Dissecting phylogenetic fuzzy weighting: theory and application in metacommunity phylogenetics
Dissecting phylogenetic fuzzy weighting: theory and application in metacommunity phylogenetics
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DOI：
10.1111/2041-210x.12547
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发表时间：
2016-08-01
影响因子：
6.6
通讯作者：
Pillar, Valerio D.
中科院分区：
文献类型：
--
作者：
Duarte, Leandro D. S.;Debastiani, Vanderlei J.;Pillar, Valerio D.
元群落系统发育学旨在评估驱动进化枝分布的环境和/或历史因素。系统发育模糊加权（PFW）基于物种间系统发育亲缘关系定义的模糊集来描述进化枝在元群落中的分布。该方法能够分析进化枝分布的环境和/或生物地理决定因素。PFW还提供了一种探索性工具，通过系统发育结构主坐标（pps）来可视化进化支的分布。在本文中，我们描述了PFW的理论特性和生物学背景，并与其他系统多样性方法（COMDIST， COMDISTNT, Rao's H和UniFrac）比较，评估了其在评估物种分布的环境和系统发育决定因素方面的统计性能（I型误差和统计功率）。通过(i)模拟不同物种聚集情景（受环境和/或系统发育影响或不受影响的物种分布）、生态位宽度容忍度和物种池大小的元群落，对PFW和其他系统多样性指标的统计性能进行了测试；（ii）向PFW提交群落矩阵，并得出群落（D-P）和pps之间的成对系统发育差异；（iii）将这些指标和其他系统多样性方法提交给不同的分析方法（Mantel测试，对不同矩阵的回归- ADONIS和GLM），以评估环境和系统发育对元群落系统发育结构的影响；（iv）通过替代排列程序估计I型误差和功率估计。结果表明，PFW对物种分布的环境和系统发育驱动因素提供了可靠的评估。尽管所有方法在Mantel测试和ADONIS测试中都有可接受的I型误差，但只有PFW在两种测试中都显示出可接受的功率。Rao的H只对Mantel测试有可接受的功率，而COMDIST只对ADONIS测试有可接受的功率。COMDISTNT和UniFrac在这两项测试中的统计性能都很差。相反，GLM仅对第一个pps具有可接受的功率。在D-P上执行ADONIS提供了对物种分布的环境和系统发育驱动因素的全面评估。另一方面，通过ADONIS拒绝零假设后进行ppps分析，可以识别与环境梯度主要相关的系统发育节点。PFW能够综合和分析元群落的系统发育模式，从而更全面地了解物种分布的生态和进化驱动因素。
Metacommunity phylogenetics aims at evaluating environmental and/or historical factors driving clade distribution. Phylogenetic fuzzy weighting (PFW) describes clade distribution across metacommunities based on fuzzy sets defined by phylogenetic relatedness among species. The method enables analysing environmental and/or biogeographic determinants of clade distribution. PFW also offers an exploratory tool for visualizing clade distribution via Principal Coordinates of Phylogenetic Structure (PCPS). In this article, we describe the theoretical properties and biological backgrounds of PFW and evaluate its statistical performance (type I error and statistical power) in assessing environmental and phylogenetic determinants of species distribution in comparison with other phylobetadiversity methods (COMDIST, COMDISTNT, Rao's H and UniFrac). The statistical performance of PFW and the other phylobetadiversity metrics was tested by (i) simulating metacommunities under different species assembly scenarios (species distribution influenced or not by environment and/or phylogeny), niche breadth tolerance and species pool sizes; (ii) submitting community matrices to PFW and deriving pairwise phylogenetic dissimilarities between communities (D-P) and PCPS; (iii) submitting these metrics and the other phylobetadiversity methods to different analytical approaches (Mantel test, regression on dissimilarity matrices - ADONIS, and GLM) to evaluate the influence of environment and phylogeny on metacommunity phylogenetic structure; and (iv) estimating type I error and power estimates via alternative permutation procedures. Results demonstrated that PFW provides robust assessment of environmental and phylogenetic drivers of species distribution across metacommunities. Although all methods had acceptable type I error for both Mantel test and ADONIS, only PFW showed acceptable power for both tests. Rao's H had acceptable power only for Mantel test, while COMDIST had acceptable power only for ADONIS. COMDISTNT and UniFrac showed poor statistical performance for both tests. Conversely, GLM had acceptable power only for the first PCPS. Performing ADONIS on D-P provides a robust overall assessment of environmental and phylogenetic drivers of species distribution. On the other hand, performing PCPS analysis after rejecting the null hypotheses via ADONIS allows identifying the phylogenetic nodes mostly associated with environmental gradients. PFW enables synthesizing and analysing phylogenetic patterns in metacommunities, allowing attaining a more complete portrait of ecological and evolutionary drivers of species distribution.