scholarly journals Conversion of Secondary Forests into Chestnut Forests Affects Soil Nutrients in Anji County, China

2019 ◽  
Vol 11 (8) ◽  
pp. 2373 ◽  
Author(s):  
Shiyong Sun ◽  
Zebo Li ◽  
Rongjia Wang ◽  
Jianfeng Zhang ◽  
Chunxia Pan ◽  
...  
Keyword(s):  
Soil Nutrients ◽  
Water Conservation ◽  
Secondary Forest ◽  
Soil Depth ◽  
Soil Nutrient ◽  
Vegetation Coverage ◽  
Secondary Forests ◽  
Nutrient Contents ◽  
Particle Form ◽  
Soil Nutrient Contents

The maintenance of drinking water safety is a major environmental issue. It is necessary to strengthen environmental protection in water source areas and establish good vegetation coverage. This study examined the effects of secondary forests transformation on chestnut forests on soil nutrient changes in the Fuji Reservoir, Anji County, Zhejiang province, China. Plots were set up in a chestnut plantation and a nearby secondary forest to measure the nutrient contents of soil samples that were collected from different soil depths. Differences of soil nutrient content from the two stands were significant at 0–20 cm soil depth. There were no significant differences in the contents of total phosphorus and total potassium between the two forests; however, the available phosphorus content in chestnut stands was 2.73 mg/kg higher than in secondary forests. Overall, the soil nutrient contents under chestnut stands were lower than those under secondary forests. Some of the soil surface is exposed due to the low diversity of the chestnut forest. The soil nutrients in the chestnut forest are usually carried and transferred in soil particle form and they become dissolved in the runoff during rainfall and lost, which explains the lower soil nutrient contents in the chestnut forest than the secondary forest. Therefore, for economic forests, such as chestnut forests, measures should be taken to protect understory vegetation and enhance soil and water conservation capacity, which is conducive to retaining soil nutrients.

scholarly journals Effects of Planting Density on Soil Bulk Density, pH and Nutrients of Unthinned Chinese Fir Mature Stands in South Subtropical Region of China

Forests ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 351
Author(s):  
Aiguo Duan ◽  
Jie Lei ◽  
Xiaoyan Hu ◽  
Jianguo Zhang ◽  
Hailun Du ◽  
...  
Keyword(s):  
Organic Matter ◽  
Bulk Density ◽  
Soil Depth ◽  
Soil Nutrient ◽  
Chinese Fir ◽  
Planting Density ◽  
Total N ◽  
Nutrient Contents ◽  
Exchangeable Ca ◽  
Soil Nutrient Contents

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) is a fast-growing evergreen conifer with high-quality timber and is an important reforestation and commercial tree species in southern China. Planting density affects the productivity of Chinese fir plantations. To study the effect of five different planting densities and soil depth on soil nutrient contents of a mature C. lanceolata plantation, the soil nutrient contents (soil depths 0–100 cm) of 36-year-old mature Chinese fir plantations under five different planting densities denoted A (1667 trees·ha−1), B (3333 trees·ha−1), C (5000 trees·ha−1), D (6667 trees·ha−1), and E (10,000 trees·ha−1) were measured in Pingxiang county, Guangxi province, China. Samples were collected from the soil surface down to a one meter depth from each of 45 soil profiles, and soil samples were obtained at 10 different soil depths of 0–10, 10–20, 20–30, 30–40, 40–50, 50–60, 60–70, 70–80, 80–90, and 90–100 cm. Twelve soil physical and chemical indicators were analyzed. The results showed that: (1) as planting density increased, the organic matter, organic carbon, total N and P, available N, effective Fe, and bulk density decreased. Soil pH, total K, and effective K increased with increasing planting density. Planting density did not significantly influence the exchangeable Ca and Mg. (2) Soil organic matter; organic carbon; total N and P; effective N, P, and K; exchangeable Ca and Mg; effective Fe content; and bulk density decreased with increasing soil depth. This pattern was particularly evident in the top 30 cm of the soil. (3) Excessively high planting density is not beneficial to the long-term maintenance of soil fertility in Chinese fir plantations, and the planting density of Chinese fir plantations should be maintained below 3333 stems·ha−1 (density A or B) to maintain soil fertility while ensuring high yields.

