scholarly journals Application of Ordinary Kriging and Regression Kriging Method for Soil Properties Mapping in Hilly Region of Central Vietnam

2019 ◽  
Vol 8 (3) ◽  
pp. 147 ◽  
Author(s):  
Tung Gia Pham ◽  
Martin Kappas ◽  
Chuong Van Huynh ◽  
Linh Hoang Khanh Nguyen
Keyword(s):  
Land Use ◽  
Soil Properties ◽  
Soil Ph ◽  
Ordinary Kriging ◽  
Environmental Variables ◽  
Agricultural Land ◽  
Regression Kriging ◽  
Topographic Wetness Index ◽  
Central Vietnam ◽  
Hilly Region

Soil property maps are essential resources for agricultural land use. However, soil properties mapping is costly and time-consuming, especially in the regions with complicated topographic conditions. This study was conducted in a hilly region of Central Vietnam with the following objectives: (i) to evaluate the best environmental variables to estimate soil organic carbon (SOC), total nitrogen (TN), and soil reaction (pH) with a regression kriging (RK) model, and (ii) to compare the accuracy of the ordinary kriging (OK) and RK methods. SOC, TN, and soil pH data were measured at 155 locations within the research area with a sampling grid of 2 km × 2 km for a soil layer from 0 to 30 cm depth. From these samples, 117 were used for interpolation, and the 38 randomly remaining samples were used for evaluating accuracy. The chosen environmental variables are land use type (LUT), topographic wetness index (TWI), and transformed soil adjusted vegetation index (TSAVI). The results indicate that the LUT variable is more effective than TWI and TSAVI for determining TN and pH when using the RK method, with a variance of 7.00% and 18.40%, respectively. In contrast, a combination of the LUT and TWI variables is the best for SOC mapping with the RK method, with a variance of 14.98%. The OK method seemed more accurate than the RK method for SOC mapping by 3.33% and for TN mapping by 10% but the RK method was found more precise than the OK method for soil pH mapping by 1.81%. Further selection of auxiliary variables and higher sampling density should be considered to improve the accuracy of the RK method.

scholarly journals Relating environmental variables with aquatic community structure in an agricultural/urban coldwater stream

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Daniel T. L. Myers ◽  
Richard R. Rediske ◽  
James N. McNair ◽  
Aaron D. Parker ◽  
E. Wendy Ogilvie
Keyword(s):  
Land Use ◽  
Environmental Variables ◽  
Fish Community ◽  
Agricultural Land ◽  
Urban Land ◽  
Urban Land Use ◽  
Aquatic Communities ◽  
Natural Stream ◽  
Longitudinal Gradients ◽  
Agricultural Areas

Abstract Background Urban areas are often built along large rivers and surrounded by agricultural land. This may lead to small tributary streams that have agricultural headwaters and urbanized lower reaches. Our study objectives assessed are as follows: (1) landscape, geomorphic, and water quality variables that best explained variation in aquatic communities and their integrity in a stream system following this agricultural-to-urban land use gradient; (2) ways this land use gradient caused aquatic communities to differ from what would be expected for an idealized natural stream or other longitudinal gradients; and (3) whether the impacts of this land use gradient on aquatic communities would grow larger in a downstream direction through the agricultural and urban developments. Our study area was an impaired coldwater stream in Michigan, USA. Results Many factors structured the biological communities along the agricultural-to-urban land use gradient. Instream woody debris had the strongest relationship with EPT (Ephemeroptera, Plecoptera, and Trichoptera) abundance and richness and were most common in the lower, urbanized watershed. Fine streambed substrate had the strongest relationship with Diptera taxa and surface air breather macroinvertebrates and was dominant in agricultural headwaters. Fish community assemblage was influenced largely by stream flow and temperature regimes, while poor fish community integrity in lower urban reaches could be impacted by geomorphology and episodic urban pollution events. Scraping macroinvertebrates were most abundant in deforested, first-order agricultural headwaters, while EPT macroinvertebrate richness was the highest downstream of agricultural areas within the urban zone that had extensive forest buffers. Conclusion Environmental variables and aquatic communities would often not conform with what we would expect from an idealized natural stream. EPT richness improved downstream of agricultural areas. This shows promise for the recovery of aquatic systems using well-planned management in watersheds with this agricultural-to-urban land use pattern. Small patches of forest can be the key to conserving aquatic biodiversity in urbanized landscapes. These findings are valuable to an international audience of researchers and water resource managers who study stream systems following this common agricultural-to-urban land use gradient, the ecological communities of which may not conform with what is generally known about land use impacts to streams.

