Recreational fisheries are diverse in scale, scope, and participation worldwide, constituting an important ecosystem service of marine and freshwater ecosystems. Management of these socio-ecological systems is challenged by monitoring gaps, stemming from difficulties engaging with participants, biased sampling, and insufficient resources to conduct biological or social surveys of fish and human populations. In the Internet age, online data have great potential to make a meaningful contribution to recreational fisheries research, monitoring, and management. Recreational fishers in some countries increasingly use social and other digital media to share their experiences with followers, with most data freely available to web scrapers that compile databases of text (e.g. tweets, status updates, comments), photos, videos and other media that contain information about spatiotemporal activity, sentiments towards catches/experiences, targeted and bycatch species, effort levels, and more. Although the future of recreational fisheries research, monitoring and management will likely involve more digital scraping, uptake is only just beginning and there are several challenges including tool availability/accessibility, sampling biases, and making findings relevant and usable to practitioners. Despite these challenges, we envision fisheries managers will increasingly turn towards online sources of fisheries data to supplement conventional methods. We challenge scientists to work towards continued method development and validation of various digital fisheries data tools and emphasize how biases from the online behaviour of users may complicate interpretations of these data for fisheries management.

中文翻译：

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互联网时代的数字渔业数据：在休闲渔业中使用在线数据进行研究和监测的新兴工具

休闲渔业在世界范围内的规模、范围和参与度各不相同，构成了海洋和淡水生态系统的重要生态系统服务。这些社会生态系统的管理受到监测差距的挑战，这些差距源于与参与者接触的困难、有偏见的抽样以及对鱼类和人口进行生物或社会调查的资源不足。在互联网时代，在线数据具有为休闲渔业研究、监测和管理做出有意义贡献的巨大潜力。一些国家的休闲渔民越来越多地使用社交媒体和其他数字媒体与追随者分享他们的经验，大多数数据免费提供给编译文本数据库（例如推文、状态更新、评论）、照片、包含有关时空活动、对渔获物/经验、目标和兼捕物种、努力程度等信息的视频和其他媒体。尽管休闲渔业研究、监测和管理的未来可能会涉及更多的数字抓取，但采用才刚刚开始，并且存在一些挑战，包括工具的可用性/可及性、抽样偏差以及使研究结果对从业者相关和可用。尽管存在这些挑战，我们预计渔业管理者将越来越多地转向渔业数据的在线资源来补充传统方法。