Avoid non-probability sampling to select population monitoring sites: Comment on McClure and Rolek (2023)

IF 6.3 2区 环境科学与生态学 Q1 ECOLOGY Methods in Ecology and Evolution Pub Date : 2024-07-09 DOI:10.1111/2041-210X.14380
Jan Perret, Fabien Laroche, Guillaume Papuga, Aurélien Besnard
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避免使用非概率抽样来选择种群监测点:对 McClure 和 Rolek(2023 年)的评论
由于不可能对研究区域内的所有地点进行调查,因此种群监测计划通常依赖于抽样调查。在这种情况下,为获得无偏见的种群趋势估计值,一般建议采用概率取样法选择监测点。不过,在实践中,不以概率抽样为基础的地点选择也很常见,例如在监测计划开始时选择个体数量最多的地点。尽管如此,这些方法仍有可能获得有偏差的趋势估计值。McClure & Rolek(2023 年)通过模拟,研究了三种非概率采样选址方法在某些特定条件下能否获得无偏的趋势估计值。对于其中的两种方法,即选择高质量地点和选择已知有人居住的地点,作者得出结论认为,获得有偏差的趋势估计值存在很大风险。对于第三种方法,即选择初始丰度最大的地点,他们发现可以获得无偏估计值的条件。他们的结论是,应修改使用概率抽样的一般建议。在此,我们要说明的是,尽管作者的研究结果完全正确,但并不能证明这一建议无效。首先,我们指出,作者在模拟中对种群的功能做了很强的假设,特别是所有地点的丰度年际变异是相似的,而这在大多数真实种群中是不可能的。我们通过简单的模拟表明,即使稍微放宽这一假设,作者的结果也会失效。我们还指出,对于作者提出的大多数假设,在研究开始时通常并不知道这些假设是否会得到遵守。此外,作者也没有提供证据表明,与概率抽样方法相比,根据高初始丰度选择地点会带来更精确的趋势估计。因此,这种方法的益处和风险都不得而知。我们的结论是,在提供证据证明基于丰度的地点选择能提高估算精度,以及明确确定在哪些情况下使用这种方法能提供无偏的估算结果之前,应继续使用概率取样法。
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来源期刊
CiteScore
11.60
自引率
3.00%
发文量
236
审稿时长
4-8 weeks
期刊介绍: A British Ecological Society journal, Methods in Ecology and Evolution (MEE) promotes the development of new methods in ecology and evolution, and facilitates their dissemination and uptake by the research community. MEE brings together papers from previously disparate sub-disciplines to provide a single forum for tracking methodological developments in all areas. MEE publishes methodological papers in any area of ecology and evolution, including: -Phylogenetic analysis -Statistical methods -Conservation & management -Theoretical methods -Practical methods, including lab and field -This list is not exhaustive, and we welcome enquiries about possible submissions. Methods are defined in the widest terms and may be analytical, practical or conceptual. A primary aim of the journal is to maximise the uptake of techniques by the community. We recognise that a major stumbling block in the uptake and application of new methods is the accessibility of methods. For example, users may need computer code, example applications or demonstrations of methods.
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