NDLI: Quantitative classification of life-style types in predaceous phytoseiid mites

Content Provider	Springer Nature Link
Author	Luh, Hang Kwang A. Croft, Brian
Copyright Year	2001
Abstract	Classification of species into different functional groups based on biological criteria has been a difficult problem in ecology. The difficulty mainly arises because natural classification patterns are not necessarily mutually exclusive. The more group characteristics overlap, the more difficult it is to identify the membership of a species in the overlapping portions of any two groups. In this paper, we present an application of discriminant analysis by creating classification models from life history and morphological data for two specialist and two generalist life-styles type of predaceous phytoseiid mites. Two stages can be distinguished in our method: life-style group membership assignment and trait variable evaluation. We use a Bayesian framework to create a classifier system to locate or assign species within a mixture of trait distributions. The method assumes that a mixture of trait distributions can represent the multiple dimensions of biological data. The mixture is most evident near the boundaries between groups. Because of the complexity of analytical solution, an iterative method is used to estimate the unknown means, variances, and mixing proportion between groups. We also developed a criterion based on information theory to evaluate model performance with different combinations of input variables and different hypotheses. We present a working example of our proposed methods. We apply these methods to the problem of selecting key species for inoculative release and for classical introductions of biological pest control agents.
Starting Page	403
Ending Page	424
Page Count	22
File Format	PDF
ISSN	01688162
Journal	Experimental & Applied Acarology
Volume Number	25
Issue Number	5
e-ISSN	15729702
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2001-01-01
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Animal Systematics/Taxonomy/Biogeography
Content Type	Text
Resource Type	Article
Subject	Ecology Medicine Insect Science

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