优先重新评估国际自然保护联盟 (IUCN) 红色名单上数据不足的物种
Victor Cazalis1,2, Luca Santini3, Pablo M Lucas3
1German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
概括
一种新方法有助于优先重新评估国际自然保护联盟红色名单中数据不足 (DD) 物种. 这种方法识别了可能有足够数据的物种,改善了保护政策和全球生物多样性评估.
科学领域:
- 保护生物学 保护生物学
- 生物多样性评估评估
- 种类红色名单 种类红色名单
背景情况:
- 国际自然保护联盟 (IUCN) 红色名单对保护政策至关重要.
- 很大一部分 (14%) 的物种被归类为数据不足 (DD),限制了红色名单的实用性.
- 需要强大的方法来识别可能被重新分类到数据充足的类别的DD物种.
研究的目的:
- 开发和测试一种可重复的方法,优先重新评估国际自然保护联盟红色名单上数据不足的物种.
- 为了确定哪些缺乏数据的物种在重新评估后最有可能被重新分类到具有足够数据的IUCN红色名单类别.
主要方法:
- 设计了一种方法来计算6887种缺乏数据的哺乳动物,爬行动物,两动物,鱼类和类动物的重新评估到数据充足的类别的概率.
- 共同变量包括可用的知识 (事件记录,出版物),知识代理 (范围偏远) 和物种特征 (夜间活动).
- 还评估了基于息地丧失的重新评估概率和潜在威胁状况的变化.
主要成果:
- 1907个物种显示,被重新评估为数据充足的类别的概率大于0.5.
- 自上次评估以来,624种物种的这种概率增加了0.25以上.
- 77种物种被确定为可能符合近期危或危类别的物种,原因是最近的息地丧失.
结论:
- 开发的方法有效地识别了数据不足的物种,这些物种可能有足够的数据进行重新评估.
- 优先考虑这些物种可以显著提高IUCN红色名单的全面性和代表性.
- 这种方法通过将资源集中在最有可能产生最新的灭绝风险信息的物种上,有助于保护工作.
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