Probabilistic models of species discovery and biodiversity comparisons
Probabilistic models of species discovery and biodiversity comparisons
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DOI：
10.1073/pnas.1616355114
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发表时间：
2017-04-04
影响因子：
11.1
通讯作者：
Jablonski, David
中科院分区：
文献类型：
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作者：
Edie, Stewart M.;Smits, Peter D.;Jablonski, David
推断驱动生物多样性的大规模过程取决于对物种丰富度的系统发育和空间格局的理解。然而，分支和地理区域以不均匀的速度积累新描述的物种，可能影响目前观察到的多样性模式的稳定性。在这里，我们提出了一个物种发现的概率模型来评估进化枝和地区之间多样性水平的不确定性。我们使用贝叶斯时间序列回归估计了海洋双壳类物种描述率的长期趋势，发现新种积累存在明显的空间偏差。尽管存在这些偏差，未来物种丰富度的概率估计在目前观察到的区域多样性等级顺序中显示出相当大的稳定性。然而，丰富度的绝对差异仍有可能发生变化，这可能会改变物种数量与被认为促进生物多样性的地理、环境和生物因素之间的相关性。应用于扇贝及其相关分支，我们发现积累的深海物种知识可能会改变这三个科的相对丰富度，强调在其多样性的定量研究中需要考虑双壳类分类的不完整性。除了对观察到的多样性模式的预期变化进行估计外，本文所描述的模型还精确地指出了最迫切需要进行系统研究的地理区域和分支——这是建立更完整、更准确的生物多样性动态模型的重要实践，可以为生态学和进化理论提供信息，并改善保护实践。
Inferring large-scale processes that drive biodiversity hinges on understanding the phylogenetic and spatial pattern of species richness. However, clades and geographic regions are accumulating newly described species at an uneven rate, potentially affecting the stability of currently observed diversity patterns. Here, we present a probabilistic model of species discovery to assess the uncertainty in diversity levels among clades and regions. We use a Bayesian time series regression to estimate the long-term trend in the rate of species description for marine bivalves and find a distinct spatial bias in the accumulation of new species. Despite these biases, probabilistic estimates of future species richness show considerable stability in the currently observed rank order of regional diversity. However, absolute differences in richness are still likely to change, potentially modifying the correlation between species numbers and geographic, environmental, and biological factors thought to promote biodiversity. Applied to scallops and related clades, we find that accumulating knowledge of deep-sea species will likely shift the relative richness of these three families, emphasizing the need to consider the incomplete nature of bivalve taxonomy in quantitative studies of its diversity. Along with estimating expected changes to observed patterns of diversity, the model described in this paper pinpoints geographic areas and clades most urgently requiring additional systematic study-an important practice for building more complete and accurate models of biodiversity dynamics that can inform ecological and evolutionary theory and improve conservation practice.