Biodiversity and Conservation

, Volume 16, Issue 9, pp 2531–2538 | Cite as

To Fit or Not to Fit? A Poorly Fitting Procedure Produces Inconsistent Results When the Species–Area Relationship is used to Locate Hotspots

Original paper


Ulrich and Buszko (2005, Biodivers Conserv 14:1977–1988) have recently applied the species–area relationship (SAR) to find butterfly hotspots in Europe using the linearized power function. They found that, with this method, despite the fact that the larger southern European countries and the Asian part of Turkey belong to the group of ecological hotspots defined by Myers et al. (2000, Nature 403:853–858), the SAR was unable to separate these countries from others. However, this result was a consequence of a poor fit. When different fitting models are compared, there is no obvious reason to prefer the linearized power function model, while a curvilinear fit to the power function should be selected as a best fit for this data set. Using this fit, two large southern European countries (Italy and Greece) and the Asian part of Turkey are identified as hotspots by the SAR. This simple exercise illustrates how an inappropriate choice of the fitting equation for the SAR may lead to inconsistent results.

Key words

Hotspots Lepidoptera Species–area relationships Fitting equations 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.



I am very grateful to W. Ulrich (Nicolaus Copernicus University, Gagarina, Torun) for stimulating discussions and two anonymous referees for their comments.


