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Island biogeography of the Anthropocene

Nature volume 513, pages 543–546 (2014)Cite this article

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Abstract

For centuries, biogeographers have examined the factors that produce patterns of biodiversity across regions. The study of islands has proved particularly fruitful and has led to the theory that geographic area and isolation influence species colonization, extinction and speciation such that larger islands have more species and isolated islands have fewer species (that is, positive species–area and negative species–isolation relationships)1,2,3,4. However, experimental tests of this theory have been limited, owing to the difficulty in experimental manipulation of islands at the scales at which speciation and long-distance colonization are relevant5. Here we have used the human-aided transport of exotic anole lizards among Caribbean islands as such a test at an appropriate scale. In accord with theory, as anole colonizations have increased, islands impoverished in native species have gained the most exotic species, the past influence of speciation on island biogeography has been obscured, and the species–area relationship has strengthened while the species–isolation relationship has weakened. Moreover, anole biogeography increasingly reflects anthropogenic rather than geographic processes. Unlike the island biogeography of the past that was determined by geographic area and isolation, in the Anthropocene—an epoch proposed for the present time interval—island biogeography is dominated by the economic isolation of human populations.

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Figure 1: The biogeographic distributions of Caribbean anole lizards in the Anthropocene.
Figure 2: The linearization of the Caribbean anole species–area relationship (SAR) and flattening of the species–isolation relationship (SIR).
Figure 3: Anole lizards are establishing on Caribbean islands at an increasing rate.

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Acknowledgements

We thank J. Behm, J. Ellers, A. Ives, C. Pfister, J. Vermaat and T. Wootton for critical feedback; S. Buckner, S. Charles, A. Fields, M. López Darias, G. Perry, R. Platenberg, R. Powell, G. Reynolds, A. Sanchez, G. van Buurt and G. Wever for information on anole introductions; and A. Reglain for access to the RAC/REMPEITC-Caribe UNEP shipping traffic data set. M.R.H. was supported by the Netherlands Organisation for Scientific Research (858.14.040) and the US National Science Foundation (DBI 0906011).

Author information

Authors and Affiliations

  1. Department of Animal Ecology, Amsterdam Global Change Institute, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands,

    Matthew R. Helmus

  2. Center for Population Biology, University of California, Davis, 95616, California, USA

    D. Luke Mahler

  3. Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University, Cambridge, 02138, Massachusetts, USA

    Jonathan B. Losos

Authors
  1. Matthew R. Helmus
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  2. D. Luke Mahler
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  3. Jonathan B. Losos
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Contributions

M.R.H. conceived of the study, built the data sets and wrote the manuscript. M.R.H and D.L.M. performed the analyses. J.B.L. was involved in study design and contributed data. All authors discussed the results and commented on the manuscript.

Corresponding author

Correspondence to Matthew R. Helmus.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Bayesian maximum clade credibility phylogeny of Caribbean Anolis lizards with estimates of geographic history based on native species distributions.

The relative likelihoods of character states at internal nodes31 are depicted as pie charts and are coloured by geography (see tip colours and labels). Grey boxes encompass nodes and edges with relative log likelihood for a mainland state >0.005. Six banks here are identified as having had cladogenetic (in situ) speciation: the Greater Antilles (as previously reported6), St Vincent and Guadeloupe—St Vincent because our phylogeny13,21,29 is different from the phylogeny of the previous work6, and Guadeloupe because unlike the previous work6 we aggregated islands to banks.

Extended Data Figure 2 Caribbean anole bank saturation and the effect of isolation on the species–area relationship (SAR).

a, We used the residuals from a linear regression (dashed line) of the bank SAR and deviations from a 90% quantile regression (dotted line in a–c) of the SAR of islands within the Cuban bank as estimates of native anole saturation (Extended Data Table 2 and 3). SR is species richness. The two metrics of saturation were strongly correlated (ρ = 0.989, P ≪ 0.001). b, Cuban islands span the range of areas exhibited by Caribbean banks and are much less isolated and nearby to Cuba, the most species-rich island in the Caribbean. Our 90% quantile regression is analogous to calculations of island saturation curves based on drawing a line between a source island and a species-rich island very near to the source1. c, In the present day, bank richness has not exceeded the saturation curve, an indication that banks are not currently oversaturated with anoles. Filled symbols indicate banks with exotics. d, Isolation determines much of the nonlinear relationship between past (that is, native) anole richness and area (Fig. 2a) and validates our use of a linear model for the analyses in Tables 1 and 2. The ordinate is the residual from a regression of past species richness on the three isolation metrics, and unlike the raw SAR in a, a linear model (solid line), and not a breakpoint model (Fig. 2a), best fit the data.

Extended Data Figure 3 The loss of the Caribbean anole negative phylogenetic diversity–isolation relationship (PDIR).

a, In the past there was a strong negative PDIR (P = 0.003), but in the present day (b), this negative relationship has been reduced by 71% and c, is no longer significant (see Table 1 footnote for definitions of the values in c). Phylogenetic species variability (PSV) is the mean relative phylogenetic relatedness of all species on a bank32. Red points are banks with, and blue points banks without, in situ speciation. Filled symbols show banks with exotics. Grey points in b are banks that in the past had <2 anole species, but with exotic colonization now have 2 or more species such that PSV can now be calculated32. Note that to be comparable, both the PSV regressions in c are only on the banks with 2 or more native species. Variation in PSV is caused both by colonization and in situ speciation. Specifically, (1) Jamaica, Guadeloupe and St Vincent have low PSV because they are derived from one colonization and then in situ speciation (Extended Data Fig. 1); (2) Grenada, St Eustatius, Anguilla and Antigua have low PSV because each of their two colonizations came from the same clade; (3) Cay Sal, Little Cayman and Acklins have high PSV because they had colonizations from distantly related clades originating from Cuba—each had a natural colonization of the ubiquitous Anolis sagrei and of an ancestor from the carolinensis clade; (4) Great Bahama has high PSV because it received colonizations from both Hispaniola and Cuba; and (5) Cuba, Hispaniola and Puerto Rico have high PSV because they have had much in situ speciation derived from multiple colonizations.

Extended Data Figure 4 The effect of the US trade embargo on Cuban economic isolation.

a, There is a negative economic isolation–area relationship (EIAR) across Caribbean banks. b, The largest residual (studentized) of the EIAR (line in a) is Cuba. c, The predicted economic isolation of Cuba (× symbol) if the trade embargo is lifted, based on the EIAR.

Extended Data Table 1 Exotic colonization data set
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Extended Data Table 2 Natural and anthropogenic mechanisms determine exotic anole richness
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Extended Data Table 3 The saturation of banks with native anoles is explained by bank isolation and in situ speciation
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Extended Data Table 4 Correlations of the original isolation metrics and the three orthogonal isolation metrics used in all analyses
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Extended Data Table 5 The shifting importance of geographic area and isolation (Table 1) and the importance of economic isolation to anole Anthropocene island biogeography (Table 2) are robust to variations in the underlying data
Full size table
Extended Data Table 6 Correlations of economic isolation on geographic area and isolation
Full size table

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Helmus, M., Mahler, D. & Losos, J. Island biogeography of the Anthropocene. Nature 513, 543–546 (2014). https://doi.org/10.1038/nature13739

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