将比较方法应用于不同的数据库:从哺乳动物物种的人口统计分析中得到的教训

J. Gaillard, Victor Ronget, J. Lemaitre, C. Bonenfant, G. Péron, P. Capdevila, Marlène Gamelon, R. Salguero‐Gómez
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引用次数: 1

摘要

比较人口统计学分析的目的是确定生命率的变化轴和决定物种沿这些轴的位置的因素。这些分析可以使用不同的主要数据集来执行,这些数据集在数据质量和结构上具有明显的异质性。人口统计学比较分析的结果是否取决于所使用的数据库,因为进化生态学的理论预测不是那么可靠,取决于所分析的物种集,或者因为数据限制阻止了预期模式的识别,这一点从未被调查过。本章通过从两个不同的数据库(Comadre和maldaba)中对哺乳动物物种进行比较人口统计学分析来填补这一知识空白,这两个数据库是为不同的目的而建立的。本章首先估计了每个数据库的一些人口统计指标,分析了它们的异速生长关系,并通过进行系统发育回归将估计与理论预期进行了比较。与Comadre相比,使用maldaba导致了更强的异速生长关系,更接近于期望。此外,在不同的数据库中,无量纲人口指标对人口轨迹形状变化轴的贡献是不同的。本章的研究结果证明了年龄依赖性在哺乳动物物种人口统计策略形成中的关键作用,并强调了根据所问问题仔细选择数据库和使用指标的必要性。作者的分析很好地说明了不同的数据库可以用来解决关于生活史变化的不同问题,而不是对立的数据库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applying comparative methods to different databases: lessons from demographic analyses across mammal species
Comparative demographic analyses aim to identify axes of variation in vital rates and the factors that determine the position of species along these axes. These analyses can be performed using different primary data sets, with marked heterogeneity in data quality and structure. Whether the outcome of demographic comparative analyses depends on the database used because theoretical predictions of evolutionary ecology are not that robust and depend on the set of species analysed or because data limitation prevents the identification of the expected patterns has never been investigated. This chapter fills this knowledge gap by performing a comparative demographic analysis across mammalian species from two distinct databases (Comadre and Malddaba) that were built for different purposes. The chapter first estimates some demographic metrics for each database, analyses their allometric relationships, and compares the estimates with theoretical expectations by performing phylogenetic regressions. Using Malddaba led to stronger allometric relationships closer to the expectation than Comadre. Moreover, the contribution of dimensionless demographic metrics to axes of variation in the shape of demographic trajectories was different between databases. The findings in the chapter demonstrate the key role of age dependence in vital rates for shaping demographic tactics across mammalian species and highlight the need for carefully choosing the database and the metrics to use depending on the question asked. Instead of opposing databases, the authors’ analysis nicely illustrates that different databases could be used to address different questions about life history variation.
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