Journal article
Validating Predictive Models of Nutritional Condition for Mule Deer
The Journal of wildlife management, Vol.71(6), pp.1934-1943
08/2007
Handle:
https://hdl.handle.net/2376/107981
Abstract
: We developed new, and validated existing, indices of nutritional condition for live and dead mule deer (Odocoileus hemionus). Live animal indices included a body condition score (BCS), thickness of subcutaneous fat and selected muscles using ultrasonography, and body mass. Dead animal indices included femur, metatarsal, and mandible marrow fat, 3 kidney fat indices, and 2 carcass scoring methods. We used 21 female deer and 4 castrates (1‐11 yr old) varying widely in nutritional condition (2‐28% ingesta‐free body fat). Deer were euthanized and homogenized for chemical analysis of fat, protein, water, and ash content. Estimates of fat and gross energy (GE) were regressed against each condition indicator using regression. Subcutaneous fat thickness, a rump BCS, and rLIVINDEX (an arithmetic combination of subcutaneous fat thickness and the rump BCS) were most related to condition for live animals (r2 ≥ 0.87, P < 0.001) whereas the Kistner score and kidney fat were most related to fat and GE for dead animals (r2 ≥ 0.77, P < 0.001). We also evaluated range of usefulness and sensitivity to small changes in body condition for all models. In general, indices with moderate or highly curvilinear statistical relations to body fat or those based on only one fat depot or a small number of ranking scores will have limitations in their use. Our results identify robust tools for a variety of research and monitoring designs useful for evaluating nutrition's effect on mule deer populations.
Metrics
16 Record Views
Details
- Title
- Validating Predictive Models of Nutritional Condition for Mule Deer
- Creators
- RACHEL C COOKTHOMAS R STEPHENSONWOODROW L MYERSJOHN G COOKLISA A SHIPLEY
- Publication Details
- The Journal of wildlife management, Vol.71(6), pp.1934-1943
- Academic Unit
- Environment, School of the (CAHNRS)
- Publisher
- Blackwell Publishing Ltd; Oxford, UK
- Number of pages
- 10
- Identifiers
- 99900547148501842
- Language
- English
- Resource Type
- Journal article