Premium
Relationship between field metabolic rate and body weight in mammals: effect of the study
Author(s) -
Riek A.
Publication year - 2008
Publication title -
journal of zoology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.915
H-Index - 96
eISSN - 1469-7998
pISSN - 0952-8369
DOI - 10.1111/j.1469-7998.2008.00482.x
Subject(s) - allometry , body weight , statistics , exponent , metabolic rate , random effects model , biology , measure (data warehouse) , regression analysis , field (mathematics) , mathematics , meta analysis , medicine , endocrinology , ecology , linguistics , philosophy , database , pure mathematics , computer science
Field metabolic rate (FMR) is a measure of daily energy expenditure under field conditions. Results of various studies on FMR have been used to calculate allometric equations that can predict FMR from body weight. One of the problems in calculating these regression equations lies in the treatment of the available FMR and body weight data. However, with the tool of mixed model analysis, it is possible to account for the effect of the study as a random effect in this kind of meta‐analysis. The present study is the first that has included the study as a random effect in an FMR meta‐analysis. Prediction equations were derived, allowing the estimation of FMR based on body weight. Including all available single animal data on FMR and body mass in a mixed model analysis with the study as a random effect yielded the equation: FMR in kJ day −1 =6.68 ± 1.21 (body weight in g) 0.67 ± 0.03 ( P <0.001) that had a mean error rate of 21.5% ( sd 29.0%, minimum 0, maximum 236%) and a coefficient of variation of 98%. This was c . 2.7 times more precise than not including the study effect (mean error rate 58.4%). Thus, the present investigation showed that including the effect of the study in FMR meta‐analysis changes not only the predictive values of the equation but also the exponent (slope).