2011
DOI: 10.1002/jwmg.23
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Evaluating how hunters see and react to telemetry collars on white‐tailed deer

Abstract: Fates of individuals outfitted with radiotransmitters commonly are used for estimating survival rates in populations of large animals that are hunted. Despite precautions, this practice may be subject to complex biases associated with hunter reaction to presence of radiotransmitters. To assess this potential bias we conducted an experiment using artificial deer (i.e., decoys) to measure hunters' abilities to see deer and determine if deer seen were wearing radiocollars. We used logistic regression to quantify … Show more

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Cited by 15 publications
(42 citation statements)
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“…Despite finding only limited evidence for an effect of a radio collar on harvest rates, we believe the presence of a radio collar may influence whether some hunters decide to harvest a deer. Furthermore, we agree with Jacques et al () that hunter behavior is likely heterogeneous and, depending on the hunter, could be manifested as either an increased or reduced likelihood of harvesting a radio‐collared deer. For example, in our survey of hunters, a nearly equal percentage of hunters agreed and disagreed with the statement that they were less willing to harvest an antlerless deer with a radio collar (Table ) and could explain why we found no effect of collars on female harvest rates.…”
Section: Discussionsupporting
confidence: 92%
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“…Despite finding only limited evidence for an effect of a radio collar on harvest rates, we believe the presence of a radio collar may influence whether some hunters decide to harvest a deer. Furthermore, we agree with Jacques et al () that hunter behavior is likely heterogeneous and, depending on the hunter, could be manifested as either an increased or reduced likelihood of harvesting a radio‐collared deer. For example, in our survey of hunters, a nearly equal percentage of hunters agreed and disagreed with the statement that they were less willing to harvest an antlerless deer with a radio collar (Table ) and could explain why we found no effect of collars on female harvest rates.…”
Section: Discussionsupporting
confidence: 92%
“…We concluded our data provided limited support for the hypothesis that the presence of a radio collar on a deer causes a systematic bias in harvest rate estimates because of hunter selectivity. We failed to detect a difference for males during 2002–2004 and females during 2009–2011, and the differences we detected for yearling and adult males during 2009–2011 were opposite of what we predicted and as was indicated by Jacques et al (). Although the estimated differences for these male harvest rates were large enough to have management implications (Table ), we cannot explain why radio‐collared adult males would be less likely to be harvested when our survey of hunters suggested that the presence of a radio collar would be less likely to affect their decision to harvest a large‐antlered deer.…”
Section: Discussioncontrasting
confidence: 86%
“…Prior to analyses, we posited biologically plausible logistic regression models of how observations of pronghorn might be influenced by group size, group behavior, cover type, percent vegetation, and topography (Table ); all models were additive without interactions. Our justification for inclusion of model covariates under an information theoretic approach to analysis (Burnham and Anderson , Jacques et al ) included: Group size (GS). Group size has been identified as influencing detection probability of moose ( Alces americanus ; Gasaway et al ) and elk ( Cervus elaphus ; Samuel et al , Cogan and Diefenbach ).…”
Section: Methodsmentioning
confidence: 99%
“…Group size data were not normally distributed so we log transformed these data and incorporated the number of pronghorns in a group on a log scale as a covariate in our regression models. We used Akaike's Information Criterion (AIC) to select models that best described the data and used Akaike weights ( w i ) as a measure of relative support for model fit (Burnham and Anderson , Jacques et al ). We used model averaging to account for model selection uncertainty (Burnham and Anderson ).…”
Section: Methodsmentioning
confidence: 99%
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