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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Sustainable Agricultural Systems Laboratory » Research » Publications at this Location » Publication #378033

Research Project: Cover Crop-Based Weed Management: Defining Plant-Plant and Plant-Soil Mechanisms and Developing New Systems

Location: Sustainable Agricultural Systems Laboratory

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

item BYBEE-FINLEY, ANN - Cornell University
item CORDEAU, STEPHANE - Inland Northwest Research Alliance, Inra
item YVOZ, SEVERIN - Inland Northwest Research Alliance, Inra
item Mirsky, Steven
item RYAN, MATTHEW - Cornell University

Submitted to: Ecological Applications
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/26/2021
Publication Date: 10/21/2021
Citation: Bybee-Finley, A., Cordeau, S., Yvoz, S., Mirsky, S.B., Ryan, M. 2021. Finding the right mix: A framework for selecting seeding rates for cover crop mixtures. Ecological Applications.

Interpretive Summary: Cover crops are nonmarketed crops used as multi-functional tools to promote agroecosystem function and environmental stewardship. Cover crops can be categorized several ways, including by the functional groups they fall into (e.g., legumes and grasses, winter and summer annuals). Due to the desire to maximize benefits from cover crops, farmers increasingly are planting cover crop mixtures to take advantage of the different strengths of varied cover crop species. However, the performance of any given cover crop in a mix depends on balancing the seeding rates in the mix so that no one species dominates to the detriment of the others. In this study, we conducted field experiments with different seeding rates of cowpea, sunn hemp, pearl millet, and sorghum sudangrass to quantify the interactions among the species based on seeding rate. We found that sorghum sudangrass was most competitive in mixture, followed by sunn hemp, pearl millet, and cowpea. When two species in the same functional group were planted together (such as a grass and a grass), the less competitive species displayed higher levels of intraspecific competition. Using these results and results from other similar studies, we modeled the interaction of these four cover crop species in mixture. Once we verified that the models were a good fit, we identified the optimum seeding rates for species in three- and four-species mixtures to maximize species biomass while minimizing seed cost to maximize the agroecosystem benefits provided. This work can improve seeding rate recommendations to improve cover crop performance, which may encourage farmers to increase adoption of the cover of cover crops.

Technical Abstract: Cover crop mixtures have the potential to provide more ecosystem services than cover crop monocultures. However, non-optimized seeding rates that are typically recommended (i.e., seeding rates in pure stand divided by the number of species in the mix) often result in one or two competitive species dominating the mixture, and thus limiting the amount of ecosystem services that are provided. We developed an analytical framework for selecting seeding rates for cover crop mixtures that maximize multifunctionality while minimizing costs. The framework was developed using data from a field experiment, which included six response surface designs of two-species mixtures, as well as a factorial replacement design of three- and four-species mixtures. We quantified intra- and interspecific competition among two grasses and two legume cover crop species: pearl millet [Pennisetum glaucum (L.) R. Br.], sorghum sudangrass [Sorghum bicolor (L.) Moench × S. sudanense (Piper) Stapf], sunn hemp (Crotalaria juncea L.), and cowpea [Vigna unguiculata (L.) Walp]. Yield-density models were fit to estimate intra and interspecific competition coefficients for each biculture. The hierarchy from most to least competitive was sorghum sudangrass > sunn hemp > pearl millet > cowpea. Intraspecific competition of a less competitive species was the greatest when the biculture was composed of two species in the same functional group (i.e., grass-grass, legume-legume). Competition coefficients were used to build models that estimated the biomass of each cover crop species in three- and four-species mixtures. The competition coefficients and models were validated with an additional nine site-years of an experiment that had the same cover crop mixtures. The biomass of a species in a site-year was accurately predicted 69% of the time (low root mean square error, correlation > 0.5, not biased, r2 > 0.5). Applying the framework, we designed three- and four-species mixtures (i.e., identifying relative seeding rates) that produced high biomass with high species evenness (i.e., high multifunctionality) at low seed costs based on a Pareto front analysis of 10,418 mixtures. Accounting for competition when constructing cover crop mixtures can improve the ecosystem services provided, and such an advancement would likely lead to greater farmer adoption.