Toward the Quantification of a Conceptual Framework for Movement Ecology Using Circular Statistical Modeling

Abstract

To analyze an animal’s movement trajectory, a basic model is required that satisfies the following conditions: the model must have an ecological basis and the parameters used in the model must have ecological interpretations, a broad range of movement patterns can be explained by that model, and equations and probability distributions in the model should be mathematically tractable. Random walk models used in previous studies do not necessarily satisfy these requirements, partly because movement trajectories are often more oriented or tortuous than expected from the models. By improving the modeling for turning angles, this study aims to propose a basic movement model. On the basis of the recently developed circular auto-regressive model, we introduced a new movement model and extended its applicability to capture the asymmetric effects of external factors such as wind. The model was applied to GPS trajectories of a seabird (Calonectris leucomelas) to demonstrate its applicability to various movement patterns and to explain how the model parameters are ecologically interpreted under a general conceptual framework for movement ecology. Although it is based on a simple extension of a generalized linear model to circular variables, the proposed model enables us to evaluate the effects of external factors on movement separately from the animal’s internal state. For example, maximum likelihood estimates and model selection suggested that in one homing flight section, the seabird intended to fly toward the island, but misjudged its navigation and was driven off-course by strong winds, while in the subsequent flight section, the seabird reset the focal direction, navigated the flight under strong wind conditions, and succeeded in approaching the island.

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“…with potential field approaches [34], [35], continuous time analysis [36], [37]) or further analytical account of the observed directional persistence due to support inclinations (e.g. [38]). …”

Crown asymmetry in high latitude forests: disentangling the directional effects of tree competition and solar radiation

“…Spatially explicit studies in forest ecology often assume isotropy and ignore orientations, despite the clearly directional nature of many ecological structures and processes (Abe et al ). Currently, circular statistics are widely applied in other ecological fields, such as in studies of animal behavior (Schick et al ), in which orientations often play a central role (Shimatani et al ). Although our analysis was limited to the influence of inter‐tree competition and directionality of solar radiation, and we pooled the three species in the dataset, we point out that the modeling approach presented here can be easily extended for studying species differences, as well as the influence of other abiotic variables.…”

Flight paths of seabirds soaring over the ocean surface enable measurement of fine-scale wind speed and direction

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