Using Continuous‐Time Spatial Capture–Recapture models to make inference about animal activity patterns

Abstract

Abstract Quantifying the distribution of daily activity is an important component of behavioral ecology. Historically, it has been difficult to obtain data on activity patterns, especially for elusive species. However, the development of affordable camera traps and their widespread usage has led to an explosion of available data from which activity patterns can be estimated. Continuous‐time spatial capture–recapture (CT SCR) models drop the occasion structure seen in traditional spatial and nonspatial capture–recapture (CR) models and use the actual times of capture. In addition to estimating density, CT SCR models estimate expected encounters through time. Cyclic splines can be used to allow flexible shapes for modeling cyclic activity patterns, and the fact that SCR models also incorporate distance means that space–time interactions can be explored. This method is applied to a jaguar dataset. Jaguars in Belize are most active and range furthest in the evening and early morning and when they are located closer to the network of trails. There is some evidence that females have a less variable pattern than males. The comparison between sexes demonstrates how CT SCR can be used to explore hypotheses about animal behavior within a formal modeling framework. SCR models were developed primarily to estimate and model density, but the models can be used to explore processes that interact across space and time, especially when using the CT SCR framework that models the temporal dimension at a finer resolution.

Keywords

• activity patterns
• behavioral ecology
• continuous‐time spatial capture–recapture
• spatial capture–recapture
• temporal partitioning