  1. Cobolli M, Ketmaier V, Lucarelli M (1997) Ricerche sulla Valle Peligna (Italia Centrale, Abruzzo). 14. Lepidoptera Papilionoidea e Hesperoidea (Insecta). In: Osella BG, Biondi M, Di Marco C, Riti M (eds) Ricerche sulla Valle Peligna. Quaderni di provinciaoggi, 23 (I). Amministrazione provinciale de Lȁ9Aquila. Graphicpress, Lȁ9Aquila, pp 255–282Google Scholar
  2. Connor EF, McCoy ED (1979) The statistics and biology of the species–area relationship. Am Nat 113:791–833CrossRefGoogle Scholar
  3. Diamond JM (1972) Biogeographic kinetics: estimation of relaxation times for avifaunas of Southwest Pacific Islands. Proc Nat Acad Sci USA 69:3199–3203CrossRefPubMedGoogle Scholar
  4. Fattorini S (2002a) Biogeography of the tenebrionid beetles (Coleoptera, Tenebrionidae) on the Aegean Islands (Greece). J Biogeogr 29:49–67CrossRefGoogle Scholar
  5. Fattorini S (2002b) Relict versus dynamic models for tenebrionid beetles of Aegean Islands (Greece) (Coleoptera: Tenebrionidae). Belgian J Zool 132:55–64Google Scholar
  6. Fattorini S (2005) A simple method to fit geometric series and broken stick models in community ecology and island biogeography. Acta Oecol 28:199–205Google Scholar
  7. Ferguson RI (1986) River loads underestimated by rating curves. Water Resour Res 22:74–76CrossRefGoogle Scholar
  8. Gould SJ (1979) An allometric interpretation of species–area curves: the meaning of the coefficient. Am Nat 114:335–343CrossRefGoogle Scholar
  9. Harte J, Kinzig A, Green J (1999a) Self-similarity in the distribution and abundance of species. Science 284:334–336CrossRefGoogle Scholar
  10. Harte J, Kinzig A, Green J (1999b) Response. Science 284:334–336Google Scholar
  11. He F, Legendre P (1996) On species–area relations. Am Nat 148:719–737CrossRefGoogle Scholar
  12. He F, Legendre P (2002) Species diversity patterns derived from species–area models. Ecology 83:1185–1198Google Scholar
  13. Hobohm C (2003) Characterization and ranking of biodiversity hotspots: centres of species richness and endemism. Biodiv Conserv 12:279–287CrossRefGoogle Scholar
  14. Keeley JE (2003) Relating species abundance distributions to species–area curves in two Mediterranean-type shrublands. Diversity Distrib 9:253–259CrossRefGoogle Scholar
  15. Loehle C (1990) Proper statistical treatment of species–area data. Oikos 57:143–145CrossRefGoogle Scholar
  16. Maddux RD, Athreya K (1999) On the distribution and abundance of species. Science 286:1647CrossRefGoogle Scholar
  17. May RM (1975) Patterns of species abundance and diversity. In: Cody ML, Diamond JM (eds) Ecology and evolution of communities. Harvard University Press, Cambridge, pp 81–120Google Scholar
  18. Myers N, Mittermeier RA, Mittermeier CG, da Fonseca GAB, Kent J (2000) Biodiversity hotspots for conservation priorities. Nature 403:853–858CrossRefPubMedGoogle Scholar
  19. Plotkin JB, Potts MD, Yu DW, Bunyavejchewin S, Condit R, Foster R, Hubbell S, LaFrankie J, Manokaran N, Seng LH, Sukumar R, Nowak MA, Ashton PS (2000) Predicting species diversity in tropical forests. Proc Nat Acad Sci USA 97:10850–10854CrossRefPubMedGoogle Scholar
  20. Preston RW (1948) The commonness, and rarity, of species. Ecology 29:254–283CrossRefGoogle Scholar
  21. Preston RW (1962) The canonical distribution of commonness and rarity: Part I. Ecology 43:185–215CrossRefGoogle Scholar
  22. Quinn GP, Keough MJ (2002) Experimental design and data analysis for biologists. Cambridge University Press, CambridgeGoogle Scholar
  23. Ricklefs RE, Lovette IJ (1999) The roles of island area per se and habitat diversity in the species–area relationships of four Lesser Antillean faunal groups. J Animal Ecol 68:1142–1160CrossRefGoogle Scholar
  24. Russell JC, Clout MN, McArdle BH (2004) Island biogeography and the species richness of introduced mammals on New Zealand offshore islands. J Biogeogr 31:653–664Google Scholar
  25. Šizling AL, Storch D (2004) Power-law species–area relationships and self-similar species distributions within finite areas. Ecol Letters 7:60–68CrossRefGoogle Scholar
  26. Storch D, Šizling AL, Gaston KJ (2003) Geometry of the species–area relationship in central European birds: testing the mechanism. J Animal Ecol 72:509–519CrossRefGoogle Scholar
  27. Sugihara G (1981) S = CAz, z ≅ 1/4: a reply to Connor and McCoy. Am Nat 117:790–793CrossRefGoogle Scholar
  28. Tjørve E (2003) Shapes and functions of species–area curves: a review of possible models. J Biogeogr 30:827–835CrossRefGoogle Scholar
  29. Turner WR, Tjørve E (2005) Scale-dependence in species–area relationships. Ecography 28:1–10CrossRefGoogle Scholar
  30. Ulrich W, Buszko J (2003a) Self-similarity and the species-area relation of Polish butterflies. Basic Appl Ecol 4:263–270Google Scholar
  31. Ulrich W, Buszko J (2003b) Species-area relationships of butterfiles in Europe and species richness forecasting. Ecography 26:365–373Google Scholar
  32. Ulrich W, Buszko J (2004) Habitat reduction and patterns of species loss. Basic Appl Ecol 5:231–240Google Scholar
  33. Ulrich W, Buszko J (2005) Detecting biodiversity hotspots using species–area and endemics–area relationships: the case of butterflies. Biodiv Conserv 14:1977–1988CrossRefGoogle Scholar
  34. Veech JA (2000) Choice of species–area function affects identification of hotspots. Conserv Biol 14:140–147CrossRefGoogle Scholar
  35. Viglioglia V (2004) Note preliminari sullȁ9entomofauna del Parco degli Acquedotti (Roma). Boll Ass Romana Entomol 59:1–18Google Scholar
  36. Williamson M, Gaston KJ (2005) The lognormal distribution is not an appropriate null hypothesis for the species-abundance distribution. J Animal Ecol 74:409–422CrossRefGoogle Scholar
  37. Wright SJ (1981) Intra-archipelago vertebrate distributions: the slope of the species–area relation. Am Nat 118:726–748CrossRefGoogle Scholar
  38. Zar JH (1999) Biostatistical Analysis, 4th edn. Prentice-Hall, Upper Saddle River, New JerseyGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2006

Authors and Affiliations

  1. 1.RomaItaly

Personalised recommendations