Eigenanalysis of selection ratios from animal radio-tracking data

Area of Science:

• Ecology
• Wildlife Biology
• Quantitative Ecology

Background:

• Analyzing habitat selection in radio-tracking studies with multiple resource categories is challenging.
• Existing methods like White and Garrott statistic and Manly's selection ratio have limitations with large datasets.

Purpose of the Study:

• To introduce a novel method, eigenanalysis of selection ratios, for analyzing habitat selection.
• To generalize and optimize existing statistical approaches for habitat selection studies.

Main Methods:

• The eigenanalysis of selection ratios generalizes White and Garrott statistic and Manly's selection ratio.
• This method uses additive linear partitioning to maximize differences between habitat use and availability.
• The analysis is applicable to both uniform (design II) and variable (design III) habitat availability across animals.

Main Results:

• Application to radio-tracking data of 17 squirrels in five habitat types revealed significant variability in habitat selection.
• Two distinct groups of animals exhibited different habitat preference patterns.
• These patterns were correlated with the patch structure of the study area.

Conclusions:

• The eigenanalysis of selection ratios is an optimal and exploratory tool for habitat selection studies.
• The method is robust as it does not rely on distributional assumptions.
• It effectively identifies patterns of habitat preference and their ecological drivers.