Landscape Ecology

, Volume 29, Issue 7, pp 1237–1248 | Cite as

Continuous predictors of species distributions support categorically stronger inference than ordinal and nominal classes: an example with urban bats

  • F. M. CarylEmail author
  • A. K. Hahs
  • L. F. Lumsden
  • R. Van der Ree
  • C. Wilson
  • B. A. Wintle
Research Article


Understanding of how species distributions are driven by landscape-level processes has been obscured by null or inconsistent findings from poorly designed studies. We explore how differences in the way potential drivers of species distributions are defined can influence their perceived effects. Specifically, we evaluate how much statistical power is lost when continuous variables are discretised, and how the use of qualitatively defined nominal variables impacts biological interpretation of results. We fitted generalized linear models to dependent variables relating to bat distribution (species richness, diversity, relative abundance of functional groups and individual species) obtained from 36 sites across Melbourne, Australia, and independent variables that were continuous (percentage tree cover, dwelling density), ordinal (dichotomised continuous variables) or nominal (land-use, urban context). We found that models fitted with continuous predictors had better fit and explanatory power than those fitted with ordinal predictors for all response variables. Ordinal models failed to detect statistically significant effects for 4 of the 11 response variables that were successfully modelled with continuous data, suggesting Type II errors had occurred. Models fitted with nominal data explained a comparable amount of variation in some dependent variables as continuous models. However, interpretation of the mechanisms behind responses to nominal categorical levels was obscured because environmental conditions within them were confounded and not homogenous. To gain better understanding from nominal predictors would therefore require further investigation. Our findings show that careful consideration must be given to the choice of environmental variables used for species distribution modelling and how those variables are defined.


Experimental design Functional guilds Insectivorous bats South-east Australia Species distribution Urbanisation Variable selection 



The research was funded by ARC linkage Grant LP0990359, the National Environmental Research Program Environmental Decisions Hub, and The Baker Foundation. We thank the residents who granted us access to their properties to conduct bat surveys. Caragh Threlfall and Mark McDonnell provided comments that greatly improved this manuscript.

Supplementary material

10980_2014_62_MOESM1_ESM.docx (30 kb)
Supplementary material 1 (DOCX 30 kb)


