4.8 Article

Individual heterozygosity predicts translocation success in threatened desert tortoises

Journal

SCIENCE
Volume 370, Issue 6520, Pages 1086-+

Publisher

AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/science.abb0421

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Funding

  1. Bureau of Land Management Las Vegas Field Office
  2. NSF

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Anthropogenic environmental modification is placing as many as 1 million species at risk of extinction. One management action for reducing extinction risk is translocation of individuals to locations from which they have disappeared or to new locations where biologists hypothesize they have a good chance of surviving. To maximize this survival probability, the standard practice is to move animals from the closest possible populations that contain presumably related individuals. In an empirical test of this conventional wisdom, we analyzed a genomic dataset for 166 translocated desert tortoises (Gopherus agassizii) that either survived or died over a period of two decades. We used genomic data to infer the geographic origin of translocated tortoises and found that individual heterozygosity predicted tortoise survival, whereas translocation distance or geographic unit of origin did not. Our results suggest a relatively simple indicator of the likelihood of a translocated individual's survival: heterozygosity.

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Response to Comment on Individual heterozygosity predicts translocation success in threatened desert tortoises

Peter A. Scott, Linda J. Allison, Kimberleigh J. Field, Roy C. Averill-Murray, H. Bradley Shaffer

Summary: Hedrick raises potential concerns that he believes challenge or limit the main finding, focusing on unknown ecological aspects of the translocated tortoises. However, we believe these concerns do not bias the results or interpretation as presented in our original paper.

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Summary: The main finding suggests that genetic rescue should not solely focus on genetic diversity, but also consider the genetic load and representation of population diversity in translocated individuals. However, these recommendations are based on specific model assumptions and fitness effects, which may not be applicable to all endangered species.

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