Biodiversity and Climate Research Centre (BiK-F) by Senckenberg Research Institut & Goethe University, Senckenberganlage 25, D-60325, Frankfurt/Main, Germany.
BMC Evol Biol. 2012 Nov 24;12:224. doi: 10.1186/1471-2148-12-224.
While research on the impact of global climate change (GCC) on ecosystems and species is flourishing, a fundamental component of biodiversity - molecular variation - has not yet received its due attention in such studies. Here we present a methodological framework for projecting the loss of intraspecific genetic diversity due to GCC.
The framework consists of multiple steps that combines 1) hierarchical genetic clustering methods to define comparable units of inference, 2) species accumulation curves (SAC) to infer sampling completeness, and 3) species distribution modelling (SDM) to project the genetic diversity loss under GCC. We suggest procedures for existing data sets as well as specifically designed studies. We illustrate the approach with two worked examples from a land snail (Trochulus villosus) and a caddisfly (Smicridea (S.) mucronata).
Sampling completeness was diagnosed on the third coarsest haplotype clade level for T. villosus and the second coarsest for S. mucronata. For both species, a substantial species range loss was projected under the chosen climate scenario. However, despite substantial differences in data set quality concerning spatial sampling and sampling depth, no loss of haplotype clades due to GCC was predicted for either species.
The suggested approach presents a feasible method to tap the rich resources of existing phylogeographic data sets and guide the design and analysis of studies explicitly designed to estimate the impact of GCC on a currently still neglected level of biodiversity.
虽然关于全球气候变化 (GCC) 对生态系统和物种影响的研究正在蓬勃发展,但生物多样性的一个基本组成部分——分子变异——在这些研究中尚未得到应有的重视。在这里,我们提出了一种用于预测 GCC 导致的种内遗传多样性丧失的方法框架。
该框架由多个步骤组成,结合了 1) 分层遗传聚类方法来定义可比较的推断单位,2) 物种积累曲线 (SAC) 来推断采样完整性,和 3) 物种分布模型 (SDM) 来预测 GCC 下的遗传多样性损失。我们为现有数据集以及专门设计的研究提出了程序。我们用两个来自陆地蜗牛 (Trochulus villosus) 和石蛾 (Smicridea (S.) mucronata) 的实例来说明这种方法。
对于 T. villosus,采样完整性在第三个最粗的单倍型分支水平上进行诊断,对于 S. mucronata,在第二个最粗的水平上进行诊断。对于这两个物种,在所选择的气候情景下,预计会有大量的物种范围损失。然而,尽管在空间采样和采样深度方面的数据集质量存在显著差异,但对于这两个物种,都没有预测到由于 GCC 导致的单倍型分支损失。
所提出的方法为利用现有的系统地理学数据集的丰富资源提供了一种可行的方法,并指导了旨在估计 GCC 对目前仍被忽视的生物多样性水平的影响的研究的设计和分析。