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17 - Scaling biodiversity under neutrality

Published online by Cambridge University Press:  05 August 2012

By
Luís Borda-de-Água ,
Stephen P. Hubbell  and
Fangliang He
Edited by
David Storch ,
Pablo Marquet  and
James Brown
Luís Borda-de-Água
Affiliation:
University of Georgia
Stephen P. Hubbell
Affiliation:
University of Georgia, Smithsonian Tropical Research Institute
Fangliang He
Affiliation:
University of Alberta
David Storch
Affiliation:
Charles University, Prague
Pablo Marquet
Affiliation:
Pontificia Universidad Catolica de Chile
James Brown
Affiliation:
University of New Mexico
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Summary

Introduction

To better understand biodiversity scaling, it may be useful to characterize the biodiversity scaling relationships that arise from the neutral perspective. This exercise will help in formulating quantitative null hypotheses for observed biodiversity scaling relationships. Here we use the term biodiversity to refer not only to species richness, but also to relative species abundance, and biodiversity scaling to refer to how patterns of biodiversity change on increasing sampling (spatial) scales. The study of biodiversity includes questions about the spatial dispersion and geographic range of species, relative species abundance, endemism, and beta diversity, the turnover of species across landscapes. A full discussion of all-taxa biodiversity scaling in the context of neutral theory is beyond the scope of the present theory because the theory currently applies only to communities of trophically similar species (a tree community, for example). It is also individual based rather than biomass based. Despite these limitations neutral theory is nevertheless a mechanistic, dynamical theory of community assembly based on fundamental demographic processes (birth, death, dispersal, speciation) – even though its postulated assembly rules are extremely simple. Under current neutral theory, speciation, ecological drift (demographic stochasticity in birth and deaths), and dispersal govern the presence or absence and the abundance of species in communities over local to global scales. Extinction is also critically important, but under neutrality, the extinction rate can be predicted once the other three processes are known.

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Chapter
Information
Scaling Biodiversity , pp. 347 - 375
Publisher: Cambridge University Press
Print publication year: 2007