  1. Adams M, Law B, Gibson M (2010) Reliable automation of bat call identification for eastern New South Wales, Australia, using classification trees and AnaScheme software. Acta Chiropterologica 12:231–245CrossRefGoogle Scholar
  2. Austin MP (2002) Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecol Model 157:101–118CrossRefGoogle Scholar
  3. Australian Bureau of Statistics (2006) Victoria mesh blocks digital boundaries. Available from Accessed Sep 2013
  4. Avila-flores R, Fenton MB (2005) Use of spatial features by foraging insectivorous bats in a large urban landscape. J Mammal 86:1193–1204CrossRefGoogle Scholar
  5. Bartonička T, Zukal J (2003) Flight activity and habitat use of four bat species in a small town revealed by bat detectors. Folia Zool 52:155–166Google Scholar
  6. Basham R, Law B, Banks P (2011) Microbats in a “leafy” urban landscape: are they persisting, and what factors influence their presence? Austral Ecol 36:663–678Google Scholar
  7. Bech M, Gyrd-Hansen D (2005) Effects coding in discrete choice experiments. Health Econ 14:1079–1083PubMedCrossRefGoogle Scholar
  8. Bjornstad O (2013) ncf: spatial nonparametric covariance functions. R package version 1.1–5Google Scholar
  9. Burnham KP, Anderson DR, Huyvaert KP (2010) AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons. Behav Ecol Sociobiol 65:23–35CrossRefGoogle Scholar
  10. Chace JF, Walsh JJ (2006) Urban effects on native avifauna: a review. Landsc Urban Plann 74:46–69CrossRefGoogle Scholar
  11. Cottingham KL, Lennon JT, Brown BL (2005) Knowing when to draw the line: designing more informative ecological experiments. Front Ecol Environ 3:145–152CrossRefGoogle Scholar
  12. Department of Environment and Primary Industries (2006) Tree Cover Grid (TREE25). Available from Accessed Sep 2013)
  13. Duchamp JE, Swihart RK (2008) Shifts in bat community structure related to evolved traits and features of human-altered landscapes. Landscape Ecol 23:849–860CrossRefGoogle Scholar
  14. Eigenbrod F, Hecnar SJ, Fahrig L (2011) Sub-optimal study design has major impacts on landscape-scale inference. Biol Conserv 144:298–305CrossRefGoogle Scholar
  15. Ewers RM, Didham RK (2006) Confounding factors in the detection of species responses to habitat fragmentation. Biol Rev 81:117–142PubMedCrossRefGoogle Scholar
  16. Fidler F, Burgman MA, Cumming G et al (2006) Impact of criticism of null-hypothesis significance testing on statistical reporting practices in conservation biology. Conserv Biol 20:1539–1544PubMedCrossRefGoogle Scholar
  17. Gaisler J, Zukal J, Rehak Z, Homolka M (1998) Habitat preference and flight activity of bats in a city. J Zool 244:439–445CrossRefGoogle Scholar
  18. Gehrt S, Chelsvig J (2003) Bat activity in an urban landscape: patterns at the landscape and microhabitat scale. Ecol Appl 13:939–950CrossRefGoogle Scholar
  19. Graham MH (2003) Confronting multicollinearity in ecological multiple regression. Ecology 84:2809–2815CrossRefGoogle Scholar
  20. Grimm NB, Faeth SH, Golubiewski NE et al (2008) Global change and the ecology of cities. Science 319:756–760PubMedCrossRefGoogle Scholar
  21. Hahs AK, McDonnell MJ (2006) Selecting independent measures to quantify Melbourne’s urban-rural gradient. Landsc Urban Plann 78:435–438CrossRefGoogle Scholar
  22. Hanspach J, Fischer J, Ikin K, Stott J, Law BS (2012) Using trait-based filtering as a predictive framework for conservation: a case study of bats on farms in southeastern Australia. J App Ecol 49:842–850CrossRefGoogle Scholar
  23. Hourigan CL, Johnson C, Robson SK (2006) The structure of a micro-bat community in relation to gradients of environmental variation in a tropical urban area. Urban Ecosyst 9:67–82CrossRefGoogle Scholar
  24. Hourigan CL, Catterall CP, Jones D, Rhodes M (2010) The diversity of insectivorous bat assemblages among habitats within a subtropical urban landscape. Austral Ecol 35:849–857CrossRefGoogle Scholar
  25. Hurlbert SH (1984) Pseudoreplication and the design of ecological field experiments. Ecol Monogr 54:187–211CrossRefGoogle Scholar
  26. Lindegarth M, Gamfeldt L (2005) Comparing categorical and continuous ecological analyses: effects of “wave exposure” on rocky shores. Ecology 86:1346–1357CrossRefGoogle Scholar
  27. Luck GW, Smallbone L, Threlfall C, Law B (2013) Patterns in bat functional guilds across multiple urban centres in south-eastern Australia. Landscape Ecol 28:455–469CrossRefGoogle Scholar
  28. Lumsden L, Bennett A (2005) Scattered trees in rural landscapes: foraging habitat for insectivorous bats in south-eastern Australia. Biol Conserv 122:205–222CrossRefGoogle Scholar
  29. Lumsden LF, Bennett AF, Silins JE (2002) Selection of roost sites by the lesser long-eared bat (Nyctophilus geoffroyi) and Gould’s wattled bat (Chalinolobus gouldii) in south-eastern Australia. J Zool 257:207–218CrossRefGoogle Scholar
