Data from: Time-series analysis reveals genetic responses to intensive management of razorback sucker (Xyrauchen texanus)

Time-series analysis is used widely in ecology to study complex phenomena, and may have considerable potential to clarify relationships of genetic and demographic processes in natural and exploited populations. We explored the utility of this approach to evaluate population responses to management in razorback sucker, a long-lived and fecund, but declining freshwater fish species. A core population in Lake Mohave (Arizona-Nevada, USA) has experienced no natural recruitment for decades, and is maintained by harvesting naturally produced larvae from the lake, rearing them in protective custody, and repatriating them at sizes less vulnerable to predation. Analyses of mtDNA and 15 microsatellites characterized for sequential larval cohorts collected over a 15-year time series revealed no changes in geographic structuring, but indicated significant increase in mtDNA diversity for the entire population over time. Likewise, ratios of annual effective breeders to annual census size (Nb/Na) increased significantly despite seven-fold reduction of Na. These results indicated that conservation actions diminished near-term extinction risk due to genetic factors, and should now focus on increasing numbers of fish in Lake Mohave to ameliorate longer-term risks. More generally, time series analysis permitted robust testing of trends in genetic diversity, despite low precision of some metrics.时间序列分析（time-series analysis）在生态学领域被广泛应用于复杂现象研究，其在阐明自然种群与渔业开发种群的遗传过程及种群动态过程间的关联方面，具备可观的应用潜力。本研究探讨了该方法在评估锐背吸口鲤（razorback sucker）种群对管理措施响应方面的应用价值——该物种为长寿且繁殖力较强的淡水鱼类，但种群数量正持续下降。位于美国亚利桑那州与内华达州交界的莫哈韦湖（Lake Mohave）中的核心种群数十年来未发生自然补充，其种群维持依赖于从湖中采集自然繁育的幼鱼，在人工保护条件下培育至不易被捕食的体型后再放归湖中。对15年时间序列内按时间顺序采集的各批次幼鱼群开展的线粒体DNA（mtDNA）与15个微卫星位点（microsatellites）分析结果显示，种群的地理结构未发生变化，但整体种群的mtDNA多样性随时间推移出现了显著提升。同样，尽管年度普查个体数（Na）下降了7倍，年度有效繁殖个体数与年度普查个体数的比值（Nb/Na）仍出现了显著提升。上述结果表明，此次保护行动降低了由遗传因素导致的短期灭绝风险，后续工作应聚焦于提升莫哈韦湖中的鱼类种群数量，以缓解长期存续风险。从更广泛的视角来看，尽管部分监测指标的精度有限，时间序列分析仍可对遗传多样性的变化趋势开展稳健的检验。