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References

Allen, A. P. & White, E. P. (2003). Effects of range size on species-area relationships. Evolutionary Ecology Research, 5, 493–499.Google Scholar
Badii, R. & Broggi, G. (1988). Measurement of the dimension spectrum f(α): fixed mass approach. Physics Letters A, 131, 339–343.CrossRefGoogle Scholar
Badii, R. & Politi, A. (1984). Intrinsic oscillations in measuring the fractal dimension. Physics Letters A, 104, 303–305.CrossRefGoogle Scholar
Bell, G. (2000). The distribution of abundance in neutral communities. American Naturalist, 155, 606–617.CrossRefGoogle ScholarPubMed
Bell, G. (2001). Neutral macroecology. Science, 293, 2413–2418.CrossRefGoogle ScholarPubMed
Bramson, M., Cox, J. T. & Durrett, R. (1996). Spatial models for species-area curves. Annals of Probability, 24, 1721–1751.Google Scholar
Chambers, J. M., Mallows, C. L. & Stuck, B. W. (1976). A method for simulating stable random variables. Journal of the American Statistical Association, 71, 340–344.CrossRefGoogle Scholar
Chave, J. & Leigh, E. G. Jr. (2002). A spatially explicit neutral model of β-diversity in tropical forests. Theoretical Population Biology, 62, 153–168.CrossRefGoogle ScholarPubMed
Chave, J., Muller-Landau, H. C. & Levin, S. A. (2002). Comparing classical community models: theoretical consequences for patters of diversity. American Naturalist, 159, 1–23.CrossRefGoogle Scholar
Clark, J. S., Fastie, C., Hurtt, G., et al. (1998). Reid's paradox of rapid plant migration. Bioscience, 48, 13–24.CrossRefGoogle Scholar
Clark, J. S., Silman, M., Kern, R., Macklin, E. & HilleRisLambers, J. (1999). Seed dispersal near and far: patterns across temperate and tropical forests. Ecology, 80, 1475–1494.CrossRefGoogle Scholar
Condit, R., Hubbell, S. P., LaFrankie, J. V., et al. (1996). Species-area and species-individual relationships for tropical trees: a comparison of three 50 ha plots. Journal of Ecology, 84, 549–562.CrossRefGoogle Scholar
Cutler, C. D. (1993). A review of the theory and estimation of fractal dimension. In Dimension Estimation and Models, ed. Tong, H., pp. 1–107. Singapore: World Scientific.CrossRefGoogle Scholar
Diggle, P. J. (1983). Statistical Analysis of Spatial Point Processes. London: Academic Press.Google Scholar
Durrett, R. & Levin, S. (1996). Spatial models for species-area curves. Journal of Theoretical Biology, 179, 119–127.CrossRefGoogle Scholar
Etienne, R. S. & Olff, H. (2004). A novel genealogical approach to neutral biodiversity theory. Ecology Letters, 7, 170–175.CrossRefGoogle Scholar
Evertsz, C. J. G. & Mandelbrot, B. B. (1992). Multifractal measures. In Chaos and Fractals. New Frontiers of Science, ed. Peitgen, H. O., Jürgens, H. & Saupe, D., pp. 921–953. New York: Springer-Verlag.CrossRefGoogle Scholar
Gnedenko, B. V. & Kolmogorov, A. N. (1954). Limit Distributions for Sums of Independent Random Variables. Cambridge, MA: Addison-Wesley.Google Scholar
Grassberger, P. & Procaccia, I. (1983). Characterization of strange attractors. Physical Review Letters, 50, 346–349.CrossRefGoogle Scholar
Grassberger, P., Badii, R. & Politi, A. (1988). Scaling laws for invariant measures on hyperbolic and nonhyperbolic atractors. Journal of Statistical Physics, 51, 135–178.CrossRefGoogle Scholar
Halley, J. M. & Iwasa, Y. (1998). Extinction rate of a population under both demographic and environmental stochasticity. Theoretical Population Biology, 53, 1–15.CrossRefGoogle ScholarPubMed
Hirabayashi, T., Ito, K. & Yoshii, T. (1992). Multifractal analysis of earthquakes. Pure and Applied Geophysics, 138, 591–610.CrossRefGoogle Scholar
Holley, R. A. & Liggett, T. M. (1975). Ergodic theorems for weakly interacting systems and the voter model. Annals of Probability, 3, 643–663.CrossRefGoogle Scholar
Houchmandzadeh, B. & Vallade, M. (2003). Clustering in neutral ecology. Physical Review E, 68, Art. No. 061912.CrossRefGoogle ScholarPubMed
Hubbell, S. P. (1997). A unified theory of biogeography and relative species abundance and its applications to tropical rain forests and coral reefs. Coral Reefs, 16 (suppl.), S9–S21.CrossRefGoogle Scholar
Hubbell, S. P. (2001). The Unified Neutral Theory of Biodiversity and Biogeography. Princeton: Princeton University Press.Google Scholar
Hubbell, S. P. (2005). Neutral theory of biodiversity and biogeography and Stephen Jay Gould. Paleobiology, 31 (suppl.), 122–132.CrossRefGoogle Scholar
Hubbell, S. P. & Borda-de-Água, L. (2004). The distribution of relative species abundance in local communities under neutrality: a response to the comment by Chisholm & Burgman. Ecology, 85, 3175–3178.CrossRefGoogle Scholar
