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Welcome to the interactive web schedule for the 2019 Midwest Fish & Wildlife Conference! The schedule is subject to change (as of November 7, 2018). Please check back for updates. To return to the main Conference website, go to: www.midwestfw.org.

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Monday, January 28 • 4:00pm - 4:20pm
(WILDLIFE: CERVIDS) Evaluation of an Ek Detection Probability Model in the Black Hills, South Dakota

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AUTHORS: Christopher Jacques, Western Illinois University; Evan Phillips, Colorado Parks and Wildlife; Angela Jarding, National Park Service; Susan Rupp, Enviroscapes Ecological Consulting, LLC; Robert Klaver, U.S. Geological Survey; Chadwick Lehman, South Dakota Game, Fish and Parks; Jonathan Jenks, South Dakota State University ABSTRACT: Since 1993, elk (Cervus canadensis nelsoni) abundance in the Black Hills of South Dakota has been estimated using a detection probability model previously developed in Idaho, though are likely negatively biased because of a failure to account for visibility biases under local conditions.  To correct for this bias, we evaluated the current detection probability across the Black Hills during January and February 2009-2011 using radiocollared elk.  We used logistic regression to evaluate topographic features, habitat characteristics, and group characteristics relative to their influence on detectability of elk.  Elk detection probability increased with less vegetation cover (%), increased group size, and snow cover (%); overall detection probability was 0.60 (95% CI = 0.52-0.68) with 91 of 152 elk groups detected. Predictive capability of the selected model was excellent (ROC = 0.807), and prediction accuracy ranged from 70.2% to 73.7%.  Cross-validation of the selected model with other population estimation methods resulted in comparable estimates.  Application of our model should be applied cautiously if characteristics of the area (e.g., vegetation cover > 50%, snow cover > 90%, group sizes > 16 elk) differ notably from the range of variability in these factors under which the model was developed. 

Monday January 28, 2019 4:00pm - 4:20pm
CENTER STREET ROOM D