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Novel Weighting Method for Evaluating Forest Soil Fertility Index: A Structural Equation Model
Wenfei Zhao1, Xiaoyu Cao1,2, Jiping Li1,2
1Faculty of Forestry, Central South University of Forestry and Technology, Changsha 410004, China.
Plants (Basel, Switzerland)
|January 21, 2023
Summary
Assessing forest soil nutrients is vital for ecosystem health. A structural equation model (SEM) effectively evaluated soil fertility index (SFI) in Chinese fir forests, highlighting total nitrogen (TN) as key.
Area of Science:
- Forestry Science
- Soil Science
- Ecosystem Management
Background:
- Forest soil nutrient quantity and quality are crucial for sustainable forest management and ecosystem services.
- Understanding these factors aids in maintaining forest health and productivity.
Purpose of the Study:
- To evaluate forest soil fertility index (SFI) using a structural equation model (SEM).
- To assess the influence of six soil nutrient indicators on SFI across different aged Chinese fir stands.
Main Methods:
- Measured soil organic matter (SOM), total nitrogen (TN), total phosphorus (TP), available nitrogen (AN), available phosphorus (AP), and available potassium (AK) in five age groups of Chinese fir forests.
- Developed and validated a structural equation model (SEM) to estimate the SFI based on the measured soil nutrients.
- Analyzed nutrient content variations with soil depth and stand age.
Main Results:
- Soil nutrient content varied significantly with soil depth and stand age.
- Total nitrogen (TN) exhibited the highest weight (0.4154) in the SEM for SFI estimation, while total phosphorus (TP) had the lowest (0.1991).
- Soil fertility index (SFI) was higher in older stands and topsoil compared to deeper soil layers.
Conclusions:
- The developed SEM accurately describes forest soil nutrient status and is suitable for estimating SFI.
- Total nitrogen, available phosphorus, and available potassium are the most influential indicators for evaluating SFI in these forests.
- This study offers an innovative approach for assessing forest soil nutrient status and fertility, providing a scientific basis for forest ecosystem management.
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