Natural Resource Ecology and Management 929-2014 Re-Evaluating Neonatal-Age Models for Ungulates : Does Model Choice Affect Survival Estimates ?

New-hoof growth is regarded as the most reliable metric for predicting age of newborn ungulates, but variation in estimated age among hoof-growth equations that have been developed may affect estimates of survival in staggered-entry models. We used known-age newborns to evaluate variation in age estimates among existing hoof-growth equations and to determine the consequences of that variation on survival estimates. During 2001–2009, we captured and radiocollared 174 newborn (≤24-hrs old) ungulates: 76 white-tailed deer (Odocoileus virginianus) in Minnesota and South Dakota, 61 mule deer (O. hemionus) in California, and 37 pronghorn (Antilocapra americana) in South Dakota. Estimated age of known-age newborns differed among hoof-growth models and varied by >15 days for white-tailed deer, >20 days for mule deer, and >10 days for pronghorn. Accuracy (i.e., the proportion of neonates assigned to the correct age) in aging newborns using published equations ranged from 0.0% to 39.4% in white-tailed deer, 0.0% to 3.3% in mule deer, and was 0.0% for pronghorns. Results of survival modeling indicated that variability in estimates of age-at-capture affected short-term estimates of survival (i.e., 30 days) for white-tailed deer and mule deer, and survival estimates over a longer time frame (i.e., 120 days) for mule deer. Conversely, survival estimates for pronghorn were not affected by estimates of age. Our analyses indicate that modeling survival in daily intervals is too fine a temporal scale when age-at-capture is unknown given the potential inaccuracies among equations used to estimate age of neonates. Instead, weekly survival intervals are more appropriate because most models accurately predicted ages within 1 week of the known age. Variation among results of neonatalage models on shortand long-term estimates of survival for known-age young emphasizes the importance of selecting an appropriate hoof-growth equation and appropriately defining intervals (i.e., weekly versus daily) for estimating survival. Disciplines Ecology and Evolutionary Biology | Natural Resources Management and Policy | Statistics and Probability | Zoology Comments This article is published as Grovenburg, Troy W. , Kevin L. Monteith, Christopher N. Jacques, Robert W. Klaver, Christopher S. DePerno, Todd J. Brinkman, Kyle B. Monteith et al. "Re-evaluating neonatal-age models for ungulates: does model choice affect survival estimates? " PloS one 9, no. 9 (2014): e108797, doi: 10.1371/journal.pone. 0108797. Rights This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. This article is available at Iowa State University Digital Repository: http://lib.dr.iastate.edu/nrem_pubs/230 Authors Troy W. Grovenburg, Kevin L. Monteith, Christopher N. Jacques, Robert W. Klaver, Christopher S. DePerno, Todd J. Brinkman, Kyle B. Monteith, Sophie L. Gilbert, Joshua B. Smith, Vernon C. Bleich, Christopher C. Swanson, and Jonathan A. Jenks This article is available at Iowa State University Digital Repository: http://lib.dr.iastate.edu/nrem_pubs/230 Re-Evaluating Neonatal-Age Models for Ungulates: Does Model Choice Affect Survival Estimates? Troy W. Grovenburg*, Kevin L. Monteith, Christopher N. Jacques, Robert W. Klaver, Christopher S. DePerno, Todd J. Brinkman, Kyle B. Monteith, Sophie L. Gilbert, Joshua B. Smith, Vernon C. Bleich, Christopher C. Swanson, Jonathan A. Jenks 1 Department of Natural Resource Management, South Dakota State University, Brookings, South Dakota, United States of America, 2 Wyoming Cooperative Fish and Wildlife Research Unit, Department of Zoology and Physiology, University of Wyoming, Laramie, Wyoming, United States of America, 3 Department of Biological Sciences, Western Illinois University, Macomb, Illinois, United States of America, 4 U.S. Geological Survey, Iowa Cooperative Fish and Wildlife Research Unit, Department of Natural Resource Ecology and Management, Iowa State University, Ames, Iowa, United States of America, 5 Department of Forestry and Environmental Resources, Fisheries, Wildlife, and Conservation Biology, North Carolina State University, Raleigh, North Carolina, United States of America, 6 Institute of Arctic Biology and Department of Biology and Wildlife, University of Alaska Fairbanks, Fairbanks, Alaska, United States of America, 7 Sierra Nevada Bighorn Sheep Recovery Program, California Department of Fish and Game, Bishop, California, United States of America, 8 U.S. Fish and Wildlife Service, Kulm, North Dakota, United States of America