The Application of GIS Techniques in Soil Testing and Fertilizer Recommendations: Part II the Distribution of Soil Nutrients in Hainan, China

2012 ◽  
Vol 610-613 ◽  
pp. 3697-3701
Author(s):  
Zhi Yuan Wei ◽  
Deng Feng Wang ◽  
Zhi Ping Qi
Keyword(s):  
Spatial Analysis ◽  
Soil Nutrients ◽  
Arable Land ◽  
Soil Nutrient ◽  
Hainan Island ◽  
Nutrient Elements ◽  
Available N ◽  
Nutrient Contents ◽  
Fertilizer Recommendations ◽  
Soil Nutrient Contents

The research on the distribution of soil nutrient contents in arable land regionally is the basis for the proper fertilization. The study, taking Hainan Island as the study area, analyzes the distribution and variation of soil nutrient contents in arable land spatially and temporally by applying GIS spatial analysis. As the study shows, from the 1980s to the year of 2005, the TN, TP, TK, and Available N contents in soil of arable land have declined to certain degree, while Available P and Available K kept increasing. Generally, the soil nutrients have declined in quality during last two decades but remain in a mediate level. Spatial analysis can reflect the distribution characteristics of the regional soil nutrient elements in an objective manner.

Predicting soil nutrient contents using Landsat OLI satellite images in rain-fed agricultural lands, northwest of Iran

2021 ◽  
Vol 193 (9) ◽  
Author(s):  
Naser Miran ◽  
Mir Hassan Rasouli Sadaghiani ◽  
Vali Feiziasl ◽  
Ebrahim Sepehr ◽  
Mehdi Rahmati ◽  
...  
Keyword(s):  
Satellite Images ◽  
Soil Nutrient ◽  
Agricultural Lands ◽  
Nutrient Contents ◽  
Northwest Of Iran ◽  
Soil Nutrient Contents

scholarly journals Vegetation degradation impacts soil nutrients and enzyme activities in wet meadow on the Qinghai-Tibet Plateau

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jiangqi Wu ◽  
Haiyan Wang ◽  
Guang Li ◽  
Weiwei Ma ◽  
Jianghua Wu ◽  
...  
Keyword(s):  
Enzyme Activity ◽  
Soil Nutrients ◽  
Enzyme Activities ◽  
Soil Depth ◽  
Soil Nutrient ◽  
Tibet Plateau ◽  
Wet Meadow ◽  
Vegetation Degradation ◽  
Thaw Cycle ◽  
Qinghai Tibet Plateau

AbstractVegetation degradation, due to climate change and human activities, changes the biomass, vegetation species composition, and soil nutrient input sources and thus affects soil nutrient cycling and enzyme activities. However, few studies have focused on the responses of soil nutrients and enzymes to vegetation degradation in high-altitude wet meadows. In this study, we examined the effects of vegetation degradation on soil nutrients (soil organic carbon, SOC; total nitrogen, TN; total phosphorus, TP) and enzyme activities (i.e., urease, catalase, amylase) in an alpine meadow in the eastern margin of the Qinghai-Tibet Plateau. Four different levels of degradation were defined in terms of vegetation density and composition: primary wet meadow (CK), lightly degraded (LD), moderately degraded (MD), and heavily degraded (HD). Soil samples were collected at depth intervals of 0–10, 10–20, 20–40, 40–60, 60–80, and 80–100 cm to determine soil nutrient levels and enzyme activities. The results showed that SOC, TN, catalase and amylase significantly decreased with degradation level, while TP and urease increased with degradation level (P < 0.05). Soil nutrient and enzyme activity significantly decreased with soil depth (P < 0.05), and the soil nutrient and enzyme activity exhibited obvious "surface aggregation". The activities of soil urease and catalase were strongest in spring and weakest in winter. The content of TN in spring, summer, and autumn was significantly higher than observed in winter (P < 0.05). The soil TP content increased in winter. Soil amylase activity was significantly higher in summerm than in spring, autumn, and winter (P < 0.05). TP was the main limiting factor for plant growth in the Gahai wet meadow. Values of SOC and TN were positively and significantly correlated with amylase and catalase (P < 0.05), but negatively correlated with urease (P < 0.05). These results suggest the significant role that vegetation degradation and seasonal freeze–thaw cycle play in regulating enzyme activities and nutrient availability in wet meadow soil.

scholarly journals Decomposition characteristics of long-established Salix psammophila sand barriers in an arid area, Northwestern China

BioResources ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. 5947-5963
Author(s):  
Ruidong Wang ◽  
Xia Yang ◽  
Yong Gao ◽  
Xiaohong Dang ◽  
Yumei Liang ◽  
...  
Keyword(s):  
Nutrient Release ◽  
Soil Nutrient ◽  
Decomposition Process ◽  
Northwestern China ◽  
Barrier Material ◽  
Nutrient Contents ◽  
Arid Northwestern China ◽  
Decomposition Time ◽  
Soil Nutrient Contents

