Phylogenetic and Functional Beta Diversity

  • Nathan G. Swenson
Chapter
Part of the Use R! book series (USE R)

Abstract

The first objective of this chapter is to introduce the conceptual and empirical background for why phylogenetic and functional analyses of beta diversity are of interest to ecologists. This is followed by detailed instructions on how to calculate in R the major metrics of phylogenetic and functional beta diversity that are most commonly employed in the literature. The ultimate goal is to obtain a robust conceptual and practical knowledge of phylogenetic and functional beta diversity.

Keywords

Distance Matrix Beta Diversity Phylogenetic Diversity Alpha Diversity Much Recent Common Ancestor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Supplementary material

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References

  1. 64.
    Swenson, N.G., D.L. Erickson, X. Mi, N.A. Bourge, J. Forero-Montana, X. Ge, R. Howe, J.K. Lake, X. Liu, K. Ma, N. Pei, J. Thompson, M. Uriarte, A. Wolf, S.J. Wright, W. Ye, J. Zhang, J.K. Zimmerman, and W.J. Kress. 2012. Phylogenetic and functional alpha and beta diversity in temperate and tropical tree communities. Ecology 93: S112–S125.CrossRefGoogle Scholar
  2. 68.
    Rao, C.R. 1982. Diversity and dissimilarity coefficients: A unified approach. Theoretical Population Biology 21: 24–43.CrossRefMATHMathSciNetGoogle Scholar
  3. 80.
    Swenson, N.G., P. Anglada-Cordero, and J.A. Barone. 2011. Deterministic tropical tree community turnover: Evidence from patterns of functional beta diversity along an elevational gradient. Proceedings of the Royal Society B 278: 877–884.CrossRefGoogle Scholar
  4. 89.
    Siefert, A., C. Ravenscroft, M.D. Weiser, and N.G. Swenson. 2013. Functional beta diversity patterns reveal deterministic community assembly processes in eastern North American trees. Global Ecology and Biogeography 22: 682–691.CrossRefGoogle Scholar
  5. 105.
    Tuomisto, H., and K. Ruokolainen. 2006. Analyzing of explaining beta diversity? Understanding the targets of different methods of analysis. Ecology 87: 2697–2708.CrossRefGoogle Scholar
  6. 106.
    Legendre, P., D. Borcard, and P.R. Peres-Neto. 2008. Analyzing of explaining beta diversity? Comment. Ecology 89: 3238–3244.CrossRefGoogle Scholar
  7. 107.
    Tuomisto, H., and K. Ruokolainen. 2008. Analyzing or explaining beta diversity? Reply. Ecology 89: 3244–3256.CrossRefGoogle Scholar
  8. 108.
    Anderson, M.J., T.O. Crist, J.M. Chase, M. Vellend, B.D. Inouye, A.L. Freestone, N.J. Sanders, H.V. Cornell, L.S. Comita, K.F. Davies, S.P. Harrison, N.J.B. Kraft, J.C. Stegen, and N.G. Swenson. 2011. Navigating the multiple meanings of beta diversity: A roadmap for the practicing ecologist. Ecology Letters 14: 19–28.CrossRefGoogle Scholar
  9. 109.
    Fukami, T., T.M. Bezemer, S.R. Mortimer, and W.H. van der Putten. 2005. Species divergence and trait convergence in experimental plant community assembly. Ecology Letters 8: 1283–1290.CrossRefGoogle Scholar
  10. 110.
    Swenson, N.G., J.C. Stegen, S.J. Davies, D.L. Erickson, J. Forero-Montana, A.H. Hurlbert, W.J. Kress, J. Thompson, M. Uriarte, S.J. Wright, and J.K. Zimmerman. 2012. Temporal turnover in the composition of tropical tree communities: Functional determinism and phylogenetic stochasticity. Ecology 93: 490–499.CrossRefGoogle Scholar
  11. 111.
    Zhang, J., N.G. Swenson, S. Chen, X. Liu, Z. Li, J. Huang, X. Mi, and K. Ma. 2013. Phylogenetic beta diversity in tropical forests: Implications for the role of geographical and environmental distance. Journal of Systematics and Evolution 51: 71–85.CrossRefGoogle Scholar
  12. 112.
    Swenson, N.G. 2011. Phylogenetic beta diversity metrics, trait evolution and inferring the functional beta diversity of communities. PLoS One 6: e21264.CrossRefGoogle Scholar
  13. 113.
    Martin, A.P. 2002. Phylogenetic approaches for describing and comparing the diversity of microbial communities. Applied and Environmental Microbiology 68: 3673–3682.CrossRefGoogle Scholar
  14. 114.
    Lozupone, C., and R. Knight. 2005. UniFrac: A new phylogenetic method for comparing microbial communities. Applied and Environmental Microbiology 71: 8228–8235.CrossRefGoogle Scholar
  15. 115.
    Graham, C.H., and P.V.A. Fine. 2008. Phylogenetic beta diversity: Linking ecological and evolutionary processes across space and time. Ecology Letters 11: 1265–1277.CrossRefGoogle Scholar
  16. 116.
    Lozupone, C.A., M. Hamady, S.T. Kelley, and R. Knight. 2007. Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities. Applied Environmental Microbiology 73: 1576–1585.CrossRefGoogle Scholar
  17. 117.
    Chen, J., K. Bittinger, E.S. Charlson, C. Hoffmann, J. Lewis, G.D. Wu, R.G. Collman, F.D. Bushman, and H. Li. 2012. Associating microbiome composition with environmental covariates using generalized UniFrac distances. Bioinformatics 28: 2106–2113.CrossRefGoogle Scholar
  18. 118.
    Chang, Q., Y. Luan, and F. Sun. 2011. Variance adjusted weighted UniFrac: A powerful beta diversity measure for comparing communities based on phylogeny. BMC Bioinformatics 12: 118.CrossRefGoogle Scholar
  19. 119.
    Bryant, J.B., C. Lamanna, H. Morlon, A.J. Kerkhoff, B.J. Enquist, and J.L. Green. 2008. Microbes on mountainsides: Contrasting elevational patterns of bacterial and plant diversity. Proceedings of the National Academy of Sciences of the United States of America 105: 7774–7778.CrossRefGoogle Scholar
  20. 120.
    Ricotta, C., and S. Burrascano. 2008. Beta diversity for functional ecology. Preslia 80: 61–71.Google Scholar
  21. 121.
    Ricotta, C., and S. Burrascano. 2009. Testing for differences in beta diversity with asymmetric dissimilarities. Ecological Indicators 9: 719–724.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Nathan G. Swenson
    • 1
  1. 1.Michigan State UniversityEast LansingUSA

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