Hubbell, S. P. & Foster, R. B. (1983). Diversity of canopy trees in a neotropical forest and implications for the conservation of tropical trees. In Tropical Rain Forest: Ecology and Management, ed. Sutton, S. J., Whitmore, T. C. & Chadwick, A. C., pp. 25–41. Oxford: Blackwell.Google Scholar
Hubbell, S. P. & Lake, J. K. (2003). The neutral theory of biodiversity and biogeography, and beyond. In Macroecology: Concepts and Consequences, ed. Blackburn, T. M. & Gaston, K. J., pp. 45–63. Oxford: Blackwell Science.Google Scholar
Jones, F. A., Chen, J., Weng, G. J. & Hubbell, S. P. (2005). A genetic evaluation of seed dispersal in a Neotropical tree, Jacaranda copaia (Bignoniaceae). American Naturalist, 166, 543–555.CrossRefGoogle Scholar
Kot, M., Lewis, M. A. & Driessche, P. (1996). Dispersal data and the spread of invading organisms. Ecology, 77, 2027–2042.CrossRefGoogle Scholar
Lewis, M. A. (1997). Variability, patchiness, and jump dispersal in the spread of an invading population. In Spatial Ecology: The Role of Space in Population Dynamics and Interspecific Interactions, ed. Tilman, D. & Kareiva, P., pp. 46–74. Princeton: Princeton University Press.Google Scholar
Liebovitch, L. S. (1998). Fractals and Chaos Simplified for the Life Sciences. Oxford: Oxford University Press.Google Scholar
MacArthur, R. H. & Wilson, E. O. (1967). The Theory of Island Biogeography, Princeton: Princeton University Press.Google Scholar
Mandelbrot, B. B. (1977). Fractals: Form, Chance, and Dimension. San Francisco: W. H. Freeman.Google Scholar
Mandelbrot, B. B. (1997). Fractals and Scaling in Finance: Discontinuity, Concentration, Risk. New York: Springer.CrossRefGoogle Scholar
Manly, (1997). Randomization, Bootstrap and Monte Carlo Methods in Biology. 2nd edn. London: Chapman & Hall/CRC.Google Scholar
Mantegna, R. N. & Stanley, H. E. (2000). An Introduction to Econophysics: Correlations and Complexity in Finance. Cambridge: Cambridge University Press.Google Scholar
McKane, A. J, Alonso, D. & Solé, R. V. (2004). Analytic solution of Hubbell's model of local community dynamics. Theoretical Population Biology, 65, 67–73.CrossRefGoogle ScholarPubMed
Meneveau, C. & Sreenivasan, K. R. (1989). Measurements of f(α) from scaling histograms and applications to dynamical systems and fully developed turbulence. Physics Letters A, 137, 103–112.CrossRefGoogle Scholar
Muller-Landau, M. C., Dalling, J. W., Harms, K. E., et al. (2004). Seed dispersal and density-dependent seed and seedling survival in Trichilia turbeculata and Miconia argentea. In Tropical Forest Diversity and Dynamism: Findings From a Large-scale Plot Network, ed. Losos, C. & Leigh, E. G. Jr., pp. 340–362. Chicago: University of Chicago Press.Google Scholar
Nagylaki, T. (1974). The decay of genetic variability in geographically structured populations. Proceedings of the National Academy of Sciences of the USA, 71, 2932–2936.CrossRefGoogle ScholarPubMed
Nathan, R. & Muller-Landau, H. (2000). Spatial patterns of seed dispersal, their determinants and consequences for recruitment. Trends in Ecology and Evolution, 15, 278–285.CrossRefGoogle ScholarPubMed
Petit, J. R., Pineau, E., Demesure, B., Bacilieri, R., Ducousso, A. & Kremer, A. (1997). Proceedings of the National Academy of Sciences of the USA, 94, 9996–10001.CrossRef
Preston, F. W. (1948). The commonness, and rarity, of species. Ecology, 29, 254–283.CrossRefGoogle Scholar
Rosenzweig, M. L. (1995). Species Diversity in Space and Time. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Silvertown, J., Holtier, J. S., Johnson, J. & Dale, P. (1992). Cellular automaton models of interspecific competition for space – the effect of pattern on process. Journal of Ecology, 80, 527–534.CrossRefGoogle Scholar
Vallade, M. & Houchmandzadeh, B. (2003). Analytical solution of a neutral model of biodiversity. Physical Review E, 68, Art. No. 061902.CrossRefGoogle ScholarPubMed
Volkov, I., Banavar, J. R., Hubbell, S. P. & Maritan, A. (2003). Neutral theory and relative species abundance in ecology. Nature, 424, 1035–1037.CrossRefGoogle ScholarPubMed
Volkov, I., Banavar, J., He, F., Hubbell, S. P. & Maritan, A. (2005). Density dependence explains tree species abundance and diversity in tropical forests. Nature, 438, 658–661.CrossRefGoogle ScholarPubMed
Weiss, G. H. (1994). A primer of random walkology. In Fractals in Science, ed. Bunde, A. & Havlin, S., pp. 119–161. Berlin: Springer-Verlag.Google Scholar
West, B. J. & Deering, W. (1994). Fractal physiology for physicists: Lévy statistics. Physics Reports, 246, 1–100.CrossRefGoogle Scholar

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