Biodiversity and Conservation

, Volume 18, Issue 11, pp 2893–2908 | Cite as

Using habitat suitability models to sample rare species in high-altitude ecosystems: a case study with Tibetan argali

  • Navinder J. Singh
  • Nigel G. YoccozEmail author
  • Yash Veer Bhatnagar
  • Joseph L. Fox
Original Paper


Models of the distribution of rare and endangered species are important tools for their monitoring and management. Presence data used to build up distribution models can be based on simple random sampling, but this for patchy distributed species results in small number of presences and therefore low precision. Convenience sampling, either based on easily accessible units or a priori knowledge of the species habitat but with no known probability of sampling each unit, is likely to result in biased estimates. Stratified random sampling, with strata defined using habitat suitability models [estimated in the resource selection functions (RSFs) framework] is a promising approach for improving the precision of model parameters. We used this approach to sample the Tibetan argali (Ovis ammon hodgsoni) in Indian Transhimalaya in order to estimate their distribution and to test if it can lead to a significant reduction in survey effort compared to random sampling. We first used an initial sample of argali feeding sites in 2005 and 2006 based on a priori selected vantage points and survey transects. This initial sample was used to build up an initial distribution model. The spatial predictions based on estimated RSFs were then used to define three strata of the study area. The strata were randomly sampled in 2007. As expected, much more presences per hour were obtained in the high quality strata compared to the low quality strata—1.33 obs/h vs. 0.080/h. Furthermore the best models selected on the basis of the prospective sample differed from those using the first a priori sample, suggesting bias in the initial sampling effort. The method therefore has significant implications for decreasing sampling effort in terms of sampling time in the field, especially when dealing with rare species, and removing initial sampling bias.


Efficiency Transhimalaya Stratified random sampling Sampling bias Effort 



The University of Tromsø and Rufford Foundation for Nature conservation generously supported the fieldwork. Thanks to Dr. Charudutt Mishra for initial and valuable advice during the preparation of manuscript. Department of Wildlife protection, Jammu and Kashmir provided necessary permits for undertaking the study, thanks to them. Thanks to Nature Conservation Foundation for the support during the preparation of the manuscript. Rinchen, Jigmet and Ajaan Stanzin Dorjey provided essential and inspiring field assistance during field work. We are grateful to all the people and organizations involved in the study. An anonymous referee provided helpful comments on a previous version.


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Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Navinder J. Singh
    • 1
    • 2
  • Nigel G. Yoccoz
    • 1
    Email author
  • Yash Veer Bhatnagar
    • 2
  • Joseph L. Fox
    • 1
  1. 1.Department of Biology, Faculty of Mathematics and Natural SciencesUniversity of TromsøTromsøNorway
  2. 2.Nature Conservation FoundationMysoreIndia

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