A Methodological Framework to Estimate the Site Fidelity of Tagged Animals Using Passive Acoustic Telemetry

Abstract

The rapid expansion of the use of passive acoustic telemetry technologies has facilitated unprecedented opportunities for studying the behavior of marine organisms in their natural environment. This technological advance would greatly benefit from the parallel development of dedicated methodologies accounting for the variety of timescales involved in the remote detection of tagged animals related to instrumental, environmental and behavioral events. In this paper we propose a methodological framework for estimating the site fidelity (“residence times”) of acoustic tagged animals at different timescales, based on the survival analysis of continuous residence times recorded at multiple receivers. Our approach is validated through modeling and applied on two distinct datasets obtained from a small coastal pelagic species (bigeye scad, Selar crumenophthalmus) and a large, offshore pelagic species (yellowfin tuna, Thunnus albacares), which show very distinct spatial scales of behavior. The methodological framework proposed herein allows estimating the most appropriate temporal scale for processing passive acoustic telemetry data depending on the scientific question of interest. Our method provides residence times free of the bias inherent to environmental and instrumental noise that can be used to study the small scale behavior of acoustic tagged animals. At larger timescales, it can effectively identify residence times that encompass the diel behavioral excursions of fish out of the acoustic detection range. This study provides a systematic framework for the analysis of passive acoustic telemetry data that can be employed for the comparative study of different species and study sites. The same methodology can be used each time discrete records of animal detections of any nature are employed for estimating the site fidelity of an animal at different timescales.

Population assessment of tropical tuna based on their associative behavior around floating objects

“…We could demonstrate that for values of the model parameters inferred from field data, the accuracy of the association index is very high, already for a reduced numbers of residence times. Collecting field data of this kind is challenging: the number of fish that can be tagged is bounded by the high costs of the electronic tags and the issues of acoustic collisions that occur when too many individuals are tagged4554. Our study demonstrates that such limits do not constitute a major issue for population assessments of tropical tuna.…”

“…We considered a system of N fish individuals in an array of p FADs434445. A fish can be in one of the two following states: it can either be associated with one of the FADs, or be unassociated, i.e., occupy a portion of the sea outside of the zone of influence of any FAD.…”

“…refs 45, 46, 47). By exploiting the methods of survival analysis, the model parameters in equation (2) can be inferred from the survival curves of CRTs and CATs4546.…”

“…refs 45, 46, 47). By exploiting the methods of survival analysis, the model parameters in equation (2) can be inferred from the survival curves of CRTs and CATs4546. The association dynamics defined in equation (2), where the probabilities μ i and θ i are two time-independent constants, implies a memoryless process with an exponential distribution of CRTs and CATs45.…”

“…The hypothesis of time-independence in the association and departure probabilities (see equation (2)) was tested by fitting the survival curves of both CRTs and CATs with three models: exponential, double exponential and power law, using the nls function50. The first two models correspond to a memoryless, time-independent dynamics whereas the latter implies time-dependent probabilities to depart from and/or reach a FAD4546, see Appendix 2 in the Supplementary material for more details. Goodness of fits was compared through the Akaike information criterion (AIC)51.…”