Biology Department, Colorado State University, 251 W. Pitkins St, Fort Collins, CO, 80521, U.S.A.
Center for Tropical Research, Institute of the Environment and Sustainability, University of California, 619 Charles E Young Drive East, Los Angeles, CA, 90095, U.S.A.
Conserv Biol. 2020 Dec;34(6):1482-1491. doi: 10.1111/cobi.13536. Epub 2020 Jul 3.
Migratory animals are declining worldwide and coordinated conservation efforts are needed to reverse current trends. We devised a novel genoscape-network model that combines genetic analyses with species distribution modeling and demographic data to overcome challenges with conceptualizing alternative risk factors in migratory species across their full annual cycle. We applied our method to the long distance, Neotropical migratory bird, Wilson's Warbler (Cardellina pusilla). Despite a lack of data from some wintering locations, we demonstrated how the results can be used to help prioritize conservation of breeding and wintering areas. For example, we showed that when genetic, demographic, and network modeling results were considered together it became clear that conservation recommendations will differ depending on whether the goal is to preserve unique genetic lineages or the largest number of birds per unit area. More specifically, if preservation of genetic lineages is the goal, then limited resources should be focused on preserving habitat in the California Sierra, Basin Rockies, or Coastal California, where the 3 most vulnerable genetic lineages breed, or in western Mexico, where 2 of the 3 most vulnerable lineages overwinter. Alternatively, if preservation of the largest number of individuals per unit area is the goal, then limited conservation dollars should be placed in the Pacific Northwest or Central America, where densities are estimated to be the highest. Overall, our results demonstrated the utility of adopting a genetically based network model for integrating multiple types of data across vast geographic scales and better inform conservation decision-making for migratory animals.
迁徙动物在全球范围内减少，需要协调一致的保护努力来扭转当前的趋势。我们设计了一种新颖的基因景观网络模型，该模型将遗传分析与物种分布建模和人口统计数据相结合，以克服在整个年度周期中概念化迁徙物种替代风险因素的挑战。我们将我们的方法应用于长距离的新热带候鸟，威尔逊莺（Cardellina pusilla）。尽管一些越冬地点的数据不足，但我们展示了如何利用结果来帮助确定繁殖区和越冬区的保护优先级。例如，我们表明，当综合考虑遗传、人口统计和网络建模结果时，保护建议将因目标是保留独特的遗传谱系还是每单位面积的鸟类数量最多而有所不同。更具体地说，如果保护遗传谱系是目标，那么有限的资源应集中在加利福尼亚内华达山脉、盆地落基山脉或加利福尼亚沿海地区保护栖息地，这是 3 个最脆弱的遗传谱系繁殖的地方，或者在 2 个最脆弱的遗传谱系越冬的地方，在墨西哥西部。或者，如果目标是每单位面积保留最多的个体数量，那么有限的保护资金应该放在太平洋西北部或中美洲，那里的密度估计是最高的。总的来说，我们的结果表明，采用基于遗传的网络模型来整合跨越广阔地理范围的多种类型的数据，并为迁徙动物的保护决策提供更好的信息，是有用的。
