| 其他摘要 | With the increasing concern of the ecological environmental problems, carbon
related scientific questions have been becoming the research focus of scientists all over
the world. As the biggest carbon pool on the terrestrial ecosystem, soil carbon pool is a
main research field for soil scientists. For an accurate estimation of soil carbon storage, it
is critical to understand soil carbon spatial variation at a specific scale. The Loess Plateau
of China is characterized for its diverse landforms induced by serious soil erosion. It is a
challenging work to estimate soil carbon storage on the Loess Plateau, especially the soil
carbon storage in farmland with a mosaic distribution on the region. So far, most
researches on soil carbon spatial variability were focused on field and small watershed
scale on the Loess Plateau. Fresh work has been done on regional scale as well as
different scales. In this thesis soil carbon spatial variability at regional scale and county
scale on the Loess Plateau were studied using a geo-statistics method combined with
Geographic Information System (GIS).The main content of the thesis include the spatial
variability of soil organic carbon and its influencing factors, a reasonable number of
samples and differences of sampling methods about organic carbon, which may provide a
scientific basis for the calculation model of organic carbon storage and accurately
understanding the current situation of farmland soil organic matter and nutrient for
agricultural departments. The main conclusions are as following:
(1) Variability of soil organic carbon had scale effect in different scales and different landscape types on the Loess Plateau, and the scale effect was obvious
about the SOC and coefficient variation in Loess Hilly Region. The SOC in the Plains
was the highest, followed by Plateau Area and the Loess Hilly Region on regional scale,
but the variation of SOC was in contrast. On the country scale, the highest of SOC was in
the Plains, followed by the Loess Hilly Region and Plateau Area, and the order of
variation was the Plains, the Plateau Area and the Loess Hilly Region. The
representativeness of SOC in Zhuanglang county was relatively poor in the Loess Hilly
Region, and the other two areas were representative. On the whole, the study area
correlation distance shown that the greater area, greater distance. The SOC have showed
a strongly spatial self-relativity either country scale or regional scale in the Loess Hilly
Region; Randomness were strengthened with increased the area in the plains, while
showed nugget effect in Plateau Area.
(2) The rule about contribution of different factors to SOC variation on the
Loess Plateau was as follows: Main influencing factors for SOC on regional scale
was complex and covered the country scale in the same landforms except the plains.
On regional scale, soil erosion degree could explain 29.7% of variability, soil type 26.3%
and altitude 29.6% in the Loess Hilly Region; Cropping system could explain 57.4% of
variability, soil type 15.3% and soil texture 12.3% in the Plains; Soil texture could
explain 66.6% of variability, field surface slope 16.7% and Aspect 16.7% in Plateau Area.
On the country scale, altitude could explain 86.5% of variability, soil type 13.5% in the
Loess Hilly Region; Cropping system could explain 51.2% of variability, altitude 29.9%
in the plains; No influencing factors was noted in Plateau Area.
(3) The results indicated that main influencing factors for the SOC variation
were altitude and soil type in Zhuanglang county, and difference about SOC
variability was significant in different scales and different landscape types in Loess
Hilly Region. There are statistically significant differences in every increase of 200m
elevation group. Dark loessial soils, red clay soils and Cultivated loessial soils had a
statistically significant effect on SOC. The impact of natural factor on the variance of
SOC did not significantly change in high mountain region, and the others had obvious
scale effect. With the narrowing of spatial scale, SOC variation effect of altitude and soil
type began to lessen. In gully region, all the factors were not significant between the complete geomorphic units and the town scale. In the hilly region, the main factors were
the altitude and the soil type in the complete geomorphic unit scale, but in town scale
was the slope gradient of field surface. In the high mountain region, the main controlling
factor was soil type in the geomorphic unit scale, but the town scale was the soil erosion
degree.
(4) Classical statistics and Geostatistics were different in sampling. The
reasonable sampling number in combine unit stationing was less than the random
smooth stationing. It showed fully representativeness among different sample sizes
and the uncertainty of combine unit stationing was slightly larger than the random
smooth stationing. Classical statistics showed reasonable sampling number was 64 in
random smooth stationing and 61 in combine unit stationing, which expressed the
smaller difference. Based on the Geostatistics, we concluded that reasonable sampling
number of SOC was respectively about 903 and 454 in random smooth stationing and
combine unit stationing , which had great difference. Consequently, both combine unit
stationing and random smooth stationing can be applied when studied the overall trend
and characteristics by classical statistics, and the combine unit stationing was best when
studied precision distribution of nutrient by Geostatistics.
Keywords: the Loess Plateau, farmland soil organic carbon, spatial variation,
scale effect, uncertainty |
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