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在估计物种-区域关系和β-多样性时,考虑不完美的检测
Ciar D Noble1, Carlos A Peres1,2, James J Gilroy1
1School of Environmental Sciences University of East Anglia Norwich, Norfolk UK.
Ecology and evolution
|July 11, 2024
概括
在生态研究中不完善的检测会影响生物多样性指标,如物种区域关系 (SARs) 和β多样性. 虽然一些方法提供了部分纠正,但多种占用模型 (MSOM) 显示了准确的β多样性评估的前景.
科学领域:
- 生态生态学 生态生态学
- 生物多样性科学 生物多样性科学
- 保护生物学 保护生物学
背景情况:
- 生态学家传统上使用观察到的物种计数来量化生物多样性模式,例如物种区域关系 (SARs) 和β多样性.
- 不完善的检测,当不记录所有存在的物种时,可以在这些基本的生态指标和随后的社区模型中引入重大偏差.
- 目前用于纠正不完善检测的现有统计方法尚未在SAR和β多样性研究中严格评估其性能.
研究的目的:
- 调查由于检测不完善而导致的SARS和β多样性参数估计不准确性的程度.
- 评估非参数多样性估计器 (iNEXT.3D) 和多物种占用模型 (MSOMs) 在缓解这些检测相关偏差方面的有效性.
- 评估不完善检测对SAR系数估计的影响以及补丁面积对β多样性的影响.
主要方法:
- 模拟了2835个分散社区的28350个采样制度,操纵检测概率和采样重复.
- 在不同的检测概率下,SAR模型系数的量化偏差,准确性和精度以及对对的索伦森相似性估计.
- 对比了观测计数,iNEXT.3D和MSOMs在纠正不完美的检测偏差方面的性能.
主要成果:
- 不完美的检测系统地偏差了所有评估的参数,特别是在低检测概率和少量的采样重复的情况下.
- 观测计数低估了物种丰富度和SAR z值,高估了c值; iNEXT.3D和MSOM仅为SARs提供了部分偏差校正.
- 与观测计数和iNEXT.3D不同的是,MSOM提供了对beta多样性模型系数的公正估计,即使在非最佳条件下也是如此.
结论:
- 不完善的检测对物种区域关系研究的可靠性构成重大威胁,即使使用像iNEXT.3D.这样的高级估计器,也会如此.
- MSOM对于准确的β多样性评估至关重要,有效地纠正影响其他方法的区域相关偏差.
- 增加采样工作对于提高所有生物多样性估计方法的性能至关重要,强调需要适当的采样设计.
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