分类群出现数据的空间标准化--行动呼吁

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Gawain T. Antell, Roger B. J. Benson, Erin E. Saupe
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引用次数: 0

摘要

化石记录具有时空异质性:分类群出现数据的空间分布具有斑块性,这种斑块性随时间而变化。大规模的定量古生物学研究如果没有考虑到取样范围的不均匀性,轻则会得出缺乏信息的推论,重则会得出错误的结论。大规模化石数据集的分析需要明确的空间标准化方法,因为非空间样本标准化(如多样性稀释)不足以减少不同时间或不同环境和支系之间不同空间覆盖的信号。空间标准化既要控制化石地点的地理区域,也要控制化石地点的分散(扩散)。除了对数据的空间分布进行标准化之外,还可以对其他因素进行标准化,包括环境异质性或报告分类群出现的出版物或野外采集单位的数量。通过对已发表的全球古生物数据库中出现的生物进行案例研究,我们展示了强烈的采样信号;如果没有空间标准化,这些采样信号可能会被错误地归因于生物过程。我们讨论了通过子采样实现空间标准化的实际问题,并介绍了新的 R 软件包 divvy,以提高空间分析的可及性。该软件提供了三种空间子取样方法以及量化空间覆盖率的相关工具。在回顾了数据比较组之间空间覆盖率均衡化的理论、实践和历史之后,我们概述了在古生物学中改进相关数据收集、分析和报告实践的优先领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial standardization of taxon occurrence data—a call to action

The fossil record is spatiotemporally heterogeneous: taxon occurrence data have patchy spatial distributions, and this patchiness varies through time. Large-scale quantitative paleobiology studies that fail to account for heterogeneous sampling coverage will generate uninformative inferences at best and confidently draw wrong conclusions at worst. Explicitly spatial methods of standardization are necessary for analyses of large-scale fossil datasets, because nonspatial sample standardization, such as diversity rarefaction, is insufficient to reduce the signal of varying spatial coverage through time or between environments and clades. Spatial standardization should control both geographic area and dispersion (spread) of fossil localities. In addition to standardizing the spatial distribution of data, other factors may be standardized, including environmental heterogeneity or the number of publications or field collecting units that report taxon occurrences. Using a case study of published global Paleobiology Database occurrences, we demonstrate strong signals of sampling; without spatial standardization, these sampling signatures could be misattributed to biological processes. We discuss practical issues of implementing spatial standardization via subsampling and present the new R package divvy to improve the accessibility of spatial analysis. The software provides three spatial subsampling approaches, as well as related tools to quantify spatial coverage. After reviewing the theory, practice, and history of equalizing spatial coverage between data comparison groups, we outline priority areas to improve related data collection, analysis, and reporting practices in paleobiology.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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