Prediction of marsupial body mass
Prediction of marsupial body mass
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DOI：
10.1071/zo01009
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发表时间：
2001-01-01
影响因子：
0.8
通讯作者：
Myers, TJ
中科院分区：
文献类型：
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作者：
Myers, TJ
颅齿变量与有袋动物的体重相关，使用来自现存的澳大利亚代表的物种数据集，预测化石物种的体重。本文分析了38个现存的澳大利亚动物种，其中毛形类10种，双齿类22种，背形类1种，穿孔类5种。当性别二态性突出时，性别被单独评估。29颅牙变量进行了测量，每个标本和物种的平均值计算。根据每个标本的记录或公布的物种平均值采集体重。每个形态物种的颅齿测量，然后回归对平均体重在四个不同的数据集：（1）整个物种样本，（2）只有dasyromorphian类群，（3）只有diprotodontians，（4）所有物种不包括dasyromorphian。然后根据各种误差统计和相关系数对每个颅牙变量进行排名。结果表明，预测的身体大小在真兽目（如第一下臼齿面积），通常用于估计有袋动物的体重可能不是可靠或准确的指标。分类学数据集之间的预测变量的有用性也有显着差异。总颌骨长度是最可靠的预测diprotodontians，以及所有物种的组合，而下臼齿行长度似乎更适合dasyuromorphians。多变量回归模型比从单个参数得到的模型提供更高的精度。
Cranio-dental variables are correlated with body mass in marsupials, using a species data-set derived from extant australidelphian representatives, to predict body mass in fossil species. Thirty-eight extant australidelphian species, including 10 dasyuromorphians, 22 diprotodontians, 1 notoryctomorphian and 5 peramelemorphians, were analysed. Where sexual dimorphism was prominent, genders were evaluated separately. Twenty-nine cranio-dental variables were measured for each specimen and species averages calculated. Body masses were taken as recorded for each specimen or as published species averages. The cranio-dental measures for each morpho-species were then regressed against average body mass in four distinct data-sets: (1) the entire species sample, (2) only dasyuromorphian taxa, (3) only diprotodontians, and (4) all species excluding dasyuromorphians. Each cranio-dental variable was then ranked according to various error statistics and correlation coefficients. Results suggest that predictors of body size in eutherians (such as first lower molar area), commonly used to estimate body mass in marsupials may not be reliable or accurate indicators. Significant differences in the usefulness of predictor variables between taxonomic data-sets were also observed. Total jaw length is the most reliable predictor for diprotodontians, as well as for all species combined, whereas lower molar row length appears to be more appropriate for dasyuromorphians. Multiple variable regressions variably offer more precision than those derived from individual parameters.