使用比较灭绝风险分析来优先考虑IUCN红色名单对两动物的重新评估
Pablo Miguel Lucas1,2, Moreno Di Marco1, Victor Cazalis3,4
1Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Rome, Italy.
概括
国际自然保护联盟 (IUCN) 红色名单 (RL) 上的物种的保护评估可以自动化. 这项研究使用集体建模来预测哪些物种需要重新评估,有效地优先考虑保护工作和资源.
科学领域:
- 保护生物学 保护生物学
- 生物多样性评估评估
- 计算生态学计算生态学
背景情况:
- 国际自然保护联盟 (IUCN) 红色名单 (RL) 对保护政策和减少生物多样性丧失至关重要.
- 目前的RL评估方法资源密集,难以更新新物种数据.
- 自动预测方法为保持最新的物种评估提供了有效的替代方案.
研究的目的:
- 预测哪些两动物物种最有可能改变其IUCN红色名单 (RL) 类别.
- 通过自动化方法确定应优先进行重新评估的物种.
- 开发和验证用于RL类别预测的集合建模框架.
主要方法:
- 使用物种生物特征,环境变量和气候/土地利用变化代理作为预测因素.
- 采用了组合预测方法,结合了四种不同的模型算法 (累积链接模型,家族遗传学概括最小平方,随机森林,神经网络).
- 通过将组合预测与观察到的IUCN红色名单 (RL) 类别进行比较来确定优先物种,考虑到模型不确定性.
主要成果:
- 对于RL类别变化的最重要的预测因素包括物种的范围大小,范围配置,生物特征和气候/土地利用变化.
- 综合建模方法有效地预测了可能改变其IUCN红色名单 (RL) 状态的物种.
- 与独立的IUCN RL重新评估相比,开发的优先级指数和预测的RL变化显示出高性能.
结论:
- 集合建模是IUCN红色名单 (RL) 重新评估物种优先级的强大工具,有效地管理模型不确定性.
- 这种方法适用于各种类型和规模 (区域,国家) 以优化保护资源分配.
- 自动预测方法提高了最新的IUCN红色名单 (RL) 的维护,这对全球生物多样性保护至关重要.
关键词:
国际自然保护联盟 (IUCN) 表示.国际自然保护联盟红色名单在UICN的红色名单上.在UICN中,UICN代表的是UICN.两动物两动物它们是无线生物.进行比较分析.气候变化 气候变化 气候变化气候变化 气候变化 气候变化进行比较分析.组合模型组合模型组合模型灭绝的风险 灭绝的风险组装模型组装模型优先考虑优先考虑.优先考虑优先考虑.灭绝的风险 灭绝的风险更多相关视频
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