Present address: Department of Geosciences and Geography, University of Helsinki, PO Box 64, FI-00014, Finland.
Species distribution modelling in low-interaction environments: Insights from a terrestrial Antarctic system
Article first published online: 16 MAY 2012
© 2012 The Authors. Austral Ecology © 2012 Ecological Society of Australia
Volume 38, Issue 3, pages 279–288, May 2013
How to Cite
LEE, J. E., LE ROUX, P. C., MEIKLEJOHN, K. I. and CHOWN, S. L. (2013), Species distribution modelling in low-interaction environments: Insights from a terrestrial Antarctic system. Austral Ecology, 38: 279–288. doi: 10.1111/j.1442-9993.2012.02401.x
- Issue published online: 23 APR 2013
- Article first published online: 16 MAY 2012
- Accepted for publication March 2012.
- British Antarctic Survey
- SANAP. Grant Numbers: SNA200704200003, SNA2005061300001
- soil moisture;
- species distribution model
It is widely acknowledged that in the terrestrial Antarctic, interspecific interactions are typically unimportant in determining species distributions and community structure. Therefore, correlative models should prove useful for predicting current and future spatial variation in species abundance patterns. However, this idea has not been formally tested, and the utility of such models, which have shown value for understanding the distribution of diversity elsewhere, for investigating biodiversity patterns in Antarctica remains unclear. Here we make a start at such tests by using generalized linear and simultaneous autoregressive models to demonstrate that simple environmental variables and information about the spatial structure of the environment can explain more than 90% of the variation in the abundance of Maudheimia wilsoni (Oribatida; Maudheimiidae), a representative of one of the most significant groups of Antarctic terrestrial arthropods, the mites. We show that a single environmental variable, maximum soil moisture content, can account for as much as 80% of the variance in the abundance of the mite, and that linear models with only a few environmental and spatial terms can be used to forecast the species abundance at the landscape scale. Given ongoing calls for better understanding of the distribution of Antarctic diversity and its likely future change, this initial test indicates that such modelling procedures, and more sophisticated versions thereof, hold much promise for the region and should be tested for other taxa with different life forms and habitat requirements.