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Title: A genoscape–network model for conservation prioritization in a migratory bird

Journal Article · · Conservation Biology
DOI:https://doi.org/10.1111/cobi.13536· OSTI ID:2333684
ORCiD logo [1];  [2];  [3];  [2];  [4]
  1. Colorado State University, Fort Collins, CO (United States); University of California, Los Angeles, CA (United States)
  2. University of California, Los Angeles, CA (United States)
  3. The Institute for Bird Populations, Point Reyes Station, CA (United States)
  4. Tulane University, New Orleans, LA (United States)

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.

Research Organization:
Univ. of California, Los Angeles, CA (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
Grant/Contract Number:
EE0009005
OSTI ID:
2333684
Journal Information:
Conservation Biology, Vol. 34, Issue 6; ISSN 0888-8892
Publisher:
Society for Conservation Biology - WileyCopyright Statement
Country of Publication:
United States
Language:
English

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