PDF(Pubmed)
Abstract：
Tracking the state of biodiversity over time is critical to successful conservation, but conventional monitoring schemes tend to be insufficient to adequately quantify how species\' abundances and distributions are changing. One solution to this issue is to leverage data generated by citizen scientists, who collect vast quantities of data at temporal and spatial scales that cannot be matched by most traditional monitoring methods. However, the quality of citizen science data can vary greatly. In this paper, we develop three metrics (inventory completeness, range completeness, spatial bias) to assess the adequacy of spatial observation data. We explore the adequacy of citizen science data at the species level for Australia\'s terrestrial native birds and then model these metrics against a suite of seven species traits (threat status, taxonomic uniqueness, body mass, average count, range size, species density, and human population density) to identify predictors of data adequacy. We find that citizen science data adequacy for Australian birds is increasing across two of our metrics (inventory completeness and range completeness), but not spatial bias, which has worsened over time. Relationships between the three metrics and seven traits we modelled were variable, with only two traits having consistently significant relationships across the three metrics. Our results suggest that although citizen science data adequacy has generally increased over time, there are still gaps in the spatial adequacy of citizen science for monitoring many Australian birds. Despite these gaps, citizen science can play an important role in biodiversity monitoring by providing valuable baseline data that may be supplemented by information collected through other methods. We believe the metrics presented here constitute an easily applied approach to assessing the utility of citizen science datasets for biodiversity analyses, allowing researchers to identify and prioritise regions or species with lower data adequacy that will benefit most from targeted monitoring efforts.
摘要：
随着时间的推移，跟踪生物多样性的状态对于成功的保护至关重要，但是传统的监测方案往往不足以充分量化物种丰度和分布的变化。这个问题的一个解决方案是利用公民科学家产生的数据，他们在时间和空间尺度上收集了大多数传统监测方法无法比拟的大量数据。然而,公民科学数据的质量可能会有很大差异。在本文中,我们制定了三个指标(库存完整性，范围完整性，空间偏差)来评估空间观测数据的充分性。我们探索了澳大利亚陆生本地鸟类在物种水平上的公民科学数据的充分性，然后根据一组七个物种特征（威胁状态，分类学的独特性，体重,平均计数,范围大小,物种密度，和人口密度)，以确定数据充足性的预测因素。我们发现，澳大利亚鸟类的公民科学数据充分性在我们的两个指标(库存完整性和范围完整性)上都在增加，但不是空间偏差，随着时间的推移而恶化。我们建模的三个指标和七个特征之间的关系是可变的，只有两个特征在三个指标中具有一致的显著关系。我们的结果表明，尽管公民科学数据的充分性随着时间的推移而普遍增加，公民科学在监测许多澳大利亚鸟类方面的空间充分性仍然存在差距。尽管有这些差距,公民科学可以通过提供有价值的基线数据来补充通过其他方法收集的信息，从而在生物多样性监测中发挥重要作用。我们认为，这里提出的指标构成了一种易于应用的方法，可以评估公民科学数据集对生物多样性分析的效用，允许研究人员识别并优先考虑数据充分性较低的区域或物种，这些区域或物种将从有针对性的监测工作中受益最大。
