Surveys that prioritize site number over time per site will result in better gastropod status assessments: a case study on the rediscovery of Big Black Rocksnail

Calvin R. Rezac, Robert J. Ellwanger, Samantha A. Donohoo, Paul D. Hartfield, Ashley S. Ruppel, David S. Ruppel, Matthew D. Wagner,Nathan V. Whelan

Biodiversity and Conservation(2024)

引用 0|浏览0
暂无评分
摘要
Freshwater gastropods are among the most imperiled organisms on Earth. Yet, they are among the most understudied freshwater taxa. Numerous freshwater gastropod species have gone extinct in the last 100 years, but recent rediscoveries indicate that some species were prematurely declared extinct. Such premature extinction declarations remove legal protections, which could facilitate actual extinction. Thus, research and policy recommendations are needed so surveys provide the best information possible for conservation. Here, we examined the case of Lithasia hubrichti, a freshwater gastropod endemic to the Big Black River in Mississippi that was last seen in 1965. In 2022, a freshwater mollusk survey resulted in finding L. hubrichti alive. An additional survey effort in 2023 that prioritized sampling as many sites as possible in a single day clarified the current range of L. hubrichti. Genomic analyses indicated that the species has persisted with a large population size for thousands of years, rather than ever falling below a survey detection limit. When considering the case of L. hubrichti and other recent freshwater gastropod rediscoveries, we conclude that freshwater gastropod surveys should emphasize sampling as many sites as possible under favorable sampling conditions when targeting rare species, rather than expending high sampling effort at a small number of sites or when stream conditions may impact ability to detect target species. We also advocate for policies that encourage partnerships with landowners, which was required to rediscover L. hubrichti.
更多
查看译文
关键词
Conservation genomics,Demographic modeling,Extinction,Survey design,Pleuroceridae,RAD-seq
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要