Understanding the fate of soil organic matter in submerging coastal wetland soils: A microcosm approach

Geoderma ◽  
2019 ◽  
Vol 337 ◽  
pp. 1267-1277 ◽  
Author(s):  
Havalend E. Steinmuller ◽  
Kyle M. Dittmer ◽  
John R. White ◽  
Lisa G. Chambers
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Coastal Wetland ◽  
Wetland Soils

Negative Feedback by Vegetation on Soil Organic Matter Decomposition in a Coastal Wetland

Wetlands ◽  
2020 ◽  
Vol 40 (6) ◽  
pp. 2785-2797
Author(s):  
Qingyuan Lu ◽  
Lixin Pei ◽  
Siyuan Ye ◽  
Edward A. Laws ◽  
Hans Brix
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Negative Feedback ◽  
Coastal Wetland ◽  
Organic Matter Decomposition ◽  
Soil Organic Matter Decomposition

Nitrogen mineralization processes of soils from natural saline-alkalined wetlands, Xianghai National Nature Reserve, China

2005 ◽  
Vol 85 (3) ◽  
pp. 359-367 ◽  
Author(s):  
Junhong Bai ◽  
Hua Ouyang ◽  
Wei Deng ◽  
Qinggai Wang ◽  
Hui Chen ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Nitrogen Mineralization ◽  
Nature Reserve ◽  
Wetland Soils ◽  
Anaerobic Incubation ◽  
Temperature Model ◽  
Total N ◽  
National Nature Reserve ◽  
Mineralization Processes

Nitrogen mineralization was evaluated using a 12-wk anaerobic incubation at 30°C in two wetland soils located in Xianghai National Nature Reserve, China. The Erbaifangzi wetland is an open wetland because it hydrologically connected to the surrounding ecosystem, whereas the Fulaowenpao wetland is a closed wetland, which is not hydrologically connected. Nitrogen mineralization was fitted to an effective cumulative temperature model. Nitrogen mineralization increased gradually with increases in the cumulative temperature and decreased with depth in the soil profile. Nitrogen mineralization was positively correlated with total N (TN) or soil organic matter (SOM), but not with soil pH. Basal N mineralization was found to be greater in the Fulaowenpao wetland (0 .314g N m-2 d-1) than the Erbaifangzi wetland (0.230 g N m-2 d-1). Key words: Saline-alkalined wetland; marsh soils; nitrogen mineralization; anaerobic incubation; the effective cumulative temperature model

scholarly journals Estimation of Soil Organic Matter, Total Nitrogen and Total Carbon in Sustainable Coastal Wetlands

2019 ◽  
Vol 11 (3) ◽  
pp. 667 ◽  
Author(s):  
Sen Zhang ◽  
Xia Lu ◽  
Yuanzhi Zhang ◽  
Gege Nie ◽  
Yurong Li
Keyword(s):  
Neural Network ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Bp Neural Network ◽  
Coastal Wetlands ◽  
Coastal Wetland ◽  
Soil Samples ◽  
Total Carbon ◽  
First Derivative ◽  
Estimation Models

Soil plays an important role in coastal wetland ecosystems. The estimation of soil organic matter (SOM), total nitrogen (TN), and total carbon (TC) was investigated at the topsoil (0–20 cm) in the coastal wetlands of Dafeng Elk National Nature Reserve in Yancheng, Jiangsu province (China) using hyperspectral remote sensing data. The sensitive bands corresponding to SOM, TN, and TC content were retrieved based on the correlation coefficient after Savitzky–Golay (S–G) filtering and four differential transformations of the first derivative (R′), first derivative of reciprocal (1/R)′, second derivative of reciprocal (1/R)″, and first derivative of logarithm (lgR)′ by spectral reflectance (R) as R′, (1/R)′, (1/R)″, (lgR)′ of soil samples. The estimation models of SOM, TN, and TC by support vector machine (SVM) and back propagation (BP) neural network were applied. The results indicated that the effective bands can be identified by S–G filtering, differential transformation, and the correlation coefficient methods based on the original spectra of soil samples. The estimation accuracy of SVM is better than that of the BP neural network for SOM, TN, and TC in the Yancheng coastal wetland. The estimation model of SOM by SVM based on (1/R)′ spectra had the highest accuracy, with the determination coefficients (R2) and root mean square error (RMSE) of 0.93 and 0.23, respectively. However, the estimation models of TN and TC by using the (1/R)″ differential transformations of spectra were also high, with determination coefficients R2 of 0.88 and 0.85, RMSE of 0.17 and 0.26, respectively. The results also show that it is possible to estimate the nutrient contents of topsoil from hyperspectral data in sustainable coastal wetlands.

Sign in / Sign up

Export Citation Format

Share Document