Reintroduction programmes: genetic trade-offs for populations

Reintroduction programmes: genetic trade-offs for populations
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DOI:
10.1111/j.1469-1795.1999.tb00074.x
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发表时间:
1999-11-01
影响因子:
3.4
通讯作者:
Earnhardt, Joanne M.
Earnhardt, Joanne M.
中科院分区:
环境科学与生态学2区
文献类型:
--
作者:
Earnhardt, Joanne M.

文献摘要

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重新引入圈养管理的动物是保护野外灭绝的种群和物种的重要工具。由于遗传多样性可能会影响人口的持久性,重新引入和圈养种群的遗传组成是至关重要的。对于具有已知谱系的圈养管理物种,可以选择个体动物来创建具有特定遗传组成的重新引入种群。选择动物的五个遗传和人口统计学策略进行了测试的四个物种。选择策略的基础上确定的标准,在现场和理论研究。从圈养繁殖计划中模拟重新引入动物造成了基因冲突。在不同的策略中,一个亚群的遗传多样性增加与另一个亚群的遗传多样性变化呈负相关。例如,释放遗传上过度代表的动物是圈养繁殖计划最有益的策略,但为重新引入的种群提供了最少的遗传多样性。然而,不同的选择标准和不同的种群结构,种群之间的遗传多样性的增益和损失不同。由于每个物种的圈养繁殖历史各不相同,因此无法准确预测遗传组成的变化,也没有一种策略是普遍最佳的。因此,必须根据具体的方案目标评估每个人口的遗传权衡。
Reintroductions of captive-managed animals are a vital tool for the conservation of populations and species extinct in the wild. Because genetic diversity may impact population persistence, the genetic composition of reintroduced and captive populations is critical. For captive-managed species with known pedigrees, individual animals can be selected to create reintroduced populations with specific genetic compositions. Five genetic and demographic strategies for selecting animals were tested on four species. Selection strategies were based on criteria identified in field and theoretical studies. Simulated reintroductions of animals from captive-breeding programmes created a genetic conflict. Among the different strategies, increases in the genetic diversity of one subpopulation were negatively correlated with changes in the genetic diversity of the other subpopulation. For example, the release of genetically over-represented animals was the most beneficial strategy for a captive-breeding programme, but provided the least genetic diversity for the reintroduced population. However, gains and losses in genetic diversity between populations varied with different selection criteria and different population structures. Because captive-breeding histories vary for each species, changes in genetic composition cannot be accurately predicted and no one strategy is universally optimal. Thus, genetic trade-offs must be assessed for each population relative to specific programme goals.