4.7 Article

Revealing the scale- and location-specific relationship between soil organic carbon and environmental factors in China's north-south transition zone

Journal

GEODERMA
Volume 409, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.geoderma.2021.115600

Keywords

Environmental factors; Multiple scales; Multiple wavelet coherence; Bivariate wavelet coherence; Soil organic carbon

Categories

Funding

  1. National Natural Science Foun-dation of China [42171112]
  2. National Scientific and Techno-logical Basic Resource Investigation Project [2017FY100900]
  3. Key Research and Development Project in Henan Province [212102310415]
  4. Henan University Postgraduate Talents Project [SYL20060133]

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The study reveals a clear north-south transition effect of SOC in China's transitional zone, with elevation being the strongest single factor explaining SOC variations. By examining soil factors, vegetative factors, climatic factors, topographic factors, and their interactions, it is possible to better predict SOC changes.
The spatial variability of soil organic carbon (SOC) is scale- and location-dependent and controlled by various environmental factors. However, the location- and scale specific factors underpinning SOC variation often demand further investigation. This holds particularly true for topographically complex environments like China's north-south transitional zone. In this paper, wavelet analysis was used to determine the relationship between SOC and environmental factors in the region. The results showed that SOC exhibits an obvious transition effect from north to south, especially at 140 km north of the transect. Elevation was the strongest single factor to explain SOC variations (percent area of significant coherence (PASC) = 25.20%, average wavelet coherence = 0.53 at all scales). Normalized difference vegetation index (NDVI), elevation, land surface temperature (LST) and topographic moisture index (TWI) were the strongest combination of factors explaining variation in SOC (PASC = 43.80%, average wavelet coherence = 0.94 at all scales). Edaphic factors, vegetative factors, climatic factors, topographic factors and their interactions jointly controlled the variation of SOC, and showed increasing predictive power at increasing spatial scales. Our results reveal the spatial sequence changes of SOC and the scalelocation dependencies between SOC and environmental factors in China's north-south transition zone, which can be used for modeling, mapping and management of SOC at different scales.

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