A multifaceted approach to analyzing taxonomic, functional, and phylogenetic b-diversity.

Ecological literature offers a myriad of methods for quantifying b-diversity. One such methods is determining BDtotal (BD), which, unlike other methods, can be decomposed into meaningful components that indicate how unique a sampling unit is regarding its composition (local contribution) and how unique a species is regarding its occurrence in the community (species contribution). Despite this advantage, the original formulation of the BD metric only assesses taxonomic variation and neglects other important dimensions of biodiversity. We expanded the original formulation of BD to capture variation in the functional and phylogenetic dimensions of community data by computing two new metrics - BDFun and BDPhy - as well as their respective components that represent the local and species contribution. We tested the statistical performance of these new metrics for capturing variation in functional and phylogenetic composition through simulated communities and illustrated the potential use of these new metrics by analyzing b-diversity of stream fish communities. Our results demonstrated that BDPhy and BDFun have acceptable type I error and great power to detect the effect of deep evolutionary relationships and attributes mediating patterns of b-diversity. The empirical example illustrated how BDPhy and BDFun reveal complementary aspects of b-diversity relative to the original BD metric. These new metrics can be used to identify local communities that are of conservation importance because they represent unique functional, phylogenetic and taxonomic compositions. We conclude that BDPhy and BDFun are important tools for providing complementary information in the investigation of the structure of biological communities.

[1]  Stéphane Dray,et al.  Assessing the effects of spatial contingency and environmental filtering on metacommunity phylogenetics , 2012 .

[2]  Y. Súarez,et al.  Functional and phylogenetic dimensions are more important than the taxonomic dimension for capturing variation in stream fish communities , 2018 .

[3]  P. Legendre,et al.  Variation in compositional and structural components of community assemblage and its determinants , 2019, Journal of Vegetation Science.

[4]  C. Braak,et al.  Matching species traits to environmental variables: a new three-table ordination method , 1996, Environmental and Ecological Statistics.

[5]  V. Pillar,et al.  Dissecting phylogenetic fuzzy weighting: theory and application in metacommunity phylogenetics , 2016 .

[6]  Wilfried Thuiller,et al.  Combining the fourth-corner and the RLQ methods for assessing trait responses to environmental variation. , 2014, Ecology.

[7]  J. Ni,et al.  Treeline composition and biodiversity change on the southeastern Tibetan Plateau during the past millennium, inferred from a high-resolution alpine pollen record , 2019, Quaternary Science Reviews.

[8]  A. Kerkhoff,et al.  Microbes on mountainsides: Contrasting elevational patterns of bacterial and plant diversity , 2008, Proceedings of the National Academy of Sciences.

[9]  Pedro Peres-Neto,et al.  Metacommunity phylogenetics: separating the roles of environmental filters and historical biogeography. , 2010, Ecology letters.

[10]  A. Baselga Partitioning the turnover and nestedness components of beta diversity , 2010 .

[11]  F. Valente‐Neto,et al.  Metacommunity detectives: Confronting models based on niche and stochastic assembly scenarios with empirical data from a tropical stream network , 2018 .

[12]  R. Dierckx,et al.  Radiopharmaceuticals for imaging chronic lymphocytic inflammation , 2007 .

[13]  Wilfried Thuiller,et al.  Spatial mismatch and congruence between taxonomic, phylogenetic and functional diversity: the need for integrative conservation strategies in a changing world. , 2010, Ecology letters.

[14]  R. Whittaker Vegetation of the Siskiyou Mountains, Oregon and California , 1960 .

[15]  P. Legendre,et al.  ANALYZING BETA DIVERSITY: PARTITIONING THE SPATIAL VARIATION OF COMMUNITY COMPOSITION DATA , 2005 .

[16]  Mathieu Fourment,et al.  PATRISTIC: a program for calculating patristic distances and graphically comparing the components of genetic change , 2006, BMC Evolutionary Biology.

[17]  Jonathan M. Chase,et al.  Navigating the multiple meanings of β diversity: a roadmap for the practicing ecologist. , 2011, Ecology letters.

[18]  J. Heino,et al.  Species‐poor and low‐lying sites are more ecologically unique in a hyperdiverse Amazon region: Evidence from multiple taxonomic groups , 2018 .

[19]  T. Davies,et al.  Phylogenetic diversity patterns in Himalayan forests reveal evidence for environmental filtering of distinct lineages , 2018 .

[20]  Peter R. Minchin,et al.  Simulation of multidimensional community patterns: towards a comprehensive model , 1987, Vegetatio.

[21]  Tom Leinster,et al.  Measuring diversity: the importance of species similarity. , 2012, Ecology.

[22]  Pierre Legendre,et al.  Beta diversity as the variance of community data: dissimilarity coefficients and partitioning. , 2013, Ecology letters.

[23]  C. Graham,et al.  Phylogenetic beta diversity: linking ecological and evolutionary processes across space in time. , 2008, Ecology letters.

[24]  J. Diniz‐Filho,et al.  Analyzing community-weighted trait means across environmental gradients: should phylogeny stay or should it go? , 2018, Ecology.

[25]  V. Pillar,et al.  A framework for metacommunity analysis of phylogenetic structure. , 2010, Ecology letters.

[26]  P. Legendre,et al.  RELATING BEHAVIOR TO HABITAT: SOLUTIONS TO THEFOURTH-CORNER PROBLEM , 1997 .

[27]  V. Pillar,et al.  Discriminating trait‐convergence and trait‐divergence assembly patterns in ecological community gradients , 2009 .

[28]  Leandro da Silva Duarte,et al.  Phylogenetic habitat filtering influences forest nucleation in grasslands , 2011 .

[29]  D. Faith,et al.  Global conservation of phylogenetic diversity captures more than just functional diversity , 2019, Nature Communications.

[30]  F. Jiguet,et al.  Beyond taxonomic diversity patterns: how do α, β and γ components of bird functional and phylogenetic diversity respond to environmental gradients across France? , 2011 .