Spatial distribution of soil organic carbon and analysis of related factors in croplands of the black soil region, Northeast China

Liu, Dianwei; Wang, Zongming; Zhang, Bai; Song, Kaishan; Li, Xiaoyan; Li, Minglu; Li, Fang; Duan, Hongtao

doi:10.1016/j.agee.2005.09.006

Cited by 297 publications

(155 citation statements)

References 28 publications

Supporting

Mentioning

136

Contrasting

Unclassified

Order By: Relevance

“…After long term reclamation and tillage, the soil quality of the CBNC has deteriorated a lot and this is characterized by the thinning of the soil layer, reduction of organic matter, salinization of soil, soil compaction and severe soil erosion [14,15,17]. In recent years, considerable interests have been paid to the protection of soils in this region [17].…”

Section: Study Site Descriptionsmentioning

confidence: 99%

“…The climate characteristics are very suitable for the growth of corn, which made the CBNC become one of the main granaries of China. But due to soil erosion and intensive land use, serious soil degradation occurs frequently in this region [15]. All this greatly affected crop production and aggravated the vulnerabilities of China's future food security.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Assessment of Soil Quality of Croplands in the Corn Belt of Northeast China

Yang

et al. 2018

Sustainability

Self Cite

View full text Add to dashboard Cite

Abstract:The increasing global demands for land resource with increasing population have resulted in occurrence of soil degradation in many regions of the world. Assessment of soil quality has become the basic work for agricultural sustainable development and selecting regional indicators effectively has become very important since there are no standard evaluation methods and universal indicators. In this study, taking the Corn Belt of Northeast China as the study area, seven indicators-obstacle horizon thickness, cation exchange capacity, pH, soil organic matter, total nitrogen, total potassium, and available Fe-were selected to constitute the minimum data set from sixteen indictors of the total data set to assess the soil quality. The soil quality of the study area was dominated by moderate grade, increasing from west to east. The soil quality of Yushu, Changchun and Shuangyang had higher values, and that of Nongan was the lowest. We found that the distribution of cation exchange capacity has a good consistency with the assessment result of the soil quality. Black soils were distributed in the middle part of the study region from north to south and accounted for a higher quality, exactly where the areas of rapid urbanization are located. An ANOVA analysis showed that soil quality in the Corn Belt of Northeast China was greatly affected by topographic factors and agricultural management and climate was not the principal factor affecting soil quality. Though the minimum data set slightly reduced the evaluation accuracy, a large sampling density in our study was able to improve the precision loss that resulted from reducing the number of indicators to a certain extent.

show abstract

Section: Study Site Descriptionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of Soil Quality of Croplands in the Corn Belt of Northeast China

Yang

et al. 2018

Sustainability

Self Cite

View full text Add to dashboard Cite

show abstract

“…in recent years, interest has grown in studying the spatiotemporal variability of S oM because of its extreme importance in agricultural development and environment health (goovaerts 1998;Sun et al 2003;Liu et al 2006). Changes in SoM are attributable to both natural processes and to human activities (e.g., soil management practices, fertilisation, and crop rotation) (Turner & Lambert 2000;Sun et al 2003) and the importance of human activities has been widely recognised.…”

Section: Introductionmentioning

confidence: 99%

“…The concepts of geostatistics are explained in several textbooks (Cressie 1993;goovaerts 1997;Clark & harper 2000;Webster & oliver 2001). Several studies have specifically examined the spatial variability in SoM using geostatistical techniques and most of them have focused on largescale variability (Mapa & Kumaragamage 1996;Mcgrath & Zhang 2003;Liu et al 2006;huang et al 2007), or on the methodology for studying spatial variability (goovaerts 1998;Sun et al 2003). only a few studies on small-scale areas have been reported (Wang & gong 1998;Sun et al 2003;Wei et al 2006).…”

Section: Introductionmentioning

confidence: 99%

“…a better understanding of the spatiotemporal variability of SOM and related factors is important for refining agricultural management practices and improving sustainable land use (Mcgrath & Zhang 2003). it provides a valuable baseline against which subsequent and future measurements can be evaluated (Liu et al 2006). our primary objectives were to investigate the spatiotemporal variability of farmland SoM in Pinggu district with data from 2 years, 1980 and 2005, using traditional statistics, geostatistics, and a geographic information system at the county scale to provide information for sustainable agricultural development in the region.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Temporal and spatial variability of soil organic matter in a county scale agricultural ecosystem

Yuan

Chai

Gao

et al. 2007

New Zealand Journal of Agricultural Research

View full text Add to dashboard Cite

In agricultural ecosystems, soil organic matter (SOM) is a major determinant and indicator of soil fertility and quality, and is closely related to crop productivity. This paper examines the temporal and spatial variation of SOM in Pinggu district at a county scale using data for 1980 and 2005 and traditional statistics, geostatistics, and geographic information system (GIS) analyses. Pinggu district, Beijing, China is an area characterised by changing farming practices and land uses. A lognormal distribution feature was observed for both datasets, and the difference between them was significant (t-test). The geostatistical characteristics were analysed using a GIS platform. andrelative parameters were developed. The spatial distribution maps for 1980 and 2005 were generally similar, with the SOM content increasing gradually from south-west to north-east. The difference between the two maps was determined using map algebraic functions and was found to show considerable spatial change. Changes in farming practices and land use are thought to be the main reason for the temporal change. Therefore, a combination of geostatistics and GIS map algebra provides a useful tool for examining spatiotemporal changes in the environmental sciences and may detect features that are not discernible when only conventional statistics are used.

show abstract

Variability modeling and mapping of soil properties for improved management in Ethiopia

Tiruneh

Alemayehu

Meshesha

et al. 2023

Agrosystems Geosci & Env

View full text Add to dashboard Cite

Managing soils for improved agricultural production requires information on soil fertility status. Our objective was to map for better soil management in Ethiopia and determine their spatial correlation at a separation distance of 29 m. We collected 82 soil samples (0–20 cm depth) at 560 ha of land and determined pH, Olsen extractable phosphorus (Olsen‐P), and organic carbon (OC). We then interpolated between sample points (ordinary kriging‐OK and distance weighting‐IDW [inverse distance weighting]) to evaluate spatial dependence. Olsen‐P ranged from 2.68–42 mg/kg and exhibited high variability with a coefficient of variation (CV) ≥35%. Conversely, soil pH showed low variability (CV ≤ 15%) and ranging from 4.84 to 6.81. Soil OC content varied from 0.81% to 3.17%. The IDW (R2 = 0.86; RMSE = 0.019) outperformed the OK. The semivariogram results indicate a strong dependence for pH and OC for spherical, exponential, and Gaussian models, while moderately spatially auto correlated for Olsen‐P for all models. The IDW and OK predict the spatial variability of the pH (moderately acidic), Olsen‐P (low), and OC (very low) contents. The soil maps may help to improve soil management alternatives, increase crop productivity, and secure environmental quality.

show abstract

Spatial distribution of soil organic carbon and analysis of related factors in croplands of the black soil region, Northeast China

Cited by 297 publications

References 28 publications

Assessment of Soil Quality of Croplands in the Corn Belt of Northeast China

Assessment of Soil Quality of Croplands in the Corn Belt of Northeast China

Temporal and spatial variability of soil organic matter in a county scale agricultural ecosystem

Variability modeling and mapping of soil properties for improved management in Ethiopia

Contact Info

Product

Resources

About