Invention:
This invention is a method for predicting and geographically mapping the functional composition of soil microbial communities across a large geographical area and with diverse environments using machine learning. The resulting information is relevant to evaluating soil carbon, nitrogen, and phosphorus cycling.
Background:
Microbial-mediated soil organic matter decomposition regulates many key ecosystem functions such as soil nutrient cycling, carbon sequestration, and soil fertility. However, representing microbial processes in Earth system models is still a challenge due to the lack of a clear understanding regarding the spatial patterns of functional diversity within microbial communities and how diverse environments regulate these communities.
Applications:
- Biomass composition for food/fuels/chemicals
- Farm/pasture/forest management
- Other land management practices
- Consulting for policy evaluation
Advantages:
- More efficient
- Unique predictive technology
- Evaluates multiple elements simultaneously
