Measuring avian migration can prove challenging given the spatial scope and the diversity of species involved. No one monitoring technique provides all the pertinent measures needed to capture this macroscale phenomenon – emphasizing the need for data integration. Migration phenology is a key metric characterizing large-scale migration dynamics and has been successfully quantified using weather surveillance radar (WSR) data and community science observations. Separately, both platforms have their limitations and measure different aspects of bird migration. We sought to make a formal comparison of the migration phenology estimates derived from WSR and eBird data – of which we predict a positive correlation.

中文翻译：

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eBird 社区科学与基于天气监视雷达的迁徙物候估计之间的相关性


考虑到所涉及物种的空间范围和多样性，测量鸟类迁徙可能具有挑战性。没有一种监测技术能够提供捕捉这一宏观现象所需的所有相关措施——这强调了数据集成的必要性。迁徙物候学是表征大规模迁徙动态的关键指标，并已使用天气监视雷达（WSR）数据和社区科学观测成功量化。另外，这两个平台都有其局限性，并且测量鸟类迁徙的不同方面。我们试图对从 WSR 和 eBird 数据得出的迁徙物候估计进行正式比较——我们预测它们之间存在正相关性。