Vegetation Effects on Soil Properties in the Monteagle Sandy Loam Series: Implications for Land‐use Change

2017 ◽  
Author(s):  
Allison Neil
Keyword(s):  
Land Use ◽  
Organic Matter ◽  
Land Use Change ◽  
Soil Properties ◽  
Soil Carbon ◽  
Sugar Maple ◽  
Agricultural Land ◽  
Deciduous Forest ◽  
Coniferous Forest ◽  
The Impact

Soil properties are strongly influenced by the composition of the surrounding vegetation. We investigated soil properties of three ecosystems; a coniferous forest, a deciduous forest and an agricultural grassland, to determine the impact of land use change on soil properties. Disturbances such as deforestation followed by cultivation can severely alter soil properties, including losses of soil carbon. We collected nine 40 cm cores from three ecosystem types on the Roebuck Farm, north of Perth Village, Ontario, Canada. Dominant species in each ecosystem included hemlock and white pine in the coniferous forest; sugar maple, birch and beech in the deciduous forest; grasses, legumes and herbs in the grassland. Soil pH varied little between the three ecosystems and over depth. Soils under grassland vegetation had the highest bulk density, especially near the surface. The forest sites showed higher cation exchange capacity and soil moisture than the grassland; these differences largely resulted from higher organic matter levels in the surface forest soils. Vertical distribution of organic matter varied greatly amongst the three ecosystems. In the forest, more of the organic matter was located near the surface, while in the grassland organic matter concentrations varied little with depth. The results suggest that changes in land cover and land use alters litter inputs and nutrient cycling rates, modifying soil physical and chemical properties. Our results further suggest that conversion of forest into agricultural land in this area can lead to a decline in soil carbon storage.

scholarly journals Evaluation of Physicochemical Properties of Sandy-Textured Soils under Smallholder Agricultural Land Use Practices in Sarawak, East Malaysia

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Soo Ying Ho ◽  
Mohd Effendi Bin Wasli ◽  
Mugunthan Perumal
Keyword(s):  
Land Use ◽  
Physicochemical Properties ◽  
Soil Properties ◽  
Oil Palm ◽  
Agricultural Land ◽  
Secondary Forests ◽  
Land Uses ◽  
Total N ◽  
Organic C ◽  
Nutrient Contents

A study was conducted in the Sabal area, Sarawak, to evaluate the physicochemical properties of sandy-textured soils under smallholder agricultural land uses. Study sites were established under rubber, oil palm, and pepper land uses, in comparison to the adjacent secondary forests. The sandy-textured soils underlain in all agricultural land uses are of Spodosols, based on USDA Soil Taxonomy. The soil properties under secondary forests were strongly acidic with poor nutrient contents. Despite higher bulk density in oil palm farmlands, soil properties in rubber and oil palm land uses showed little variation to those in secondary forests. Conversely, soils under pepper land uses were less acidic with higher nutrient contents at the surface layer, especially P. In addition, soils in the pepper land uses were more compact due to human trampling effects from regular farm works at a localized area. Positive correlations were observed between soil total C and soil total N, soil exchangeable K, soil sum of bases, and soil effective CEC, suggesting that soil total C is the determinant of soil fertility under the agricultural land uses. Meanwhile, insufficient K input in oil palm land uses was observed from the partial nutrient balances estimation. In contrast, P and K did not remain in the soils under pepper land use, although the fertilizers application by the farmers was beyond the crop uptake and removal (harvesting). Because of the siliceous sandy nature (low clay contents) of Spodosols, they are poor in nutrient retention capacity. Hence, maintaining ample supply of organic C is crucial to sustain the productivity and fertility of sandy-textured soils, especially when the litterfall layers covering the E horizon were removed for oil palm and pepper cultivation.

scholarly journals Improving Soil Thickness Estimations Based on Multiple Environmental Variables with Stacking Ensemble Methods

2020 ◽  
Vol 12 (21) ◽  
pp. 3609
Author(s):  
Xinchuan Li ◽  
Juhua Luo ◽  
Xiuliang Jin ◽  
Qiaoning He ◽  
Yun Niu
Keyword(s):  
Machine Learning ◽  
Soil Properties ◽  
Environmental Variables ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Accurate Estimation ◽  
Support Vector ◽  
Topographic Wetness Index ◽  
Soil Thickness ◽  
Extreme Gradient Boosting

