公民科学家的适应性采样提高了物种分布模型的性能:模拟研究

IF 6.3 2区 环境科学与生态学 Q1 ECOLOGY
Thomas Mondain-Monval, Michael Pocock, Simon Rolph, Tom August, Emma Wright, Susan Jarvis
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引用次数: 0

摘要

志愿记录者通过公民科学产生了大量生物多样性数据,这些数据被用于保护规划和政策决策。非结构化取样,即志愿者想记录什么就记录什么,想在哪里记录就在哪里记录,会导致这些数据在空间上的不均匀性。虽然有很多统计技术可以解释由此产生的偏差,但也有可能通过引导一部分记录者在信息量最大的地点进行采样来改进数据集,这就是所谓的适应性采样。我们利用模拟生态群落研究了适应性采样在改善基于公民科学数据建立的物种分布模型性能方面的潜力。我们根据当前的蝴蝶数据模拟了大不列颠的生态组合,并建立了每个物种的分布模型。然后,我们模拟了基于五种适应性采样方法(一种基于经验的方法,仅用于填补空白;四种基于模型的方法,使用模型输出中的各种测量方法)和一种非适应性方法(继续按照当前模式记录的方法)的新数据采样,并重新运行了物种分布模型。其中,我们还改变了根据适应性取样分配的记录工作的速率。将使用原始数据和适应性取样数据的模型预测结果与真实的物种分布进行比较,以评估每种方法的性能。我们发现,所有适应性取样方法都提高了模型性能,与经验取样方法(即简单的填补空白)相比,基于模型的方法提高最大。所有四种基于模型的自适应采样方法都为模型输出提供了类似的好处。当适应性取样量从无取样量变为 1%取样量时,模型性能的改善幅度最大,这表明只需要记录者行为的少量改变就能改善模型性能。根据模型输出的信息,将志愿记录者引导到最需要记录的地方,可以改善基于公民科学数据建立的物种分布模型,即使对建议地点的吸收率极低。因此,我们的研究结果表明,记录者的适应性采样对现实世界的公民科学数据集是有益的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Adaptive sampling by citizen scientists improves species distribution model performance: A simulation study

Adaptive sampling by citizen scientists improves species distribution model performance: A simulation study

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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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