4.1 Article

A Modification of Jacobson et al.'s (1997) Individual Branch-Antlered Male Method for Censusing White-Tailed Deer

Journal

WILDLIFE SOCIETY BULLETIN
Volume 35, Issue 4, Pages 445-451

Publisher

WILEY
DOI: 10.1002/wsb.64

Keywords

abundance; camera traps; census technique; detection; Odocoileus virginianus; sex ratios; trap success; white-tailed deer

Funding

  1. Conservation Fund of the Campfire Club of America
  2. MRGP
  3. AE Charitable Foundation
  4. Dorr Foundation

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Jacobson et al.'s (1997) individual branch-antlered male (IBAM) method is a popular camera technique for estimating white-tailed deer (Odocoileus virginianus) abundance. Demographic ratios are estimated from raw photographic occurrences (RPO) of males, females, and fawns. Point abundance estimates of each group are estimated by using said ratios to extrapolate from a count of uniquely identifiable males. In 2009, using camera-trap data from the Mianus River Gorge Preserve (NY), we modified the IBAM technique to 1) generate measures of uncertainty for parameter estimates via bootstrapping camera stations, and 2) address the concern that RPO ratios may be biased if groups of animals differ in their probability of being photographed (e.g., trap success [TS]). For each sex-age group, we evaluated RPO as a function of TS using linear regression to generate photographic counts standardized by TS (standardized photographic occurrences [SPO]). We generated estimates of sex-age ratios and abundances using both RPO and SPO. To evaluate the accuracy of using SPO in conjunction with the IBAM method, we independently estimated the abundance of a marked group of female deer using a Poisson log normal (PNE) mark-resight estimator. Abundance estimates across sex-age classes were most similar between PNE and IBAM when SPO demographic ratios were used. Owing to the greater TS of females, using SPO discounted the relative abundance of females and, thus, lowered the female: male ratios and raised the fawn: female ratio. Uncertainty was broad across all approaches, yet accounting for TS reduced the confounding variability owing to differences in detection probability and generated more accurate parameter estimates. (C) 2011 The Wildlife Society.

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