Revisions of Rump Fat and Body Scoring Indices for Deer, Elk, and Moose
Revisions of Rump Fat and Body Scoring Indices for Deer, Elk, and Moose
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DOI：
10.2193/2009-031
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发表时间：
2010-05-01
影响因子：
2.3
通讯作者：
Miller, Patrick J.
中科院分区：
文献类型：
--
作者：
Cook, Rachel C.;Cook, John G.;Miller, Patrick J.
由于它们不需要牺牲动物，身体状况评分（BCS），臀部脂肪厚度（MAXFAT）和其他类似的体脂预测指标已经推进了有蹄类动物营养状况的估计，并且在过去十年中在北美的使用已经激增。然而，对这些预测因子的初步测试过于有限，无法评估其在整个非洲大陆不同栖息地、生态类型、亚种和种群之间的可靠性。通过在初始模型开发期间从黑尾鹿（Odocoileus hemionus）、麋鹿（Cervus elaphus）和驼鹿（Alces alces）收集的数据以及随后从美国西部大部分地区的自由放养黑尾鹿和麋鹿群收集的数据，我们评估了可靠性比最初可用的条件范围更广。首先，为了更严格地测试MAXFAT指数的可靠性，我们使用异速生长缩放函数来调整动物大小的差异，评估了其在3个物种中的稳健性。然后，我们评估了MAXFAT，臀部身体状况评分（rBCS），rLIVINDEX（MAXFAT和rBCS的算术组合），和我们新的异速生长缩放臀部脂肪厚度指数使用815个自由放养的雌性罗斯福和落基山麋鹿（C。e. roosevelti和C. e. nelsoni）和来自7个种群和2个地区的250只自由放养的雌性黑尾鹿。我们测试了亚种的影响，地理区域，圈养与自由放养的存在。当与体重进行异速生长缩放时，在38-522 kg体重范围内，臀部脂肪厚度与无摄入体脂肪相关（r（2）= 0.87; P < 0.001），表明该技术在我们分析的至少3种鹿科动物中非常可靠。然而，我们发现，对于体脂> 12%的麋鹿，rBCS存在显著偏倚。这种偏见转化为亚种之间的差异，因为在我们的样本中，落基山麋鹿往往比罗斯福麋鹿更胖。观察者误差与rBCS的影响也存在与中度至高水平的体脂肪的黑尾鹿，和鹿的身体大小显着影响的准确性的MAXFAT预测。我们的分析证实了这3个物种的臀部脂肪指数的稳健性，但强调了由于体型差异和BCS评分的观察者误差而产生偏倚的可能性。我们提出了替代LIVINDEX方程，其中消除或减少了来自rBCS的潜在偏倚和由于身体尺寸引起的偏倚。这些修改提高了用于监测畜群营养状况或评估营养对人口统计学影响的项目的体脂估计的准确性。
Because they do not require sacrificing animals, body condition scores (BCS), thickness of rump fat (MAXFAT), and other similar predictors of body fat have advanced estimating nutritional condition of ungulates and their use has proliferated in North America in the last decade. However, initial testing of these predictors was too limited to assess their reliability among diverse habitats, ecotypes, subspecies, and populations across the continent. With data collected from mule deer (Odocoileus hemionus), elk (Cervus elaphus), and moose (Alces alces) during initial model development and data collected subsequently from free-ranging mule deer and elk herds across much of the western United States, we evaluated reliability across a broader range of conditions than were initially available. First, to more rigorously test reliability of the MAXFAT index, we evaluated its robustness across the 3 species, using an allometric scaling function to adjust for differences in animal size. We then evaluated MAXFAT, rump body condition score (rBCS), rLIVINDEX (an arithmetic combination of MAXFAT and rBCS), and our new allometrically scaled rump-fat thickness index using data from 815 free-ranging female Roosevelt and Rocky Mountain elk (C. e. roosevelti and C. e. nelsoni) from 19 populations encompassing 4 geographic regions and 250 free-ranging female mule deer from 7 populations and 2 regions. We tested for effects of subspecies, geographic region, and captive versus free-ranging existence. Rump-fat thickness, when scaled allometrically with body mass, was related to ingesta-free body fat over a 38-522-kg range of body mass (r(2) = 0.87; P < 0.001), indicating the technique is remarkably robust among at least the 3 cervid species of our analysis. However, we found an underscoring bias with the rBCS for elk that had > 12% body fat. This bias translated into a difference between subspecies, because Rocky Mountain elk tended to be fatter than Roosevelt elk in our sample. Effects of observer error with the rBCS also existed for mule deer with moderate to high levels of body fat, and deer body size significantly affected accuracy of the MAXFAT predictor. Our analyses confirm robustness of the rump-fat index for these 3 species but highlight the potential for bias due to differences in body size and to observer error with BCS scoring. We present alternative LIVINDEX equations where potential bias from rBCS and bias due to body size are eliminated or reduced. These modifications improve the accuracy of estimating body fat for projects intended to monitor nutritional status of herds or to evaluate nutrition's influence on population demographics.