Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2004-8-2
pubmed:abstractText
Basal metabolic rate (BMR) is often predicted by allometric interpolation, but such predictions are critically dependent on the quality of the data used to derive allometric equations relating BMR to body mass (Mb). An examination of the metabolic rates used to produce conventional and phylogenetically independent allometries for avian BMR in a recent analysis revealed that only 67 of 248 data unambiguously met the criteria for BMR and had sample sizes with n>/=3. The metabolic rates that represented BMR were significantly lower than those that did not meet the criteria for BMR or were measured under unspecified conditions. Moreover, our conventional allometric estimates of BMR (W; logBMR=-1.461+0.669logMb) using a more constrained data set that met the conditions that define BMR and had n>/=3 were 10%-12% lower than those obtained in the earlier analysis. The inclusion of data that do not represent BMR results in the overestimation of predicted BMR and can potentially lead to incorrect conclusions concerning metabolic adaptation. Our analyses using a data set that included only BMR with n>/=3 were consistent with the conclusion that BMR does not differ between passerine and nonpasserine birds after taking phylogeny into account. With an increased focus on data mining and synthetic analyses, our study suggests that a thorough knowledge of how data sets are generated and the underlying constraints on their interpretation is a necessary prerequisite for such exercises.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1522-2152
pubmed:author
pubmed:issnType
Print
pubmed:volume
77
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
502-21
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:articleTitle
The allometry of avian basal metabolic rate: good predictions need good data.
pubmed:affiliation
Biology Department, MSC03-2020, University of New Mexico, Albuquerque, New Mexico 87131-0001, USA. mckechnie@gecko.biol.wits.ac.za
pubmed:publicationType
Journal Article, Comparative Study, Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't, Meta-Analysis