Evolutionary species–area curves as revealed by single-island endemics: insights for the inter-provincial species–area relationship
Article first published online: 5 JUN 2008
© 2007 The Authors
Volume 31, Issue 3, pages 401–407, June 2008
How to Cite
Triantis, K. A., Mylonas, M. and Whittaker, R. J. (2008), Evolutionary species–area curves as revealed by single-island endemics: insights for the inter-provincial species–area relationship. Ecography, 31: 401–407. doi: 10.1111/j.0906-7590.2007.05323.x
- Issue published online: 5 JUN 2008
- Article first published online: 5 JUN 2008
- Manuscript Accepted 21 December 2007
The species–area relationship (SAR) between different biological provinces is one of the most interesting, but least explored aspects of the well-known species–area pattern. Following the usage that a biological province is a region whose species have for the most part evolved within it, rather than immigrating from somewhere else, we propose that islands can be considered equivalent to biological provinces for single island endemic species (SIEs). Hence, analyses of the relationships between numbers of SIEs and island area can be used as model systems to explore the form of inter-provincial SARs. We analyzed 13 different data sets derived from 11 sources, using the power (log–log) model. Eleven of the SIE–area relationships were statistically significant, explaining high proportions of the variance in SIE numbers (R2 0.57–0.95). The z-values (slopes) of the statistically significant SIE–area relationships ranged from 0.47 to 1.13, with a mean value of 0.80 (SD±0.24).
All the island systems in which SIE represent >50% of species exhibited z-values for the SARs of native species higher than those deemed typical of archipelagic SARs. The SIE–area slopes are quite similar to those previously calculated for inter-provincial SARs, indicating that, when speciation becomes the dominant process adding to the species richness of assemblages, high z-values should be anticipated, regardless of the biogeographical scale of the study system.