A permutation-based combination of sign tests for assessing habitat selection
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The analysis of habitat selection in radio-tagged animals is approached by comparing the portions of use against the portions of availability observed for each habitat type. Since data are linearly dependent with singular variance-covariance matrices, standard multivariate statistical tests cannot be applied. To bypass the problem, compositional data analysis is customarily performed via log-ratio transform of sample observations. The procedure is criticized in this paper, emphasizing the several drawbacks which may arise from the use of compositional analysis. An alternative nonparametric solution is proposed in the framework of multiple testing. The habitat use is assessed separately for each habitat type by means of the sign test performed on the original observations. The resulting p values are combined in an overall test statistic whose significance is determined permuting sample observations. The theoretical findings of the paper are checked by simulation studies. Applications to case studies previously considered in literature are discussed.
KeywordsCompositional data analysis Johnson’s second order selection Johnson’s third order selection Monte Carlo studies Multiple testing Random habitat use
Proportional or random habitat use
Portion of animal trajectory
Portion of animal home range
Compositional data analysis
The authors thank Luca Pratelli for his helpful suggestions in the theoretical aspects of the work.
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