Favourability: concept, distinctive characteristics and potential usefulness

Abstract

The idea of analysing the general favourability for the occurrence of an event was presented in 2006 through a mathematical function. However, even when favourability has been used in species distribution modelling, the conceptual framework of this function is not yet well perceived among many researchers. The present paper is conceived for providing a wider and more in-depth presentation of the idea of favourability; concretely, we aimed to clarify both the concept and the main distinctive characteristics of the favourability function, especially in relation to probability and suitability, the most common outputs in species distribution modelling. As the capabilities of the favourability function go beyond species distribution modelling, we also illustrate its usefulness for different research disciplines for which this function remains unknown. In particular, we stressed that the favourability function has potential to be applied in all the cases where the probability of occurrence of an event is analysed, such as, for example, habitat selection or epidemiological studies.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3

References

  1. Acevedo P, Cassinello J, Hortal J, Gortázar C (2007) Invasive exotic aoudad (Ammotragus lervia) as a major threat to native Iberian ibex (Capra pyrenaica): a habitat suitability model approach. Divers Distrib 13:587–597

    Article  Google Scholar 

  2. Acevedo P, Ward AI, Real R, Smith GC (2010) Assessing the biogeographical relationships of ecologically related species using favourability functions: a case study on British deer. Divers Distrib 16:515–528

    Article  Google Scholar 

  3. Acevedo P, Farfán MA, Márquez AL, Delibes-Mateos M, Real R, Vargas JM (2011) Past, present and future of wild ungulates in relation to changes in land use. Landsc Ecol 26:19–31

    Article  Google Scholar 

  4. Acevedo P, Jiménez-Valverde A, Melo-Ferreira J, Real R, Alves PC (2012) Parapatric species and the implications for climate change studies: a case study on hares in Europe. Glob Chang Biol. doi:10.1111/j.1365-2486.2012.02655.x

  5. Albert CH, Thuiller W (2008) Favourability functions versus probability of presence: advantages and misuses. Ecography 31:417–422

    Article  Google Scholar 

  6. Amici A, Pelorosso R, Serrani F, Boccia L (2009) A nesting site suitability model for rock partridge (Alectoris graeca) in the Apennine Mountains using logistic regression. Ital J Anim Sci 8:751–753

    Google Scholar 

  7. Araújo MB, New M (2007) Ensemble forecasting of species distributions. Trends Ecol Evol 22:42–47

    PubMed  Article  Google Scholar 

  8. Barbosa AM, Real R, Vargas JM (2009) Transferability of environmental favourability models in geographic space: the case of the Iberian desman (Galemys pyrenaicus) in Portugal and Spain. Ecol Model 220:747–754

    Article  Google Scholar 

  9. Barbosa AM, Real R, Vargas JM (2010) Use of coarse-resolution models of species' distributions to guide local conservation inferences. Conserv Biol 24:1378–1387

    PubMed  Article  Google Scholar 

  10. Bernardo JM, Smith AFM (2000) Bayesian theory, Wiley series in probability and statistics. Wiley, Hoboken

    Google Scholar 

  11. Boadella M, Barasona JA, Pozio E, Montoro V, Vicente J, Gortázar C, Acevedo P (2012) Spatial-temporal trend and risk factors for Trichinella sp. infection in wild boar (Sus scrofa) populations of central Spain: a long-term study. Int J Parasitol (in press)

  12. Cramer JS (1999) Predictive performance of binary logit model in unbalanced samples. J R Stat Soc D 48:85–94

    Article  Google Scholar 

  13. Elith J, Phillips SJ, Hastie T, Dudík M, Chee YE, Yates CJ (2011) A statistical explanation of MaxEnt for ecologist. Divers Distrib 17:43–57

    Article  Google Scholar 

  14. Estrada A, Real R, Vargas JM (2008) Using crisp and fuzzy modelling to identify favourability hotspots useful to perform gap analysis. Biodivers Conserv 17:857–871

