Data from: Using citizen science monitoring data in species distribution models to inform isotopic assignment of migratory connectivity in wetland birds

Stable isotopes have been used to estimate migratory connectivity in many species. Estimates are often greatly improved when coupled with species distribution models (SDMs), which temper estimates in relation to occurrence. SDMs can be constructed using from point locality data from a variety of sources including extensive monitoring data typically collected by citizen scientists. However, one potential issue with SDM is that these data oven have sampling bias. To avoid this potential bias, an approach using SDMs based on marsh bird monitoring program data collected by citizen scientists and other participants following protocols specifically designed to maximize detections of species of interest at locations representative of the species range. We then used the SDMs to refine isotopic assignments of breeding areas of autumn-migrating and wintering Sora (Porzana carolina), Virginia Rails (Rallus limicola), and Yellow Rails (Coturnicops noveboracensis) based on feathers collected from individuals caught at various locations in the United States from Minnesota south to Louisiana and South Carolina. Sora were assigned to an area that included much of the western U.S. and prairie Canada, covering parts of the Pacific, Central, and Mississippi Flyways. Yellow Rails were assigned to a broad area along Hudson and James Bay in northern Manitoba and Ontario, as well as smaller parts of Quebec, Minnesota, Wisconsin, and Michigan, including parts of the Mississippi and Atlantic Flyways. Virginia Rails were from several discrete areas, including parts of Colorado, New Mexico, the central valley of California, and southern Saskatchewan and Manitoba in the Pacific and Central Flyways. Our study demonstrates extensive data from organized citizen science monitoring programs are especially useful for improving isotopic assignments of migratory connectivity in birds, which can ultimately lead to better informed management decisions and conservation actions.

稳定同位素已被广泛应用于多种鸟类的迁徙连通性估算。当结合物种分布模型（Species Distribution Models, SDMs）时，迁徙连通性的估算精度往往会得到显著提升——这类模型可基于物种出现记录对估算结果进行校正。物种分布模型可通过多来源的点位分布数据构建，其中包括通常由公民科学家收集的大规模监测数据。然而，这类数据往往存在抽样偏差，这是物种分布模型面临的一个潜在局限。为规避此类偏差，本研究采用基于湿地鸟类监测项目数据构建的物种分布模型：该项目的数据由公民科学家及其他参与者按照专门设计的采样方案收集，旨在最大化目标物种在能代表其分布范围的监测点位上的检出率。随后，我们利用所构建的物种分布模型，对从美国明尼苏达州南部至路易斯安那州、南卡罗来纳州各地捕获个体所采集的羽毛样本进行同位素溯源，以明确秋季迁徙及越冬的索拉秧鸡（Porzana carolina）、弗吉尼亚秧鸡（Rallus limicola）和黄秧鸡（Coturnicops noveboracensis）的繁殖地分布。其中，索拉秧鸡的繁殖地覆盖美国西部大部分区域及加拿大草原省份，涵盖太平洋迁飞通道、中部迁飞通道与密西西比迁飞通道的部分区段；黄秧鸡的繁殖地主要分布在马尼托巴省北部及安大略省的哈德逊湾与詹姆斯湾沿岸区域，同时覆盖魁北克省、明尼苏达州、威斯康星州与密歇根州的小片区域，涉及密西西比及大西洋迁飞通道的部分区段；弗吉尼亚秧鸡的繁殖地则分散于多个独立区域，包括科罗拉多州、新墨西哥州、加利福尼亚州中央谷地，以及太平洋与中部迁飞通道沿线的萨斯喀彻温省南部与马尼托巴省南部。本研究证实，来自规范化公民科学监测项目的大规模数据，在提升鸟类迁徙连通性的同位素溯源精度方面极具应用价值，该成果最终可为更科学的管理决策与保护行动提供有力支撑。