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采样方法对鸟物种息地适宜性建模产生影响
Sarah M Gaulke1, Tara Hohoff1, Brittany A Rogness1
1Illinois Natural History Survey, Prairie Research Institute University of Illinois Urbana-Champaign Champaign Illinois USA.
Ecology and evolution
|June 12, 2023
概括
不同的野生动物调查数据类型可以创建具有不同偏差的息地适应性模型 (HSM). 只有活跃数据最能识别蝙蝠息地,但模型重叠有显著差异,突出需要考虑保护的检测偏差.
科学领域:
- 野生动物生态学野生动物生态学
- 保护生物学 保护生物学
- 生态建模 生态建模
背景情况:
- 技术进步提供了新的野生动物调查方法.
- 息地适应性模型 (HSM) 对于保护规划至关重要.
- 用于HSM的各种数据类型可以引入偏见.
研究的目的:
- 调查不同数据类型如何影响息地适应性模型 (HSM).
- 评估检测偏差对三种蝙蝠物种的HSM的影响.
- 为了比较来自仅被动,仅活动和组合发生数据的HSM.
主要方法:
- 对三种蝙蝠物种 (Lasiurus borealis,Lasiurus cinereus,Perimyotis subflavus) 的息地适宜性模型 (HSM) 的比较.
- 使用仅被动 (声学) 和仅主动 (雾网,风力轮机死亡率) 的发生数据.
- 分析了模型重叠和不同数据类型的区分能力.
主要成果:
- 只有活跃的模型显示出发生和存在/缺席的最高分辨能力.
- 在数据类型之间,HSM 利基重叠的差异很大 (最大为 45%).
- 被动模型倾向于农业地区;积极模型倾向于森林,表明采样偏差.
结论:
- 检测和调查偏差显著影响HSM,特别是在结合数据时.
- 不同的数据类型产生了实质上不同的息地适合性预测.
- 当使用HSM进行管理决策时,请仔细考虑检测偏差.
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