    Article  Google Scholar 

  15. Estrada-Peña A, Acevedo P, Ruiz-Fons F, Gortázar C, de la Fuente J (2008) Evidence of the importance of host habitat use in predicting the dilution effect of wild boar for deer exposure to Anaplasma spp. PLoS One 3(8):e2999. doi:10.1371/journal.pone.0002999

    PubMed  Article  Google Scholar 

  16. Fernández MC, Durán AC, Real R, López D, Fernández B, de Andrés AV, Arqué JM, Gallego A, Sans-Coma V (2000) Coronary artery anomalies and aortic valve morphology in the Syrian hamster. Lab Ani-UK 34:145–154

    Article  Google Scholar 

  17. Franklin J (2009) Mapping species distributions. Spatial inference and prediction. Cambridge University Press, Cambridge

    Google Scholar 

  18. Guisan A, Thuiller W (2005) Predicting species distribution: offering more than simple habitat models. Ecol Lett 8:993–1009

    Article  Google Scholar 

  19. Guisan A, Zimmermann NE (2000) Predictive habitat distribution models in ecology. Ecol Model 135:147–186

    Article  Google Scholar 

  20. Gutiérrez-Illán J, Gutiérrez D, Wilson RW (2010) The contributions of topoclimate and land cover to species distributions and abundance: fine-resolution tests for a mountain butterfly fauna. Glob Ecol Biogeogr 19:15–173

    Google Scholar 

  21. Hastie TJ, Tibshirani RJ (1990) Generalized additive models. Chapman & Hall, London

    Google Scholar 

  22. Hirzel AH, Hausser J, Chessel D, Perrin N (2002) Ecological-niche factor analysis: how to compute habitat-suitability maps without absence data? Ecology 83:2027–2036

    Article  Google Scholar 

  23. Hirzel AH, Le Lay G, Helfer V, Randin C, Guisan A (2006) Evaluating the ability of habitat suitability models to predict species presences. Ecol Model 199:142–152

    Article  Google Scholar 

  24. Hirzel AH, Braunisch V, Le Lay G. Hausser J, Perrin N (2008) BIOMAPPER 4.0. Laboratoy of Conservation Biology, Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland. Available from http://www.unil.ch/biomapper

  25. Hosmer DW, Lemeshow S (2000) Applied logistic regression. Wiley Interscience, New York

    Google Scholar 

  26. Jiménez-Valverde A, Lobo JM (2007) Threshold criteria for conversion of probability of species presence to either-or presence–absence. Acta Oecol 31:361–369

    Article  Google Scholar 

  27. Jiménez-Valverde A, Peterson AT, Soberón J, Overton J, Aragón P, Lobo JM (2011) Use of niche models in invasive species risk assessments. Biol Invasions 13:2785–2797

    Article  Google Scholar 

  28. Keating KA, Cherry S (2004) Use and interpretations of logistic regression in habitat-selection studies. J Wildl Manage 68:774–789

    Article  Google Scholar 

  29. Laplace PS (1825) Essai philosophique sur les probabilités. Bachelier, Paris

    Google Scholar 

  30. Liu C, Berry PM, Dawson TP, Pearson RG (2005) Selecting thresholds of occurrence in the prediction of species distributions. Ecography 28:385–393

    Article  Google Scholar 

  31. Manly BFJ, McDonald LL, Thomas DL, McDonald TL, Erickson W (2002) Resource selection by animals: statistical design and analysis for field studies, 2nd edn. Kluwer, New York

    Google Scholar 

  32. Mörner T, Obendorf D, Artois M, Woodford M (2002) Surveillance and monitoring of wildlife diseases. Rev Sci Tech Off Int Epiz 21:67–76

    Google Scholar 

  33. Muñoz AR, Real R (2006) Assessing the potential range expansion of the exotic monk parakeet in Spain. Divers Distrib 12:656–665

    Article  Google Scholar 

  34. Nielsen C, Hartvig P, Kollmann J (2008) Predicting the distribution of the invasive alien Heracleum mantegazzianum at two different spatial scales. Divers Distrib 14:307–317

