Abstract During the last decade, Conservation culturomics as a new epistemology and source of information on the relationship between conservation science, public interest and social relevance of conservation policies, is steadily emerging. Google Trends culturomics meta-information framework spreads actually in literature. There is however a series of doubts and questions on the validity of such an epistemology. In this short communication, a critical evaluation of the ongoing Conservation culturomics debate is presented. Five major issues are detected and discussed: (1) the problem of absolute vs. relative frequencies of crowdsearches in the Internet regarding emblematic terms associated with biodiversity; (2) the process of construction of the searched lexicon by the general public; (3) the issue of replicability of Google Trends -based research inferences; (4) the unknown yet importance of the 1% Internet rule as to the activity of massive and anonymous Google worldwide search engine users; and, (5) the existence of a real upper limit of linguistic diversity that actually constraints any explanatory multi-variate Google Trends statistical model. This contribution aims at suggesting that potential advantages of digital big-data information in environmental science and conservation practice could gain currency from big-data Internet sources in several key-topics if procedures and conclusions might be inscribed within a different but solid epistemic Method.

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基于谷歌趋势的保护文化组学研究十年：对不断发展的认识论的批判性评估

摘要 在过去的十年中，保护文化组学作为一种新的认识论和关于保护科学、公共利益和保护政策的社会相关性之间关系的信息来源，正在稳步发展。谷歌趋势文化组学元信息框架实际上在文献中传播。然而，对于这种认识论的有效性存在一系列怀疑和问题。在这篇简短的交流中，对正在进行的保护文化组学辩论进行了批判性评估。检测和讨论了五个主要问题：（1）互联网中关于与生物多样性相关的象征性术语的人群搜索的绝对频率与相对频率的问题；(2) 公众搜索词库的构建过程；（3）基于谷歌趋势的研究推论的可复制性问题；(4) 1% 互联网规则对于大量匿名谷歌全球搜索引擎用户的活动的未知但重要性；(5) 语言多样性的真实上限的存在实际上限制了任何解释性多变量谷歌趋势统计模型。该贡献旨在表明，如果程序和结论可以写入不同但可靠的认知方法，则数字大数据信息在环境科学和保护实践中的潜在优势可以从大数据互联网资源中的几个关键主题中获得价值。(5) 语言多样性的真实上限的存在实际上限制了任何解释性多变量谷歌趋势统计模型。该贡献旨在表明，如果程序和结论可以写入不同但可靠的认知方法，则数字大数据信息在环境科学和保护实践中的潜在优势可以从大数据互联网资源中的几个关键主题中获得价值。(5) 语言多样性的真实上限的存在实际上限制了任何解释性多变量谷歌趋势统计模型。该贡献旨在表明，如果程序和结论可以写入不同但可靠的认知方法，则数字大数据信息在环境科学和保护实践中的潜在优势可以从大数据互联网资源中的几个关键主题中获得价值。