Data from: The roles of non-production vegetation in agroecosystems: a research framework for filling process knowledge gaps in a social-ecological context

1. We searched the international literature for relevant articles following a modified systematic review protocol (Pickering & Byrne 2014). Relevant articles were defined as those that described primary research conducted on farmland that addressed questions regarding any ecological function(s) associated with non-production vegetation. 2. Five distinct search strings, comprised of various keywords (Table S1) were designed to find relevant papers addressing the following broad topics related to non-production vegetation in agroecosystems; faunal diversity and use of vegetation; spatial arrangement of vegetation in the landscape; pests and disease in vegetation; weeds in vegetation; abiotic functional responses to vegetation. 3. The proportion of relevant articles returned by 30 scholarly databases was examined using all five search strings, and nine databases were selected based on the proportion of these relevant returns: BASE, BioOne, Google Scholar, JSTOR, Jurn, ProQuest, Science Direct, Scopus, and Web of Science. 4. Each search string was entered into each of the nine databases in turn, and all relevant articles were downloaded (where relevance was determined by reading the abstract). If no relevant articles were found for the first 100 returns, we moved on to the next search string. 5. For every relevant article found, we also checked all citing articles using the “Cited by” function in Google Scholar. After the initial two databases were searched, we extracted all keywords from papers and ranked them by the number of occurrences. We updated the search strings to include any commonly-used keywords that were missing from the strings. The faunal and spatial searches that were carried out first yielded significant overlap relative to our article selection criteria, and were ultimately combined into one faunal database. 6. Once all searches were complete, we extracted and cross-referenced all reference lists from the downloaded articles using ParsCit (Kan et al. 2011) to compile a final list of articles across all searches. 7. A total of 704 articles were read and 342 were included using the criteria that they were: (1) empirical (not modelling or meta-analysis) studies within agroecosystems; and (2) they at least discussed the effects of non-production vegetation on processes, not just biodiversity, within agroecosystems.1. 本研究遵循改良版系统回顾（systematic review）方案（Pickering & Byrne 2014），对国际文献进行检索以筛选相关文献。相关文献定义为：针对农田开展的原始研究（primary research），且探讨了与非生产性植被（non-production vegetation）相关的各类生态功能问题。 2. 本研究设计了5组独立检索式（search strings），各组检索式包含多种关键词（附表S1），旨在检索涉及农业生态系统（agroecosystems）中非生产性植被的以下核心主题相关文献：植被的动物群落多样性与利用、景观中植被的空间配置、植被中的病虫害、植被中的杂草、植被的非生物功能响应。 3. 本研究通过全部5组检索式，对30个学术数据库的相关文献检索结果占比进行了评估，并基于相关结果占比筛选出9个数据库：BASE、BioOne、Google Scholar、JSTOR、Jurn、ProQuest、Science Direct、Scopus及Web of Science。 4. 依次将每组检索式输入上述9个数据库，下载所有符合要求的文献（相关性通过阅读摘要判定）；若前100条检索结果中无相关文献，则跳转至下一组检索式。 5. 针对每篇筛选出的相关文献，本研究还通过Google Scholar的“被引次数”功能检索其所有被引文献。在完成前2个数据库的检索后，我们从文献中提取全部关键词并按出现频次排序，更新检索式以补充遗漏的常用关键词。由于最初开展的动物群落与空间配置类检索，其文献筛选标准存在显著重叠，最终将二者合并为一个动物群落数据库。 6. 全部检索完成后，本研究使用ParsCit（Kan et al. 2011）提取并交叉比对下载文献的全部参考文献列表，整合所有检索结果以生成最终文献清单。 7. 本研究共阅读704篇文献，最终依据以下标准纳入342篇：（1）为农业生态系统内的实证研究（empirical studies），而非建模或元分析（meta-analysis）研究；（2）至少探讨了非生产性植被对农业生态系统内各类过程的影响，而非仅关注生物多样性（biodiversity）。