Spatially continuous soil thickness data at large scales are usually not readily available and are often difficult and expensive to acquire. Various machine learning algorithms have become very popular in digital soil mapping to predict and map the spatial distribution of soil properties. Identifying the controlling environmental variables of soil thickness and selecting suitable machine learning algorithms are vitally important in modeling. In this study, 11 quantitative and four qualitative environmental variables were selected to explore the main variables that affect soil thickness. Four commonly used machine learning algorithms (multiple linear regression (MLR), support vector regression (SVR), random forest (RF), and extreme gradient boosting (XGBoost) were evaluated as individual models to separately predict and obtain a soil thickness distribution map in Henan Province, China. In addition, the two stacking ensemble models using least absolute shrinkage and selection operator (LASSO) and generalized boosted regression model (GBM) were tested and applied to build the most reliable and accurate estimation model. The results showed that variable selection was a very important part of soil thickness modeling. Topographic wetness index (TWI), slope, elevation, land use and enhanced vegetation index (EVI) were the most influential environmental variables in soil thickness modeling. Comparative results showed that the XGBoost model outperformed the MLR, RF and SVR models. Importantly, the two stacking models achieved higher performance than the single model, especially when using GBM. In terms of accuracy, the proposed stacking method explained 64.0% of the variation for soil thickness. The results of our study provide useful alternative approaches for mapping soil thickness, with potential for use with other soil properties.

scholarly journals Spatial-Temporal Changes in Soil Organic Carbon and pH in the Liaoning Province of China: A Modeling Analysis Based on Observational Data

2019 ◽  
Vol 11 (13) ◽  
pp. 3569 ◽  
Author(s):  
Li Qi ◽  
Shuai Wang ◽  
Qianlai Zhuang ◽  
Zijiao Yang ◽  
Shubin Bai ◽  
...  
Keyword(s):  
Land Use ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Environmental Variables ◽  
Spatial Variations ◽  
Liaoning Province ◽  
Mean Annual Precipitation ◽  
Topographic Wetness Index ◽  
Infrared Band ◽  
Wetness Index

Quantification of soil organic carbon (SOC) and pH, and their spatial variations at regional scales, is a foundation to adequately assess agriculture, pollution control, or environmental health and ecosystem functioning, so as to establish better practices for land use and land management. In this study, we used the random forest (RF) model to map the distribution of SOC and pH in the topsoil (0–20 cm) and estimate SOC and pH changes from 1982 to 2012 in Liaoning Province, Northeast China. A total of 10 covariates (elevation, slope gradient, topographic wetness index (TWI), mean annual temperature (MAT), mean annual precipitation (MAP), visible-red band 3 (B3), near-infrared band 4 (B4), short-wave infrared band 5 (B5), normalized difference vegetation index (NDVI), and land-use data) and a set of 806 (in 1982) and 973 (in 2012) soil samples were selected. Cross-validation technology was used to test the performance and uncertainty of the RF model. We found that the prediction R2 of SOC and pH was 0.69 and 0.54 for 1982, and 0.63 and 0.48 for 2012, respectively. Elevation, NDVI, and land use are the main environmental variables affecting the spatial variability of SOC in both periods. Correspondingly, the topographic wetness index and mean annual precipitation were the two most critical environmental variables affecting the spatial variation of pH. The mean SOC and pH decreased from 18.6 to 16.9 kg−1 and 6.9 to 6.6, respectively, over a 30-year period. SOC distribution generated using the RF model showed a decreasing SOC trend from east to west across the city in the two periods. In contrast, the spatial distribution of pH showed an opposite trend in both periods. This study provided important information of spatial variations in SOC and pH to agencies and communities in this region, to evaluate soil quality and make decisions on remediation and prevention of soil acidification and salinization.

Can soil properties and agricultural land use affect arbuscular mycorrhizal fungal communities indigenous from the Argentinean Pampas soils?

2016 ◽  
Vol 101 ◽  
pp. 47-56 ◽  
Author(s):  
A.J. Thougnon Islas ◽  
K. Hernandez Guijarro ◽  
M. Eyherabide ◽  
H.R. Sainz Rozas ◽  
H.E. Echeverría ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Properties ◽  
Agricultural Land ◽  
Arbuscular Mycorrhizal ◽  
Fungal Communities ◽  
Agricultural Land Use ◽  
Arbuscular Mycorrhizal Fungal
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