    Article  Google Scholar 

  35. Peterson AT (2008) Biogeography of diseases: a framework for analysis. Naturwissenschaften 95:483–491

    PubMed  Article  CAS  Google Scholar 

  36. Pfeiffer D, Robinson T, Stevenson M, Stevens K, Rogers D, Clements A (2008) Spatial analysis in epidemiology. Oxford University Press, New York

    Google Scholar 

  37. Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190:231–259

    Article  Google Scholar 

  38. Real R, Barbosa AM, Vargas JM (2006) Obtaining environmental favourability functions from logistic regression. Environ Ecol Stat 13:237–245

    Article  Google Scholar 

  39. Real R, Barbosa AM, Rodríguez A, García FJ, Vargas JM, Palomo LJ, Delibes M (2009) Conservation biogeography of ecologically interacting species: the case of the Iberian lynx and the European Rabbit. Divers Distrib 15:390–400

    Article  Google Scholar 

  40. Real R, Márquez AL, Olivero J, Estrada A (2010) Are species distribution models in climate warming scenarios useful for informing emission policy planning? An uncertainty assessment using fuzzy logic. Ecography 33:304–314

    Google Scholar 

  41. Robertson MP, Villet MH, Palmer AR (2004) A fuzzy classification technique for predicting species’ distributions: applications using invasive alien plants and indigenous insects. Divers Distrib 10:461–474

    Article  Google Scholar 

  42. Rochlin I, Turbow D, Gomez F, Ninivaggi DV, Campbell SR (2011) Predictive mapping of human risk for West Nile Virus (WNV) based on environmental and socioeconomic factors. PLoS One 6(8):e23280. doi:10.1371/journal.pone.0023280

    PubMed  Article  CAS  Google Scholar 

  43. Royle JA, Chandler RB, Yackulic C, Nichols JD (2012) Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions. Methods Ecol Evol. doi:10.1111/j.2041-210X.2011.00182.x

  44. Sutherst RW, Bourne AS (2009) Modelling non-equilibrium distributions of invasive species: a tale of two modelling paradigms. Biol Invasions 11:1231–1237

    Article  Google Scholar 

  45. Tabachnick BG, Fidell LS (1996) Using multivariate analysis, 3rd edn. HarperCollins College, Northridge

    Google Scholar 

  46. Thuiller W, Lafourcade B, Engler R, Araújo MB (2009) BIOMOD—a platform for ensemble forecasting of species distributions. Ecography 32:369–373

    Article  Google Scholar 

  47. Vicente J, Hofle U, Garrido JM, Fernandez-de-Mera IG, Acevedo P, Juste R, Barral M, Gortázar C (2007) Risk factors associated with the prevalence of tuberculosis-like lesions in fenced wild boar and red deer in south central Spain. Vet Res 38:451–464

    PubMed  Article  Google Scholar 

  48. Webber BL, Yates CJ, Le Maitre DC, Scott JK, Kriticos DJ, Ota N, McNeill A, Le Roux JJ, Midgley GF (2011) Modelling horses for novel climate courses: insights from projecting potential distributions of native and alien Australian acacias with correlative and mechanistic models. Divers Distrib 17:978–1000

    Article  Google Scholar 

Download references

Acknowledgements

The authors acknowledge funding from Spanish Plan Nacional de Investigación and FEDER CGL2009-11316/BOS. P. A. was supported by the Vicerrectorado de Investigación of the University of Malaga and currently by a Beatriu de Pinós fellowship funded by Comissionat per a Universitats i Recerca del Departament d’Innovació, Universitats i Empresa, of the Generalitat de Catalunya and the COFUND Programme–Marie Curie Actions under 7th Marc Programme of the European Community.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Pelayo Acevedo.

Additional information

Communicated by: Sven Thatje

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Acevedo, P., Real, R. Favourability: concept, distinctive characteristics and potential usefulness. Naturwissenschaften 99, 515–522 (2012). https://doi.org/10.1007/s00114-012-0926-0

Download citation

Keywords

  • Epidemiology
  • Favourability function
  • Habitat selection
  • Habitat suitability
  • Probability of occurrence
  • Species distribution modelling