NDLI: Estimating the proportions of closely related species: Performance of the two-phase ratio estimator

Content Provider	Springer Nature Link
Author	Hankin, David G. Mohr, Michael S. Voight, Hans
Copyright Year	2009
Abstract	In many ecological field contexts, accurately classifying closely related species based on phenotypic characteristics may be difficult. In such cases, definitive classification of species may require expensive genetic analysis of tissues or extensive quantitative measurements. If inexpensive phenotype-based species classifications are highly correlated with expensive but definitive classifications, however, then estimating the proportion of a target species in a mixed species complex using a two-phase ratio estimator may prove cost-efficient. In two-phase ratio estimation, a first-phase sample is randomly selected, and phenotype is used to classify all individuals in the sample. A smaller, second-phase sample is then randomly selected from the first-phase sample, and a definitive method is used to classify the individuals in this subsample. Net relative efficiency (i.e., cost-effectiveness) of the optimally allocated two-phase ratio estimator of a proportion depends on the relative costs of classification at the first and second phases, on the phenotypic classification accuracy for the target species (sensitivity) and nontarget species (specificity), and on the magnitude of the target species proportion. Results are presented that allow assessment of the circumstances in which this two-phase estimation approach can be recommended over an equal-cost single-phase approach based only on expensive but definitive classification. An illustrative application of these methods is provided using an example of two closely related, sympatric, anadromous salmonid species: steelhead (Oncorhynchus mykiss) and coastal cutthroat trout (O. clarki clarki).
Starting Page	15
Ending Page	32
Page Count	18
File Format	PDF
ISSN	10857117
Journal	Journal of Agricultural, Biological, and Environmental Statistics
Volume Number	14
Issue Number	1
e-ISSN	15372693
Language	English
Publisher	Springer-Verlag
Publisher Date	2009-01-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Double sampling Proportion Ratio estimation Sensitivity Species classification Specificity Two-phase sampling Statistics for Life Sciences, Medicine, Health Sciences Agriculture Environmental Monitoring/Analysis Biostatistics
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Statistics and Probability Environmental Science Agricultural and Biological Sciences Statistics, Probability and Uncertainty

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