Application of Nematode Community Analyses-Based Models towards Identifying Sustainable Soil Health Management Outcomes: A Review of the Concepts
Abstract
:1. Introduction
1.1. What Are the Characteristics of Sustainable Soil Health?
1.2. Why Nematodes Are Important to Soil Health?
1.3. Agriculture’s Footprint on Soil Health
- ●
- Approximately 46% of the maize and soybean acreage was high-yielding, 26% stable low yielding, and 28% unstable (variable) yielding.
- ●
- Low-yielding areas contributed ~44% and variable-yielding areas during years of poor yield 31% of total N loss to the environment.
- ●
- Total loss to farmers from overfertilization in low- and variable-yielding areas was ~$485 million. The loss in fertilizer value corresponded to greenhouse gas (GHG) of 6.8 MMT CO2 equivalents.
2. Conceptual Understanding of the Cycle of Soil Health Degradation
3. Barriers to Developing Sustainable Soil Health and How to Overcome the Gaps Using Nematodes
4. How the SFW Model Uses Nematodes to Identify Agroecosystem Suitability of Soil Conditions
4.1. Description of the Ferris et al. SFW Model
4.2. Examples of the SFW Model as a Decision-Making Tool to Identify Soil Health Conditions
4.3. Potential Use of the SFW Model as an Integration Platform for Soil Health Indicators
5. The FUE Model Analysis to Identify Integrated Efficiency Outcomes
5.1. The Concept and the Calculations
5.2. Visualization of the Outcomes
5.3. Examples of How the FUE Model Visualization Can Detect Hidden Patterns
6. Future Perspectives for Increased Implementation of the Models
7. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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SG | Country | SI ¥ | EI |
---|---|---|---|
FL | Ghana | 77.8 ± 6.6 ab | 18.5 ± 4.1 ed |
Kenya | 68.2 ± 4.9 bc | 30.6 ± 2.8 abc | |
Malawi | 31.9 ± 4.9 d | 36.0 ± 2.8 ab | |
LL | Ghana | 88.3 ± 5.8 a | 28.3 ± 3.4 abc |
Kenya | 62.4 ± 4.9 bc | 26.0 ± 2.8 cd | |
Malawi | 52.1 ± 5.0 c | 37.0 ± 2.9 a | |
NL | Ghana | 77.7 ± 4.9 ab | 27.7 ± 2.8 bcd |
Kenya | 62.8 ± 4.9 bc | 10.8 ± 2.8 e | |
Malawi | 42.1 ± 5.4 d | 31.3 ± 3.3 abc |
Factor | SCN ¥ | NDVI | SCN | NDVI | |
---|---|---|---|---|---|
Measured Values | AS % of Control | ||||
Nutrient (Nu) | Control | 2420 a | 0.373 a | na | na |
No N | 991 a | 0.411 a | 36.9 a | 110.3 a | |
Plus N | 2269 a | 0.333 a | 82.3 a | 89.8 a | |
Time (T) | V 5 | 3062 a | 0.348 a | 74.3 a | 108.3 a |
R1-R2 | 725 b | 0.396 a | 44.9 a | 91.9 a | |
Nu*T | 0.5398 | 0.6988 | 0.6205 | 0.9296 |
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Melakeberhan, H.; Bonito, G.; Kravchenko, A.N. Application of Nematode Community Analyses-Based Models towards Identifying Sustainable Soil Health Management Outcomes: A Review of the Concepts. Soil Syst. 2021, 5, 32. https://doi.org/10.3390/soilsystems5020032
Melakeberhan H, Bonito G, Kravchenko AN. Application of Nematode Community Analyses-Based Models towards Identifying Sustainable Soil Health Management Outcomes: A Review of the Concepts. Soil Systems. 2021; 5(2):32. https://doi.org/10.3390/soilsystems5020032
Chicago/Turabian StyleMelakeberhan, Haddish, Gregory Bonito, and Alexandra N. Kravchenko. 2021. "Application of Nematode Community Analyses-Based Models towards Identifying Sustainable Soil Health Management Outcomes: A Review of the Concepts" Soil Systems 5, no. 2: 32. https://doi.org/10.3390/soilsystems5020032