  30. Marzluff JM, Bowman R, Donnelly R (2001) A historical perspective on urban bird research: trends, terms, and approaches. In: Marzluff JM, Bowman R, Donnelly R (eds) Avian ecology and conservation in an urbanizing world. Springer, US, pp 1–17CrossRefGoogle Scholar
  31. McCarthy MA, Parris KM (2004) Clarifying the effect of toe clipping on frogs with Bayesian statistics. J Appl Ecol 41:780–786CrossRefGoogle Scholar
  32. McDonnell MJ, Hahs AK (2009) Comparative ecology of cities and towns: past, present and future. Ecol Cities TownsGoogle Scholar
  33. McDonnell MJ, Hahs AK (2013) The future of urban biodiversity research: moving beyond the “low-hanging fruit”. Urban Ecosyst 16:397–409CrossRefGoogle Scholar
  34. McGarigal K, Cushman SA (2002) Comparative evaluation of experimental approaches to the study of habitat fragmentation effects. Ecol Appl 12:335–345CrossRefGoogle Scholar
  35. McIntyre NE, Knowles-Yánez K, Hope D (2001) Urban ecology as an interdisciplinary field: differences in the use of “urban” between the social and natural sciences. Urban Ecosyst 4:5–24CrossRefGoogle Scholar
  36. Nakagawa S, Schielzeth H (2013) A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol Evol 4:133–142CrossRefGoogle Scholar
  37. Norberg UM, Rayner JMV (1987) Ecological morphology and flight in bats (Mammalia; Chiroptera): wing adaptations, flight performance, foraging strategy and echolocation. Phil Trans R Soc B 316:335–427Google Scholar
  38. Oates A, Taranto M (2001) Vegetation mapping of the Port Phillip and Westernport Region. Department of Natural Resources and Environment, MelbourneGoogle Scholar
  39. Pickett STA, Kolasa J, Jones C (2007) Ecological understanding. Academic Press, BurlingtonGoogle Scholar
  40. Pickett STA, Cadenasso ML, Grove JM et al (2008) Beyond urban legends: an emerging framework of urban ecology, as illustrated by the Baltimore Ecosystem Study. Bioscience 58:139–150CrossRefGoogle Scholar
  41. R Development Core Team (2013) R: a Language and Environment for Statistical Computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  42. Raciti S, Hutyra L, Rao P, Finzi A (2012) Inconsistent definitions of “urban” result in different conclusions about the size of urban carbon and nitrogen stocks. Ecol Appl 22:1015–1035PubMedCrossRefGoogle Scholar
  43. Razgour O, Hanmer J, Jones G (2011) Using multi-scale modelling to predict habitat suitability for species of conservation concern: the grey long-eared bat as a case study. Biol Conserv 144:2922–2930CrossRefGoogle Scholar
  44. Ries L, Fletcher RJ, Battin J, Sisk TD (2004) Ecological responses to habitat edges: mechanisms, models, and variability explained. Annu Rev Ecol Evol Syst 35:491–522CrossRefGoogle Scholar
  45. Russo D, Jones G (2003) Use of foraging habitat by bats in a Mediterranean area determined by acoustic surveys: conservation implications. Ecography 26:197–209CrossRefGoogle Scholar
  46. Shochat E, Warren PS, Faeth SH et al (2006) From patterns to emerging processes in mechanistic urban ecology. Trends Ecol Evol 21:186–191PubMedCrossRefGoogle Scholar
  47. Taylor R, Wierzbowski P, Lowe K et al (2003) Biodiversity Action Planning: Strategic Overview for the Victorian Volcanic Plain Bioregion. Department of Natural Resources and Environment, MelbourneGoogle Scholar
  48. Theobald DM (2004) Placing exurban land-use change in a human modification framework. Front Ecol Environ 2:139–144CrossRefGoogle Scholar
  49. Threlfall C, Law B, Penman T, Banks PB (2011) Ecological processes in urban landscapes: mechanisms influencing the distribution and activity of insectivorous bats. Ecography 34:814–826CrossRefGoogle Scholar
  50. Threlfall CG, Law B, Banks PB (2012) Sensitivity of insectivorous bats to urbanization: implications for suburban conservation planning. Biol Conserv 146:41–52CrossRefGoogle Scholar
  51. Van der Ree R, McCarthy MA (2005) Inferring the persistence of indigenous mammals in response to urbanisation. Anim Conserv 8:309–319CrossRefGoogle Scholar
  52. Venables WN, Ripley BD (2013) MASS: modern applied statistics with S. R package version 7.3–29Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • F. M. Caryl
    • 1
    Email author
  • A. K. Hahs
    • 2
  • L. F. Lumsden
    • 3
  • R. Van der Ree
    • 2
  • C. Wilson
    • 1
  • B. A. Wintle
    • 1
  1. 1.FMC, School of BotanyUniversity of MelbourneParkvilleAustralia
  2. 2.Australian Research Centre for Urban Ecology, Royal Botanic Gardens Victoria, School of BotanyUniversity of MelbourneParkvilleAustralia
  3. 3.Department of Environment and Primary IndustriesArthur Rylah Institute for Environmental ResearchHeidelbergAustralia

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