Abstract Citizen science observations represent a significant and growing source of species and ecosystem knowledge. These data have potential to support traditional surveys. Databases of citizen observations of wildlife are growing, but how to use this information for scientific purposes is less clear owing to uncertainty in sampling distribution and data quality. In this study, we demonstrate how mapping cetacean patterns using citizen observations and systematic surveys generate consistent and different understandings of cetacean distributions and densities, and evaluate potential risk by assessing cumulative human effects in British Columbia, Canada. We used GIS-based map comparison methods that quantified differences and similarities between geographic datasets to locate where cetacean distributions and densities had spatially unique or spatially analogous representation. Where spatial clusters in both data sources are congruent, we interpret with a higher level of confidence that species occur, and mapped patterns accurately reflect distribution and density. In areas where datasets exhibit dissimilar species densities and distributions, we acknowledge lower confidence and advise further sampling. Regions of agreement were primarily in the central-western portion of the study area (off the southeastern coast of Haida Gwaii); areas of disagreement were heterogeneously distributed across the study area. Spatial clusters from citizen data exhibited significantly higher cumulative human effect scores than from systematic surveys, despite previous data adjustments for human effort. We demonstrate the use of citizen observations as a confirmatory dataset to broaden ecological exploration by augmenting scientific survey datasets and identifying strategic areas for future data collection efforts.

中文翻译：

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比较公民科学报告和海洋哺乳动物分布和密度的系统调查

摘要 公民科学观察代表了物种和生态系统知识的重要且不断增长的来源。这些数据有可能支持传统调查。公民对野生动物的观察数据库正在增长，但由于采样分布和数据质量的不确定性，如何将这些信息用于科学目的还不太清楚。在这项研究中，我们展示了如何使用公民观察和系统调查绘制鲸类模式图，从而对鲸类分布和密度产生一致和不同的理解，并通过评估加拿大不列颠哥伦比亚省的累积人类影响来评估潜在风险。我们使用基于 GIS 的地图比较方法来量化地理数据集之间的差异和相似性，以定位鲸类分布和密度在空间上具有独特性或空间相似性的位置。在两个数据源中的空间集群一致的情况下，我们以更高的置信度解释物种出现，并且映射模式准确地反映了分布和密度。在数据集表现出不同物种密度和分布的区域，我们承认较低的置信度并建议进一步采样。协议区域主要在研究区的中西部（海达瓜伊东南海岸附近）；分歧的领域在整个研究区域内分布不均。尽管之前的数据因人为因素进行了调整，但来自公民数据的空间集群表现出的累积人类影响得分明显高于系统调查。我们展示了使用公民观察作为验证性数据集，通过增加科学调查数据集和确定未来数据收集工作的战略领域来扩大生态探索。