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Regressions of length and width to predict arthropod biomass in the Hawaiian Islands

dc.contributor.authorGruner, Daniel
dc.identifier.citationGruner, D. S. 2003. Regressions of length and width to predict arthropod biomass in the Hawaiian Islands. Pacific Science 57:325-336.en
dc.description.abstractBiologists in many fields use published regression equations to predict biomass from simple linear body measurements. Power functions are used with arthropods, facilitating biomass estimation of a sample when destructive techniques are not feasible. Resulting predictive coefficients vary widely depending on region and taxa. There are no published biomass regressions for oceanic island fauna, despite the widely accepted conclusion that their arthropod assemblages are unusual in composition. I present a suite of general and taxonomically and morphologically restricted regression equations developed for arthropods in the Hawaiian Islands. General regression equations were highly significant when only length was used to predict biomass, but fits were usually improved by including body width. In regressing restricted sets of taxa, the addition of width did little to improve the fit of the functions. Thus, the choice of regression equations involves a trade-off in taxonomic resolution: precise biomass estimates will come either from (1) low taxonomic resolution measured for both length and width, or (2) high taxonomic resolution measured only for body length. These equations have a high predictive capacity for a broad range of arthropod taxa common in the Hawaiian Islands and, in the absence of locally developed equations, the arthropods of other oceanic islands.en
dc.format.extent122309 bytes
dc.publisherPacific Scienceen
dc.subjectregression analysisen
dc.subjectbody lengthen
dc.subjectbody widthen
dc.subjectMetrosideros polymorphaen
dc.titleRegressions of length and width to predict arthropod biomass in the Hawaiian Islandsen
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_us
dc.relation.isAvailableAtCollege of Chemical & Life Sciencesen_us
dc.relation.isAvailableAtUniversity of Maryland (College Park, MD)en_us

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