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Feeding Decisions by Steller’s Jays ( Cyanocitta stelleri ): The Utility of a Logistic Regression Model for Analyses of Where, What, and with Whom to Eat
Author(s) -
Bekoff Marc,
Allen Colin,
Grant Michael C.
Publication year - 1999
Publication title -
ethology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.739
H-Index - 74
eISSN - 1439-0310
pISSN - 0179-1613
DOI - 10.1046/j.1439-0310.1999.00438.x
Subject(s) - univariate , logistic regression , psychology , statistics , multivariate statistics , mathematics
It is widely recognized that animal behavior is simultaneously affected by many variables. Both the study of interactions between these variables under naturalistic conditions and the proper statistical analysis of data derived from such studies remain particular problems for ethologists. In the present study we investigated choices by Steller’s jays ( Cyanocitta stelleri ) selecting between two feeding locations under a variety of conditions. A multifactor logistic regression analysis of our data showed that the jays’ behavior was simultaneously affected by several variables, including proximity of the feeding site to cover, food preferences, and the presence of conspecifics and other animals. We found that (1) jays strongly preferred an unoccupied feeder over one occupied by another jay or a sympatric mammal with the effect of squirrels being much greater than that of other jays, (2) contrary to our expectations, in the absence of a reason to prefer the other feeder, the jays generally selected the feeder that was further from nearest cover, and (3) the presence of sunflower seeds on one feeder but not on the other provided a reason to prefer the feeder offering sunflower seeds. The logistic regression analysis provided a more complete and integrated model of the birds’ behavior than more commonly used univariate methods. Our approach and results are also applicable to studies of other animals. While univariate analyses are useful in some instances, multifactor procedures reveal more details about the interactions of single factors and future experimental studies can take advantage of this additional knowledge.

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