scales. Only elevation, temperature,
potential evapotranspiration, and scrub land cover types were significant
predictors at all scales. The strengths of control (the median value of
geographically weighted regression coefficients) of these four environmental
variables on SOC stocks decreased with increasing scale and were accurately
represented using mathematical functions (R2 = 0.83–0.97). The spatial
structure of SOC stocks across Alaska changed with spatial scale. Although
the variance (sill) and unstructured variability (nugget) of the calculated
variograms of SOC stocks decreased exponentially with scale, the correlation
length (range) remained relatively constant across scale. The variance of
predicted SOC stocks decreased with spatial scale over the range of 50 m to
~ 500 m, and remained constant beyond this scale. The fitted
exponential function accounted for 98 % of variability in the variance of
SOC stocks. We found moderately accurate linear relationships between mean
and higher-order moments of predicted SOC stocks (R2 ∼ 0.55–0.63).
Current ESMs operate at coarse spatial scales (50–100 km), and
are therefore unable to represent environmental controllers and spatial
heterogeneity of high-latitude SOC stocks consistent with observations. We
conclude that improved understanding of the scaling behavior of
environmental controls and statistical properties of SOC stocks could
improve ESM land model benchmarking and perhaps allow representation of
spatial heterogeneity of biogeochemistry at scales finer than those
currently resolved by ESMs. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|