The global protected area network does not harbor genetically diverse populations

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Authors

Chloé Schmidt , Eleana Karachaliou, Amy Vandergast, Eric Crandall, Jeff Falgout, Maggie Hunter, Francine Kershaw, Deborah Leigh, David O’Brien, Ivan Paz-Vinas, Gernot Segelbacher, Colin J Garroway

Abstract

Global biodiversity conservation targets include expanding protected areas and maintaining genetic diversity within species by 2030. However, the extent to which existing protected areas capture genetic diversity within species is unclear. We examined this question using a global sample of nuclear population-level genetic data comprising georeferenced genotypes from 2,513 local populations, 134,183 individuals, and 176 species of mammals and marine fish. We found that the existing protected area network does not capture populations with higher than average genetic diversity, and populations within protected areas are not more genetically differentiated than populations sampled elsewhere. This general trend does not preclude their effectiveness for specific species or regions currently, or in the future. While it may be desirable to prioritize regions with high genetic diversity when designating new protected areas, we caution that this will not be possible in many of the most at-risk regions of the world due to a lack of data. Continued focus on minimizing population decline and maintaining connectivity between protected areas remain essential considerations in area-based conservation for mediating genetic diversity loss.

DOI

https://doi.org/10.32942/X26G7Z

Subjects

Biodiversity, Evolution, Life Sciences

Keywords

biodiversity, Genetic diversity, genetic differentiation, effective population size conservation policy, genetic diversity, genetic differentiation, effective population size, conservation policy

Dates

Published: 2024-04-12 04:21

License

CC BY Attribution 4.0 International

Additional Metadata

Language:
English

Data and Code Availability Statement:
All data underlying this work are publicly available (see Methods). Code and analyzed datasets will be made available upon acceptance.