Ongoing loss of biological diversity is primarily the result of unsustainable human behavior. Thus, the long‐term success of biodiversity conservation depends on a thorough understanding of human–nature interactions. Such interactions are ubiquitous but vary greatly in time and space and are difficult to monitor efficiently at large spatial scales. However, the Information Age also provides new opportunities to better understand human–nature interactions because many aspects of daily life are recorded in a variety of digital formats. The emerging field of conservation culturomics aims to take advantage of digital data sources and methods to study human–nature interactions and thus to provide new tools for studying conservation at relevant temporal and spatial scales. Nevertheless, technical challenges associated with the identification, access, and analysis of relevant data hamper the wider adoption of culturomics methods. To help overcome these barriers, we propose a conservation culturomics research framework that addresses data acquisition, analysis, and inherent biases. The main sources of culturomic data include web pages, social media, and other digital platforms from which metrics of content and engagement can be obtained. Obtaining raw data from these platforms is usually desirable but requires careful consideration of how to access, store, and prepare the data for analysis. Methods for data analysis include network approaches to explore connections between topics, time‐series analysis for temporal data, and spatial modeling to highlight spatial patterns. Outstanding challenges associated with culturomics research include issues of interdisciplinarity, ethics, data biases, and validation. The practical guidance we offer will help conservation researchers and practitioners identify and obtain the necessary data and carry out appropriate analyses for their specific questions, thus facilitating the wider adoption of culturomics approaches for conservation applications.

中文翻译：

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数字数据源和保护文化的方法

持续的生物多样性丧失主要是人类行为不可持续的结果。因此，生物多样性保护的长期成功取决于对人与自然相互作用的透彻了解。这种相互作用无处不在，但在时间和空间上相差很大，并且很难在大的空间尺度上有效地进行监视。但是，信息时代也为更好地理解人与自然的互动提供了新的机会，因为日常生活的许多方面都以各种数字格式记录下来。保护文化的新兴领域旨在利用数字数据源和方法来研究人与自然的相互作用，从而为研究相关的时空尺度的保护提供新的工具。但是，与识别，访问，相关数据的分析阻碍了文化方法的广泛采用。为了帮助克服这些障碍，我们提出了一个保护文化研究框架，以解决数据获取，分析和固有偏差的问题。文化数据的主要来源包括网页，社交媒体和其他数字平台，从中可以获得内容和参与度的指标。从这些平台获取原始数据通常是可取的，但需要仔细考虑如何访问，存储和准备数据以进行分析。数据分析的方法包括探索主题之间联系的网络方法，对时间数据的时间序列分析以及突出显示空间模式的空间建模。与文化学研究相关的突出挑战包括跨学科，伦理，数据偏见，和验证。我们提供的实用指南将帮助保护研究人员和从业人员识别和获取必要的数据，并对他们的具体问题进行适当的分析，从而促进在保护应用中广泛采用文化学方法。