scholarly journals Short-term effects of thinning on the development and communities of understory vegetation of Chinese fir plantations in Southeastern China

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8536 ◽  
Author(s):  
Xuelei Xu ◽  
Xinjie Wang ◽  
Yang Hu ◽  
Ping Wang ◽  
Sajjad Saeed ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Community Composition ◽  
Sustainable Management ◽  
Soil Nutrient ◽  
Chinese Fir ◽  
Understory Vegetation ◽  
Southeastern China ◽  
Nutrient Contents ◽  
Thinning Intensity ◽  
Soil Nutrient Contents

Background High-density conditions are global issues that threaten the sustainable management of plantations throughout the world. Monocultures and untimely management practices have identically resulted in the simplex of community structures, decreases in biodiversity, and long-term productivity losses in plantations China. The most popular measure which is commonly used to address these issues is thinning, which potentially results in increases in the development of understory plants in plantations. However, there is limited information currently available regarding the community composition of understory vegetation and the associated environmental factors, which has limited the sustainable management of China’s fir plantation ecosystems. Method In the present study, a thinning experiment was implemented which included a control check (CK: no thinning), as well as low intensity thinning (LIT: 20%), moderate intensity thinning (MIT: 33%), and high intensity thinning (HIT: 50%) in Chinese fir plantations located in the Southeastern China. During the investigation process, the understory vegetation examined three years after thinning measures were completed, in order to analyze the impacts of different thinning intensities on the growth and community composition of the understory plants. At the same time, the associated environmental factors in the fir plantations were also investigated. Results The species richness, total coverage, and biomass of the understory vegetation were observed to be apparently increased with increasing thinning intensity. In addition, it was found that the thinning measures had prominently influenced the soil nutrients. The community compositions of the understory vegetation were significantly different among the four thinning intensity levels, especially between the CK and the HIT. Furthermore, the development of the understory vegetation was found to be significantly correlated with the soil nutrient contents, and the community compositions of the understory vegetation were prominently driven by the tree densities, slope positions, and soil nutrient contents.

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.

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

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.

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 Effect of Stand Density and Soil Layer on Soil Nutrients of a 37-year-old Cunninghamia lanceolata Plantation in Naxi, Sichuan Province, China

2019 ◽  
Vol 11 (19) ◽  
pp. 5410 ◽  
Author(s):  
Jie Lei ◽  
Hailun Du ◽  
Aiguo Duan ◽  
Jianguo Zhang
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Soil Nutrient ◽  
Stand Density ◽  
Chinese Fir ◽  
Understory Vegetation ◽  
Cunninghamia Lanceolata ◽  
Available P ◽  
Low Density ◽  
Soil Layers

In order to study the characteristics of soil nutrient elements and the changes in biomass under different densities and soil layers of forest stand, this paper considers Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) density test forests with five densities (A: 1667 trees·ha−1; B: 3333 trees·ha−1; C: 5000 trees·ha−1; D: 6667 trees·ha−1; E: 10,000 trees·ha−1) as the research objects, located in Naxi District, Sichuan Province, China. Eleven soil physical and chemical property indicators, understory vegetation, and litter biomass were measured. The results were as follows: (1) The stand density had a significant effect on the soil nutrient content, understory vegetation, and litter biomass. A low density is conducive to the accumulation of soil organic matter, hydrolytic N, available P, available K, and total Ca. (2) With the increase in soil depth, the contents of soil organic matter, total N, hydrolytic N, and total P decreased gradually; pH and total Ca decreased gradually; and available P showed a trend of decrease-up-decrease. The soil layers had no significant effect on the total K, total Fe, and total Mg concentrations. (3) Low density (density A or B) was found to be beneficial to the growth of undergrowth vegetation and forest trees, the return of nutrients, long-term soil maintenance, and the stable high yield of Chinese fir plantations.

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.

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