Performance of five statistical methods to infer interactions among moving individuals in a predator–prey system

Abstract

Abstract Rapid development of tracking technologies allow the collection of high‐quality data on multiple simultaneously moving individuals. This, in turn, initiated the development of several methods to infer interactions among moving animals. However, the performance of these methods has not been studied systematically, especially with regard to the factors that are highly relevant for field ecologists, such as duration of the tracking period, its temporal resolution and the proportion of the tracked community. Here, we assessed the performance of three dynamic interaction indices (Coefficient of sociality, Correlation coefficient and Dynamic interaction) and two novel approaches based on step selection functions (SSF‐occurrence‐distribution and SSF‐distance). We tested these methods on the data simulated with a predator–prey system, reflecting three common types of interactions while on the move: avoidance (prey individuals fleeing from the predator), attraction (predator following and chasing prey) and neutral movement (no interactions between predator and prey). We assessed the ability of each method to correctly detect the modelled interaction type by manipulating the perceptual range of the predator, the proportion of tracked prey individuals, the temporal resolution and the duration of the tracking period. We found that the ability to correctly infer interactions increased for all methods with an increase in the perceptual range of the predator and the proportion of tracked prey individuals. In contrast, the duration of the tracking period affected the methods' performance differently: some methods (Cs and SSF‐distance) were insensitive to it, whereas the performance of other methods improved (DI and SSF‐occurrence‐distribution) and worsened (Cr) with the duration of the tracking period. The three dynamic interaction indices and SSF‐distance were rather robust to changes in data resolution. Despite using the predator–prey system as our study case, our findings are applicable to other systems in which two animals on move may interact. We formulate guidelines for field ecologists studying animal movement to select the most suitable method depending on the availability of tracking devices, the duration and resolution of the tracking they can afford, as well as perceptual ranges of study species.

Keywords

• attraction‐avoidance
• biased correlated random walk
• dynamic interactions
• interactions
• movement ecology
• simulation