Factors affecting detectability of river otters during sign surveys

MacKenzie R. Jeffress, Craig P. Paukert, Brett K. Sandercock, Philip S. Gipson

Research output: Contribution to journalArticlepeer-review

36 Scopus citations


Sign surveys are commonly used to study and monitor wildlife species but may be flawed when surveys are conducted only once and cover short distances, which can lead to a lack of accountability for false absences. Multiple observers surveyed for river otter (Lontra canadensis) scat and tracks along stream and reservoir shorelines at 110 randomly selected sites in eastern Kansas from January to April 2008 and 2009 to determine if detection probability differed among substrates, sign types, observers, survey lengths, and near access points. We estimated detection probabilities (p) of river otters using occupancy models in Program PRESENCE. Mean detection probability for a 400-m survey was highest in mud substrates (p = 0.60) and lowest in snow (p = 0.18) and leaf litter substrates (p = 0.27). Scat had a higher detection probability (p = 0.53) than tracks (p = 0.18), and experienced observers had higher detection probabilities (p > 0.71) than novice observers (p < 0.55). Detection probabilities increased almost 3-fold as survey length increased from 200 m to 1,000 m, and otter sign was not concentrated near access points. After accounting for imperfect detection, our estimates of otter site occupancy based on a 400-m survey increased >3-fold, providing further evidence of the potential negative bias that can occur in estimates from sign surveys when imperfect detection is not addressed. Our study identifies areas for improvement in sign survey methodologies and results are applicable for sign surveys commonly used for many species across a range of habitats.

Original languageEnglish
Pages (from-to)144-150
Number of pages7
JournalJournal of Wildlife Management
Issue number1
StatePublished - Jan 2011


  • Kansas
  • Lontra canadensis
  • detection probability
  • river otter
  • scat
  • sign surveys
  • tracks


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