Department of Biological Sciences, Auburn University, Auburn, Alabama, 36849.
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, 04103, Germany.
Evolution. 2022 Feb;76(2):359-361. doi: 10.1111/evo.14390. Epub 2022 Jan 7.
When working with a citizen science database like eBird, there are many possible ways to filter or subsample observations. Here, we discuss the potential biases and assumptions that surround different subsampling approaches or filtering that can be done to the eBird database. Restricting observations to species that are known to frequently hybridize, a specific time of the year, or a specific location, has the potential to greatly inflate the calculated per-individual rate of hybridization. Such filtering also assumes that researchers know a birds' capacity to hybridize with all other species in its range, which we argue is an unfounded assumption. We ultimately conclude that a limited filtering approach is ideal when using a citizen science database to attempt to address a broad question such as: what is the per individual rate of hybridization across all of the bird species in the United States?
当使用像 eBird 这样的公民科学数据库时,有许多可能的方法来过滤或抽样观察结果。在这里,我们讨论了围绕不同抽样方法或可以对 eBird 数据库进行的过滤的潜在偏差和假设。将观察结果限制在已知经常杂交的物种、一年中的特定时间或特定地点,有可能极大地增加计算出的每个个体杂交率。这种过滤还假设研究人员知道鸟类与范围内所有其他物种杂交的能力,但我们认为这是一个毫无根据的假设。我们最终得出结论,当使用公民科学数据库来尝试回答一个广泛的问题时,如:在美国所有鸟类中,每个个体的杂交率是多少? 采用有限的过滤方法是理想的。