TY - JOUR
T1 - Type I errors linked to faulty statistical analyses of endangered subspecies classifications
AU - Skalski, John R.
AU - Townsend, Richard L.
AU - McDonald, Lyman L.
AU - Kern, John W.
AU - Millspaugh, Joshua J.
PY - 2008/6
Y1 - 2008/6
N2 - Legal issues related to subspecies identification frequently occur through the implementation of the 1973 Endangered Species Act (ESA). A listing under the ESA requires management actions to ensure the continued existence of the taxa. However, these actions often have important social, economic, and political implications. We examined the statistical methods of morphological analysis used in subspecies identification. Methods are illustrated using the California gnatcatcher (Polioptila californica), which was incorrectly listed under the ESA due to misinterpretation of morphological data. We found that inferences based on tests of sample means (i.e., t-test, Hotelling's T2-statistic), cluster analysis, and discriminant analysis were subject to high rates of false positives (identification of subspecies when none exist; Type I error). These simple tests ignore the common occurrence of spatial clines in animal tracts. Alternatively, spline-regression and step-regression procedures were found to be quite robust yet had high resolution in finding subspecies break locations.
AB - Legal issues related to subspecies identification frequently occur through the implementation of the 1973 Endangered Species Act (ESA). A listing under the ESA requires management actions to ensure the continued existence of the taxa. However, these actions often have important social, economic, and political implications. We examined the statistical methods of morphological analysis used in subspecies identification. Methods are illustrated using the California gnatcatcher (Polioptila californica), which was incorrectly listed under the ESA due to misinterpretation of morphological data. We found that inferences based on tests of sample means (i.e., t-test, Hotelling's T2-statistic), cluster analysis, and discriminant analysis were subject to high rates of false positives (identification of subspecies when none exist; Type I error). These simple tests ignore the common occurrence of spatial clines in animal tracts. Alternatively, spline-regression and step-regression procedures were found to be quite robust yet had high resolution in finding subspecies break locations.
KW - California gnatcatcher (Polioptila californica)
KW - Cluster analysis
KW - Discriminant analysis
KW - Multivariate statistics
KW - Spatial statistics
KW - Spline-regression
KW - Step- regression
KW - Subspecies
KW - Taxonomy
UR - http://www.scopus.com/inward/record.url?scp=56449098227&partnerID=8YFLogxK
U2 - 10.1198/108571108X310771
DO - 10.1198/108571108X310771
M3 - Article
AN - SCOPUS:56449098227
SN - 1085-7117
VL - 13
SP - 199
EP - 220
JO - Journal of Agricultural, Biological, and Environmental Statistics
JF - Journal of Agricultural, Biological, and Environmental Statistics
IS - 2
ER -