Finding the right mix: a framework for selecting seeding rates for cover crop mixtures

Area of Science:

• Agronomy and Soil Science
• Ecology
• Plant Science

Background:

• Cover crop mixtures offer greater ecosystem services than monocultures.
• Standard seeding rates are suboptimal, leading to competitive species dominance and reduced benefits.
• Optimizing mixture composition is crucial for maximizing cover crop potential.

Purpose of the Study:

• To develop an analytical framework for selecting cover crop mixture seeding rates.
• To maximize multifunctionality (ecosystem services) while minimizing seed costs.
• To account for interspecific and intraspecific competition in mixture design.

Main Methods:

• Quantified competition using yield-density models for two grasses and two legumes.
• Developed biomass prediction models for three- and four-species mixtures based on competition coefficients.
• Validated models across nine site-years.
• Utilized Pareto front analysis on 10,418 mixtures to identify optimal seeding rates.

Main Results:

• Established a competitive hierarchy: sorghum sudangrass > sunn hemp > pearl millet > cowpea.
• Biomass predictions were accurate (69% of the time) with validated models.
• Identified optimal seeding rates for high biomass, species evenness, and low cost in multi-species mixtures.

Conclusions:

• Accounting for competition is essential for designing effective cover crop mixtures.
• The developed framework enhances cover crop multifunctionality and economic viability.
• This approach can increase farmer adoption of cover crop mixtures for improved ecosystem services.