Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

Modelling Habitat-Suitability Using Museum Collections: An Example with Three Sympatric Apodemus Species from the Alps

Brigitte A. Reutter, V. Helfer, A. H. Hirzel and P. Vogel
Journal of Biogeography
Vol. 30, No. 4 (Apr., 2003), pp. 581-590
Published by: Wiley
Stable URL: http://www.jstor.org/stable/3554503
Page Count: 10
  • Download ($42.00)
  • Subscribe ($19.50)
  • Cite this Item
Modelling Habitat-Suitability Using Museum Collections: An Example with Three Sympatric Apodemus Species from the Alps
Preview not available

Abstract

Aim, Location Although the alpine mouse Apodemus alpicola has been given species status since 1989, no distribution map has ever been constructed for this endemic alpine rodent in Switzerland. Based on redetermined museum material and using the Ecological-Niche Factor Analysis (ENFA), habitat-suitability maps were computed for A. alpicola, and also for the co-occurring A. flavicollis and A. sylvaticus. Methods In the particular case of habitat suitability models, classical approaches (GLMs, GAMs, discriminant analysis, etc.) generally require presence and absence data. The presence records provided by museums can clearly give useful information about species distribution and ecology and have already been used for knowledge-based mapping. In this paper, we apply the ENFA which requires only presence data, to build a habitat-suitability map of three species of Apodemus on the basis of museum skull collections. Results Interspecific niche comparisons showed that A. alpicola is very specialized concerning habitat selection, meaning that its habitat differs unequivocally from the average conditions in Switzerland, while both A. flavicollis and A. sylvaticus could be considered as 'generalists' in the study area. Main conclusions Although an adequate sampling design is the best way to collect ecological data for predictive modelling, this is a time and money consuming process and there are cases where time is simply not available, as for instance with endangered species conservation. On the other hand, museums, herbariums and other similar institutions are treasuring huge presence data sets. By applying the ENFA to such data it is possible to rapidly construct a habitat suitability model. The ENFA method not only provides two key measurements regarding the niche of a species (i.e. marginality and specialization), but also has ecological meaning, and allows the scientist to compare directly the niches of different species.

Page Thumbnails

  • Thumbnail: Page 
[581]
    [581]
  • Thumbnail: Page 
582
    582
  • Thumbnail: Page 
583
    583
  • Thumbnail: Page 
584
    584
  • Thumbnail: Page 
585
    585
  • Thumbnail: Page 
586
    586
  • Thumbnail: Page 
587
    587
  • Thumbnail: Page 
588
    588
  • Thumbnail: Page 
589
    589
  • Thumbnail: Page 
590
    590