Knowledge of body condition is important in predicting health and performance of large mammal populations. Therefore, we assessed body condition in black bears (Ursus americanus) in Rocky Mountain National Park (RMNP), Colorado, using body mass (BM), percent body fat (BF) and a body condition index (BCI) to: (1) develop a model predictive of BM for bears in RMNP using morphometric measures, (2) compare three models predictive of BM to provide further information on the influence of elevation and more complex models on model accuracy, and (3) assess the relationship between BF and BCI to determine if BF could be estimated from BCI. Our best BM model included only girth (r2 = 0.923) and indicated that mass-morphology relationships were more consistent within specified elevation zones; complexity of models had little influence on model efficiency. We also observed a strong relationship between BF and BCI (r2 = 0.962) indicating that BCI scores can be accurately converted to estimates of BF. This predictive equation should prove useful to black bear managers in situations where BF cannot be estimated using more direct methods.
You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither BioOne nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the BioOne website.
Vol. 164 • No. 1