Salix psammophila has been extensively used as a sand barrier material for various desertification control applications. Elucidating the long-term decomposition characteristics and nutrient cycling process of this sand barrier in desert environments is of great importance. In this study, which was conducted for 1 to 9 years, changes in the mass loss percentage and the residual percentage in the decomposition process were explored of S. psammophila sand barriers in arid Northwestern China. In addition, the S. psammophila analysis nutrient elements release rule and its influence on soil properties were evaluated. The results showed that the decomposition process of S. psammophila sand barriers exhibited a “slow-fast” trend. After decomposition time for 9 years, mass decreased remarkably, and the residual percentage was 33.6%. Further, the nutrient release characteristics differed. C, P, and K were in the release state, whereas N was in the enrichment state. The decomposition percentage of the sand barriers was significantly correlated with N, P, K, C/N, C/P, and N/P (p < 0.05). The soil nutrient contents of C, P, and K contents increased 3.43, 2.23, and 2.08 g/kg compared to the initial values, respectively. The soil nutrient contents of N contents decreased 0.19 g/kg.

scholarly journals Prediction of Soil Nutrient Contents Using Visible and Near-Infrared Reflectance Spectroscopy

2019 ◽  
Vol 8 (10) ◽  
pp. 437 ◽  
Author(s):  
Yiping Peng ◽  
Li Zhao ◽  
Yueming Hu ◽  
Guangxing Wang ◽  
Lu Wang ◽  
...  
Keyword(s):  
Near Infrared ◽  
Regional Scale ◽  
Soil Nutrient ◽  
Hyperspectral Data ◽  
Estimation Accuracy ◽  
Soil Productivity ◽  
Least Squares Regression ◽  
Near Infrared Reflectance ◽  
Nutrient Contents ◽  
Soil Nutrient Contents

Quickly and efficiently monitoring soil nutrient contents using remote sensing technology is of great significance for farmland soil productivity, food security and sustainable agricultural development. Current research has been conducted to estimate and map soil nutrient contents in large areas using hyper-spectral techniques, however, it is difficult to obtain accurate estimates. In order to improve the estimation accuracy of soil nutrient contents, we introduced a GA-BPNN method, which combined a back propagation neural network (BPNN) with the genetic algorithm optimization (GA). This study was conducted in Guangdong, China, based on soil nutrient contents and hyperspectral data. The prediction accuracies from a partial least squares regression (PLSR), BPNN and GA-BPNN were compared using field observations. The results showed that (1) Among three methods, the GA-BPNN provided the most accurate estimates of soil total nitrogen (TN), total phosphorus (TP) and total potassium (TK) contents; (2) Compared with the BPNN models, the GA-BPNN models significantly improved the estimation accuracies of the soil nutrient contents by decreasing the relative root mean square error (RRMSE) values by 15.9%, 5.6% and 20.2% at the sample point level, and 20.1%, 16.5% and 47.1% at the regional scale for TN, TP and TK, respectively. This indicated that by optimizing the parameters of BPNN, the GA-BPNN provided greater potential to improving the estimation; and (3) Soil TK content could be more accurately mapped by the GA-BPNN method using HuanJing-1A Hyperspectral Imager (HJ-1A HSI) (manufacturer: China Aerospace Science and Technology Corporation; Beijing, China) data with a RRMSE value of 20.37% than the soil TN and TP with the RRMSE values of 40.41% and 34.71%, respectively. This implied that the GA-BPNN model provided the potential to map the soil TK content for the large area. The research results provided an important reference for high-accuracy prediction of soil nutrient contents.

Analysis of Soil Organic Matter and Soil Total Nitrogen Condition under Different Vegetation Patterns of Huanghuadianzi Small Watershed

2013 ◽  
Vol 807-809 ◽  
pp. 1839-1842
Author(s):  
Yue Feng Guo ◽  
Yun Feng Yao ◽  
Fu Cang Qin ◽  
Wei Qi
Keyword(s):  
Soil Nutrients ◽  
Total Nitrogen ◽  
Land Use Planning ◽  
Secondary Forest ◽  
Soil Layer ◽  
Soil Nutrient ◽  
Vegetation Patterns ◽  
Small Watershed ◽  
Obvious Effect ◽  
Soil Layers

Different vegetation patterns have difference influenced on the soil nutrients and the soil nutrient contents of different soil layers in the same vegetation patterns are also different in size. In this paper, we analyze the main soil nutrients of different soil layers in different vegetation patterns in Huanghuadianzi small watershed in Ao HanQI of Chifeng in China. The result shows that in different vegetation patterns, the secondary forest of natural bush have an obvious effect on the nutrient and concentration of organic; in the artificial forest, mingled forest has a better improving effect on soil than the pure forest and natural grassland has the smallest effect; in the same vegetation patterns, organic, total nitrogen present an overall reduction trend with the deepening of soil layer accept 40-60cm soil layers. The analysis result of this paper can provide a theoretical basis for further researching the dynamic nutrient change, tree variety optimization arrangement and regional land use planning in forest grass zone.

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