Using multiple survey methods to detect terrestrial reptiles and mammals: what are the most successful and cost-efficient combinations?

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Garden, Jenni G
McAlpine, Clive A
Possingham, Hugh P
Jones, Darryl N
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2007
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Abstract

The selection of methods for wildlife surveys is a decision that will influence the accuracy and comprehensiveness of survey outcomes. The choice of methods is commonly based on the species of interest, yet is often limited by the project budget. Although several studies have investigated the effectiveness of various survey techniques for detecting terrestrial mammal and reptile species, none have provided a quantitative analysis of the costs associated with different methods. We compare the detection success and cost efficiency of cage traps, Elliott traps, pit-fall traps, hair funnels, direct observation, and scat detection/analysis for detecting the occurrence of terrestrial reptile and small mammal species in urban bushland remnants of Brisbane City, Queensland, Australia. Cage traps and Elliott traps coupled with hair funnels were the most cost-effective methods for detecting the highest number of ground-dwelling mammal species. Pit-fall traps and direct observations were the most cost-effective methods for maximising the number of reptile species identified. All methods made a contribution to overall detection success by detecting at least one species not detected by any other method. This suggests that a combination of at least two complementary methods will provide the most successful and cost-efficient detection of reptile and mammal species in urban forest remnants. Future studies should explicitly test these findings and examine efficient trapping combinations across different habitat types and for other fauna groups

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Wildlife Research

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34

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3

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© 2007 CSIRO. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.

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Environmental sciences

Biological sciences

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