Abstract Monitoring urban biodiversity is increasingly important, given the increasing anthropogenic pressures on biodiversity in urban areas. While the cost of broad-scale monitoring by professionals may be prohibitive, citizen science (also referred to as community science) will likely play an important role in understanding biodiversity responses to urbanization into the future. Here, we present a framework that relies on broad-scale citizen science data –– collected through iNaturalist –– to quantify (1) species-specific responses to urbanization on a continuous scale, capitalizing on globally-available VIIRS night-time lights data; and (2) community-level measures of the urbanness of a given biological community that can be aggregated to any spatial unit relevant for policy-decisions. We demonstrate the potential utility of this framework in the Boston metropolitan region, using >1000 species aggregated across 87 towns throughout the region. Of the most common species, our species-specific urbanness measures highlighted the expected difference between native and non-native species. Further, our biological community-level urbanness measures –– aggregated by towns –– negatively correlated with enhanced vegetation indices within a town and positively correlated with the area of impervious surface within a town. We conclude by demonstrating how towns can be ‘ranked’ promoting a framework where towns can be compared based on whether they over- or under-perform in the urbanness of their community relative to other towns. Ultimately, biodiversity conservation in urban environments will best succeed with robust, repeatable, and interpretable measures of biodiversity responses to urbanization, and involving the broader public in the derivation and tracking of these responses will likely result in increased bioliteracy and conservation awareness.

中文翻译：

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利用机会主义公民科学数据监测城市生物多样性：多分类群框架

摘要 鉴于人为对城市地区生物多样性的压力越来越大，监测城市生物多样性变得越来越重要。虽然专业人员进行大规模监测的成本可能令人望而却步，但公民科学（也称为社区科学）可能会在理解生物多样性对未来城市化的反应方面发挥重要作用。在这里，我们提出了一个框架，该框架依赖于广泛的公民科学数据——通过 iNaturalist 收集——来量化 (1) 特定物种对城市化的连续规模响应，利用全球可用的 VIIRS 夜间灯光数据；(2) 特定生物群落城市化的社区级测量，可以汇总到与政策决策相关的任何空间单位。我们展示了该框架在波士顿大都市区的潜在效用，使用了该地区 87 个城镇聚集的 1000 多个物种。在最常见的物种中，我们针对特定物种的城市化措施突出了本地和非本地物种之间的预期差异。此外，我们的生物社区层面的城市化措施——按城镇汇总——与城镇内增强的植被指数呈负相关，与城镇内不透水表面的面积呈正相关。最后，我们展示了如何对城镇进行“排名”，以促进一个框架，在该框架中，可以根据城镇相对于其他城镇在其社区的城市化方面的表现是优胜劣汰来对城镇进行比较。最终，城市环境中的生物多样性保护将通过稳健、可重复、