Scaling up cover crop use will increase crop diversity on agricultural lands and help achieve sustainable production and environmental wellbeing. To increase the total acreage planted to cover crops, more farmers need to use cover crops on a larger proportion of their farms (extent) and for a longer time (longevity), suggesting the importance of spatial and temporal scales of adoption. The adoption literature lacks attention to the spatial and temporal precision of practice measures and misses opportunities to identify consistent or diverse mechanisms for scaling up conservation practices. To fill this gap, we used data from 1,724 corn ( Zea mays L.) and soybean ( Glycine max [L.] Merr.) farms in Illinois, Indiana, Michigan, and Ohio to study three measures of cover crop usage: the use of cover crops in a single year on a specific field, the percentage of acres planted to cover crops on a farm in a single-year, and years of cover crop use. Our models included key biophysical, operational, policy, social, and psychological factors. We hypothesize that predictors of cover crop adoption and intensity and longevity of use differ. Our results revealed five factors that performed consistently across measures (perceived benefits of cover crops, knowledge, profitability goals, no-till, and rotational diversity), while the effects of the other seven factors varied, including sustainability goals that were only associated with the longevity of use. Policy programs that aim at increasing cover crop use should consider which aspect of scaling-up is being targeted, then focus on corresponding factors that can better tailor policy and education programs to farmer motivations and decision-making contexts.

中文翻译：

---

扩大农业保护：美国中西部北部跨时间和空间覆盖作物使用的预测因素

扩大覆盖作物的使用将增加农田作物的多样性，并有助于实现可持续生产和环境福祉。为了增加覆盖作物的种植总面积，更多的农民需要在更大比例的农场（范围）和更长的时间（寿命）使用覆盖作物，这表明采用的空间和时间规模的重要性。采用文献缺乏对实践措施的空间和时间精度的关注，并且错过了确定扩大保护实践的一致或多样化机制的机会。为了填补这一空白，我们使用来自伊利诺伊州、印第安纳州、密歇根州和俄亥俄州 1,724 个玉米 (Zea mays L.) 和大豆 (Glycine max [L.] Merr.) 农场的数据来研究覆盖作物使用的三种措施：特定田地一年内覆盖作物的数量，农场一年内种植覆盖作物的面积百分比，以及覆盖作物的使用年数。我们的模型包括关键的生物物理、操作、政策、社会和心理因素。我们假设覆盖作物的采用以及使用强度和寿命的预测因素是不同的。我们的结果显示，五个因素在各种措施中表现一致（覆盖作物的感知效益、知识、盈利目标、免耕和轮作多样性），而其他七个因素的影响各不相同，包括仅与使用期限。旨在增加覆盖作物使用的政策计划应考虑扩大规模的哪个方面是针对的，