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. Article impact statement: Genoscape-network models can facilitate conservation prioritization in migratory animals across the full annual cycle. This article is protected by copyright. All rights reserved.

中文翻译：

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候鸟保护优先级的基因景观网络模型

迁徙动物在世界范围内正在减少，需要采取协调一致的保护措施来扭转当前的趋势。我们设计了一种新的基因景观网络模型，该模型将遗传分析与物种分布模型和人口统计数据相结合，以克服在整个年度周期中对迁徙物种的替代风险因素进行概念化的挑战。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)。尽管缺乏一些越冬地点的数据，但我们展示了如何使用这些结果来帮助优先保护繁殖和越冬地区。例如，我们表明，当遗传、人口统计、和网络建模结果一起考虑很明显，保护建议将根据目标是保护独特的遗传谱系还是单位面积最大数量的鸟类而有所不同。更具体地说，如果保护基因谱系是目标，那么有限的资源应集中用于保护加利福尼亚山脉、落基山脉或加利福尼亚沿海地区的栖息地，那里有 3 个最脆弱的基因谱系繁殖，或者在墨西哥西部，其中有 2 个。 3个最脆弱的血统越冬。或者，如果目标是在每单位面积上保护最大数量的个体，那么应该将有限的保护资金投入到估计密度最高的太平洋西北部或中美洲。全面的，我们的结果证明了采用基于遗传的网络模型在广阔的地理范围内整合多种类型的数据的实用性，并更好地为迁徙动物的保护决策提供信息。文章影响声明：基因景观网络模型可以促进整个年度周期中迁徙动物的保护优先级。本文受版权保护。版权所有。