- Agronomic: clovers, rye, wheat
- Crop Production: application rate management, catch crops, cover crops, crop rotation, nutrient cycling, organic fertilizers, tissue analysis
- Education and Training: decision support system, on-farm/ranch research
- Pest Management: competition, mulches - living, mulching - vegetative, physical control, smother crops, weed ecology
- Production Systems: transitioning to organic
- Soil Management: green manures, nutrient mineralization, organic matter, soil chemistry, soil quality/health
Given the environmental impact of conventional agriculture and its vulnerability to increasingly extreme climate variation, it is necessary to explore and develop alternative, more environmentally sensitive and resilient agricultural systems. By relying more heavily on natural agroecosystem processes, or management practices that mimic these processes, we can establish progressively more resilient production systems. In order to do this, we must better understand the plant-environment feedbacks in agroecosystems and develop a framework for transferring this knowledge into effective management practices. As we work to manage ecosystem processes with more precision in sustainable agriculture, cover crops are a key tool. Cover crops have been used extensively in the past, and are increasingly used today, especially in organic farming. The contribution of some cover crop species to certain ecosystem functions like increased soil nitrogen and weed suppression is understood, but the degree of impact each cover crop species has on a given ecosystem process is still uncertain. In order to successfully manage these important ecosystem functions, we must have a better understanding of the connection between a given function, the mechanisms affecting that function, and the functional traits regulating that mechanism. This proposal lays the foundation for a framework to identify and interpret the impact of cover crop species and mixtures on relevant ecosystem functions, which will eventually allow us to better manage cover crops for these services. Our initial focus will be on the functional traits relevant to biological nitrogen fixation and weed suppression in mixtures of leguminous and non-leguminous cover crops.
Project objectives from proposal:
We have identified two agriculturally important ecosystem functions to focus on initially; increased soil nitrogen and weed suppression. The following objectives relate to these two functions.
1. Quantify functional traits associated with aggressivity and BNF in a range of legume and non-legume cover crop species.
- Aggressivity traits: total biomass, seedling vigor, resource domination (tall stature).
- BNF traits: nodulation, total biomass.
2. Assess the relationship between identified traits (above) and ecosystem functions.
- We will measure these traits in all species throughout the course of the experiment along with measurements of the ecosystem functions, weed suppression (weed biomass and count) and BNF (15N abundance).
3. Rank legumes and non-legumes in terms of aggressivity in monocultures and mixtures on a relative scale.
4. Evaluate the BNF rates of different legumes in monocultures and mixtures.
5. Develop and refine simple plant-based and visual metrics for the corresponding traits.
- In conjunction with direct measurement of plant traits (above), we will also trial measurement techniques that would be more appropriate for the farm-scale, relying on visual assessment or the use of cheap, available materials for quick results. We will then use the direct measurements to test and calibrate the simpler measurement techniques.
6.Initiate a dialogue with farmers, agricultural extension agents and researchers to share results and incorporate feedback for improvements and future research.
- While this research is based on ecological fundamentals, the end goal is to provide useful information and tools for practitioners. Therefore it is critical to involve farmers, extension agents and researchers throughout the development to maximize the impact and success of the work.