种类分布模型的潜力,以区分源种群和水槽
Bilgecan Şen1,2, Christian Che-Castaldo3, H Reşit Akçakaya1
1Department of Ecology and Evolution, Stony Brook University, Stony Brook, New York, USA.
The Journal of animal ecology
|October 21, 2024
概括
物种分布模型 (SDM) 预测人口增长很差,但可以区分来源和沉没种群. 息地适宜性可能表明一个群体能够维持自身,帮助保护工作的能力.
科学领域:
- 生态生态学 生态生态学
- 保护生物学 保护生物学
- 人口动态 人口动态
背景情况:
- 物种分布模型 (SDM) 在保护中被广泛用于预测物种发生情况.
- 然而,它们预测内在增长率或区分源与沉种群的能力仍然被低估.
- 这种知识差距阻碍了依赖于超人口动态的有效保护管理.
研究的目的:
- 评估SDM估计的息地适宜性是否可以预测物种的内在生长率和丰度.
- 评估SDM在区分源和沉积点种群方面的表现.
- 为了比较两个SDM方法,增强回归树 (BRT) 和通用线性模型 (GLM),以他们的预测能力.
主要方法:
- 从17种美国鸟类的标记捕获研究中收集了17种美国鸟类的内在生长和丰度数据.
- 使用eBird的存在数据和10个环境变量开发了SDM.
- 在SDM构建中使用BRT和GLM,并使用线性回归和AUC来分析人口预测和源/下沉歧视.
主要成果:
- SDM解释了内在生长率和丰度的最小空间变化 (中位数R2 ≈0.1).
- 无论是BRT还是GLM,都显示出区分源种群和沉种群的潜力 (AUC>0.7在13种物种中的7种).
- 与沉没种群相比,SDM一致估计源种群的息地适合性更高.
结论:
- 用机会性数据构建的SDM对物种人口统计的预测能力有限.
- 息地适宜性显示出作为识别自给自足 (源) 种群的指标的希望.
- 跨多种类型的进一步研究至关重要,以验证和完善SDM在保护中的使用,以确定种群生存能力.
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