Biodiversity and Conservation

, Volume 18, Issue 3, pp 739–763

Effects of spatial heterogeneity on butterfly species richness in Rocky Mountain National Park, CO, USA

  • Sunil Kumar
  • Sara E. Simonson
  • Thomas J. Stohlgren
Original Paper

DOI: 10.1007/s10531-008-9536-8

Cite this article as:
Kumar, S., Simonson, S.E. & Stohlgren, T.J. Biodivers Conserv (2009) 18: 739. doi:10.1007/s10531-008-9536-8


We investigated butterfly responses to plot-level characteristics (plant species richness, vegetation height, and range in NDVI [normalized difference vegetation index]) and spatial heterogeneity in topography and landscape patterns (composition and configuration) at multiple spatial scales. Stratified random sampling was used to collect data on butterfly species richness from seventy-six 20 × 50 m plots. The plant species richness and average vegetation height data were collected from 76 modified-Whittaker plots overlaid on 76 butterfly plots. Spatial heterogeneity around sample plots was quantified by measuring topographic variables and landscape metrics at eight spatial extents (radii of 300, 600 to 2,400 m). The number of butterfly species recorded was strongly positively correlated with plant species richness, proportion of shrubland and mean patch size of shrubland. Patterns in butterfly species richness were negatively correlated with other variables including mean patch size, average vegetation height, elevation, and range in NDVI. The best predictive model selected using Akaike’s Information Criterion corrected for small sample size (AICc), explained 62% of the variation in butterfly species richness at the 2,100 m spatial extent. Average vegetation height and mean patch size were among the best predictors of butterfly species richness. The models that included plot-level information and topographic variables explained relatively less variation in butterfly species richness, and were improved significantly after including landscape metrics. Our results suggest that spatial heterogeneity greatly influences patterns in butterfly species richness, and that it should be explicitly considered in conservation and management actions.


Akaike’s information criterion Butterfly species richness FRAGSTATS Landscape context Landscape metrics Model selection Plant species richness Spatial autocorrelation Spatial heterogeneity Spatial scale 



Akaike’s information criterion corrected for small sample size


Digital elevation model


Environmental Systems Research Institute


Geographical information system


Global positioning system


Moderate resolution imaging spectroradiometer


North American datum


National Aeronautics and Space Administration


Normalized difference vegetation index


National land cover dataset


United States Geological Survey

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Sunil Kumar
    • 1
  • Sara E. Simonson
    • 1
  • Thomas J. Stohlgren
    • 2
  1. 1.Natural Resource Ecology LaboratoryColorado State UniversityFort CollinsUSA
  2. 2.U.S. Geological SurveyFort Collins Science CenterFort CollinsUSA