Spatial variability of soil chemical properties of Moso bamboo forests of China
- PDF / 3,020,781 Bytes
- 10 Pages / 595.276 x 790.866 pts Page_size
- 32 Downloads / 237 Views
ORIGINAL PAPER
Spatial variability of soil chemical properties of Moso bamboo forests of China Regassa Terefe1,2,3 · Kun‑yong Yu1,2 · Yangbo Deng1,2 · Xiong Yao1,2 · Fan Wang1,2 · Jian Liu1,2
Received: 7 June 2020 / Accepted: 23 September 2020 © Northeast Forestry University 2020
Abstract This study investigates the spatial variability of soil organic matter (SOM), soil organic carbon (SOC) and pH in the upper 20-cm layer and 20–40 cm layer in Moso bamboo (Phyllostachys pubescens Pradelle) forests using a geostatistics model. Interpolation maps of SOM, SOC, and pH were developed using ordinary kriging (OK) and inverse distance weighted (IDW) methods. The pH, SOC, and SOM of the two soil layers ranged from 4.6 to 4.7, from 1.5 to 2.7 g kg−1 and from 20.3 to 22.4 g kg−1, respectively. The coefficient of variation for SOM and SOC was 29.9–43.3% while a weak variability was found for pH. Gaussian and exponential models performed well in describing the spatial variability of SOC contents with R 2 varying from 0.95 to 0.90. The nugget/sill values of pH are less than 25%, which indicates a strong spatial correlation, while the nugget/sill
Project funding: The work was supported by the National Key Research and Development Program of China: High Efficiency Cultivation and Monitoring Technology for Timber Bamboo (Grant No.: 2018YFD0600103). The online version is available at http://www.springerlink.com. Corresponding editor: Yu Lei. * Regassa Terefe [email protected] * Jian Liu [email protected] 1
University Key Laboratory of Technology and Optimize Resource Utilization in Fujian Province, Fuzhou 350002, Fujian, People’s Republic of China
2
College of Forestry, Fujian Agriculture and Forestry University, Fuzhou 350002, People’s Republic of China
3
Bako Agriculture Research Center, Oromia Agriculture Research Institutes, P.O. Box, 03, Bako, Oromia, Ethiopia
values of SOC and SOM fall under moderate spatial correlation. Interpolation using ordinary kriging and inverse distance weighted methods revealed that the spatial distribution of SOM, SOC, and pH was inconsistent due to external and internal factors across the plots. Regarding the crossvalidation results, the ordinary kriging method performed better than inverse distance weighted method for selected soil properties. This study suggests that the spatial variability of soil chemical properties revealed by geostatistics modeling will help decision-makers improve the management of soil properties. Keywords Cross-validation · Geostatistics · Inverse distance weighted · Ordinary kriging · Semi-variance
Introduction Soils are critical resources for the growth and development of plants. Improvement of soil properties plays a significant role on the restoration of vegetation as key factors of structure and function for a degraded environment. Factors contributing to declining soil fertility are poor soil management, land use changes, exploitation of marginal lands, erosion, and nutrient leaching (Lemenih and Kassa 2014). For plant growth and the tran
Data Loading...
