Analysis Data for \"Identifying and characterizing pesticide use on 9,000 fields of organic agriculture\"

AbstractWe identify the location of ~9,000 organic fields from 2013 — 2019 using field-level crop and pesticide use data, along with state certification data, for Kern County, CA, one of the US’ most valuable crop producing counties. We parse apart how being organic relative to conventional affects decisions to spray pesticides and, if spraying, how much to spray. We show the expected probability of spraying any pesticides is reduced by about 30 percentage points for organic relative to conventional fields, across different metrics of pesticide use including overall weight applied and coarse ecotoxicity metrics. We report little difference, on average, in pesticide use for organic and conventional fields that do spray, though observe substantial crop-specific heterogeneity., MethodsPlease see description in manuscript & supplementary information. , Usage notesPlease see README. The Stata code file is a supplementary data file associated with the manuscript. As noted in the README, missing values are represented by empty cells, per the syntax for Stata. See README for an explanation for why different variables have missing data.**摘要**：本研究针对美国最具经济价值的作物生产县之一——加利福尼亚州克恩县（Kern County, CA），利用地块级作物与农药使用数据结合州级认证数据，识别出2013年至2019年间约9000块有机农田的空间位置。本研究厘清了有机农田相较于常规农田对农药喷施决策的影响，以及实施喷施时的农药施用量变化规律。研究表明，在农药总施用量、粗生态毒性指标等多种农药使用评价维度下，有机农田相较于常规农田的农药喷施概率平均降低约30个百分点。尽管在实际喷施农药的农田中，有机与常规农田的农药使用量平均差异较小，但我们观察到显著的作物特异性异质性。 **方法**：详见论文正文与补充材料。 **使用说明**：详见数据集说明文件（README）。本研究附带的Stata代码文件属于与论文关联的补充数据文件。根据Stata语法规范，缺失值以空单元格表示；不同变量存在缺失数据的原因可参阅README文件。