Cover crop mixtures have the potential to provide more ecosystem services than cover crop monocultures. However, seeding rates that are typically recommended (i.e. seeding rate of monoculture divided by the number of species in the mixture) are non-optimized and often result in the competitive species dominating the mixture, and therefore limiting the amount of ecosystem services that are provided. We created an analytical framework for selecting seeding rates for cover crop mixtures that maximize multifunctionality while minimizing seed 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-species and four-species mixtures. We quantified intraspecific and interspecific competition among two grasses and two legume cover crop species with grass and legume representing two functional groups: pearl millet [Pennisetum glaucum (L.) R.Br.], sorghum sudangrass [Sorghum bicolor (L.) Moench × Sorghum sudanense (Piper) Stapf], sunn hemp (Crotalaria juncea L.), and cowpea [Vigna unguiculata (L.) Walp]. Yield–density models were fit to estimate intraspecific and interspecific competition coefficients for each species in 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. Competition coefficients were used to build models that estimated the biomass of each cover crop species in three-species and four-species mixtures. The competition coefficients and models were validated with an additional nine site-years testing 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-species and four-species mixtures by 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 is likely to lead to greater farmer adoption.

中文翻译：

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寻找合适的组合：选择覆盖作物混合物播种率的框架

覆盖作物混合物有可能提供比覆盖作物单一栽培更多的生态系统服务。然而，通常推荐的播种率（即单一栽培的播种率除以混合物中的物种数量）并未优化，通常会导致竞争物种在混合物中占主导地位，因此限制了提供的生态系统服务的数量. 我们创建了一个分析框架，用于选择覆盖作物混合物的播种率，以最大限度地提高多功能性，同时最大限度地降低种子成本。该框架是使用来自现场实验的数据开发的，其中包括两种混合物的六种响应面设计，以及三种和四种混合物的因子替换设计。Pennisetum glaucum (L.) R.Br.]、高粱 [ Sorghum bicolor (L.) Moench × Sorghum sudanense (Piper) Stapf]、sunn hemp ( Crotalaria juncea L.) 和豇豆 [ Vigna unguiculata(L.) 沃尔普]。产量密度模型适合估计双养中每个物种的种内和种间竞争系数。竞争程度从高到低依次为高粱 > 荸荠 > 珍珠粟 > 豇豆。当混养由同一功能组中的两个物种组成时，竞争力较弱的物种的种内竞争最大。竞争系数用于建立模型，估计三种和四种混合物中每种覆盖作物物种的生物量。竞争系数和模型通过另外九个站点年测试相同的覆盖作物混合物进行了验证。69% 的时间准确预测了一个地点年中物种的生物量（低均方根误差，相关性 > 0.5，无偏差，> 0.5)。应用该框架，我们基于对 10,418 种混合物的帕累托前沿分析，通过确定相对播种率以低种子成本产生高生物量和高物种均匀度（即高多功能性），设计了三物种和四物种混合物。在构建覆盖作物混合物时考虑竞争可以改善提供的生态系统服务，这种进步可能会导致更多的农民采用。