Temporal and spatial variability of soil organic matter and total nitrogen in an agricultural ecosystem as affected by farming practices

Huang, Biao; Sun, Weixia; Zhao, Yongcun; Zhu, Jing; Yang, Rongqing; Zhong, Zhijun; Ding, Feng; Su, Jianping

doi:10.1016/j.geoderma.2007.02.012

Cited by 186 publications

(132 citation statements)

References 44 publications

(62 reference statements)

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“…Quantifying the effect of land management strategies on dynamic soil properties is complicated by the natural complexity of soil across space (Robertson et al 1993;Heuvelink and Webster 2001;Lin et al 2005;Huang et al 2007) and time. This study aims to build on previous efforts to address soil fertility constraints in African smallholder systems by applying a spatially balanced sampling design that accounts for landscape variability in SOC in order to assess the impacts of cultivation on SOC in the WUM of Tanzania.…”

Section: Introductionmentioning

confidence: 99%

Landscape-scale variability of soil health indicators: effects of cultivation on soil organic carbon in the Usambara Mountains of Tanzania

Winowiecki

Vågen

Massawe

et al. 2015

Nutr Cycl Agroecosyst

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Land-use change continues at an alarming rate in sub-Saharan Africa adversely affecting ecosystem services provided by soil. These impacts are greatly understudied, especially in biodiversity rich mountains in East Africa. The objectives of this study were to: conduct a biophysical baseline of soil and land health; assess the effects of cultivation on soil organic carbon (SOC); and develop a map of SOC at high resolution to enable farm-scale targeting of management interventions. Biophysical field surveys were conducted in a 100 km 2 landscape near Lushoto, Tanzania, with composite soil samples collected from 160 sampling plots. Soil erosion prevalence was scored, trees were counted, and current and historic land use was recorded at each plot. The results of the study showed a decline in SOC as a result of cultivation, with cultivated plots (n = 105) having mean topsoil OC of 30.6 g kg -1 , while semi-natural plots (n = 55) had 71 g OC kg -1 in topsoil. Cultivated areas were also less variable in SOC than seminatural systems. Prediction models were developed for the mapping of SOC based on RapidEye remote sensing data for January 2014, with good model performance (RMSEP cal = 8.0 g kg -1 ; RMSEP val = 10.5 g kg -1 ) and a SOC map was generated for the study. Interventions will need to focus on practices that increase SOC in order to enhance productivity and resilience of the farming system, in general. The highresolution maps can be used to spatially target interventions as well as for monitoring of changes in SOC.

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Section: Introductionmentioning

confidence: 99%

Landscape-scale variability of soil health indicators: effects of cultivation on soil organic carbon in the Usambara Mountains of Tanzania

Winowiecki

Vågen

Massawe

et al. 2015

Nutr Cycl Agroecosyst

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“…Positive effects of human activities on soil quality Incorporation of crop residues usually improves SOM and TN directly, and induces accumulation of C and N (Rasmussen & Parton 1994;Fischer et al 2002;Karlen et al 2006;Raiesi 2006;Huang et al 2007). Land use change from dry land to rice paddies also usually improves soil quality (Bhandari et al 2002).…”

Section: Discussionmentioning

confidence: 99%

“…Land use change from dry land to rice paddies also usually improves soil quality (Bhandari et al 2002). Smallholder farm communities often improve soil quality indirectly by increasing the active participation of farmers (Mowo et al 2006;Huang et al 2007). The results of the current study support these findings.…”

Section: Discussionmentioning

confidence: 99%

“…Email: yanbing_qi@sina.com land agriculture to rice paddy production have improved soil quality (Rasmussen & Parton 1994;Fischer et al 2002;Karlen et al 2006;Raiesi 2006;Huang et al 2007). These factors are accelerating changes in soil properties, both directly and indirectly, to the degree that new trends reveal that human-induced variation of soil properties has surpassed natural variation (David et al 2001).…”

Section: Introductionmentioning

confidence: 99%

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Impacts of agricultural land management on soil quality after 24 years: a case study in Zhangjiagang County, China

Huang

Darilek

2011

New Zealand Journal of Agricultural Research

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“…Land-use changes, including deforestation, biomass burning, draining wetlands, ploughing, the use of mineral fertilisers, and other agricultural practices, are regarded as the main factors causing the loss of soil organic carbon and the emission of Co 2 to the atmosphere (Zhang & Mcgrath2004). geostatistics has been successfully applied to quantify the distribution of the spatial patterns and changes in SoM (frogbrook & oliver 2001 ;Sun et al 2003;Wei et al 2006;huang et al 2007). geostatistics is based on the theory of a "regionalised variable" (Matheron 1963), i.e., one that is distributed in space with spatial coordinates.…”

Section: Introductionmentioning

confidence: 99%

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

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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.

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Temporal and spatial variability of soil organic matter and total nitrogen in an agricultural ecosystem as affected by farming practices

Cited by 186 publications

References 44 publications

Landscape-scale variability of soil health indicators: effects of cultivation on soil organic carbon in the Usambara Mountains of Tanzania

Landscape-scale variability of soil health indicators: effects of cultivation on soil organic carbon in the Usambara Mountains of Tanzania

Impacts of agricultural land management on soil quality after 24 years: a case study in Zhangjiagang County, China

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

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