Categorizing animal diel movement patterns with examples from high-resolution barn owl tracking

Abstract Background. Movement is central to understanding the ecology of animals. The most easily definable segments of an individual’s lifetime track (i.e., movement path defined by a relocation data time series) are its diel activity routines (DARs). This definability is due to fixed start and end points set by a 24-hour clock that depends on the individual’s quotidian schedule. An analysis of day-today variation in the DARs of individuals and the questions that can be asked, particularly in the context of lunar and annual cycles, and in comparison with other individuals, depends the relocation frequency of movement data. Here we present methods for categorizing the spatio-temporal structure of DARs when the data sampling frequency is on the order of minutes or higher. Methods. Our method involves an initial categorization of DARs with regard to the data pooled across all individuals. We approached this categorization using a Ward clustering algorithm that employs four metrics of trajectory shape (though other measures may equally well be used): 1. openness (distance between start and endpoints, aka net displacement), 2. maximum displacement from start point, 3. maximum diameter, and 4. maximum width. We illustrate the general approach using reverse-GPS data obtained from 44 barn owls, Tyto alba, in northeastern Israel. Results. We clustered 6,230 individual DARs into 7 categories. The first component of principle components analysis, which had the interpretation of DAR size, explained 86.5% of variation. The second, which essentially measure DAR openness, explained 8.4% of variation. We also constructed spatio-temporal distributions of DAR types for individuals and groups of individuals aggregated by age, sex, and seasonal trimester, as well as analyzed the idiosyncratic behavior of individuals within family groups in relation to landscape features. Conclusion. Insights into the types and distributions of DARs in populations may well prove to be more invaluable for predicting the space-use response of individuals and populations to climate and land-use changes than other currently used movement track methods of analysis. anisms of organismal movement, analyzed primarily using relocation data, often collected