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Sammanfattning

Underwater acoustic telemetry positioning is widely used to track the fine-scale movements of aquatic animals. In study areas near acoustically reflective surfaces, reflected transmissions may cause large detection outliers that can severely reduce the accuracy of positioning models. A novel time-of-arrival model for telemetry positioning is presented that utilizes a population Monte Carlo algorithm to solve positions (termed PMC-TOA). Telemetry detection error is modelled as a mixture distribution, allowing reflected detections to be identified and positions to be estimated despite their presence. Importantly, the PMC-TOA model provides good measures of positioning uncertainty, facilitating the use of post-processing state-space models to further refine position estimates. A simulated telemetry study is used to validate the PMC-TOA model and compare its performance to a conventional time-difference-of-arrival positioning model. A real case study on Atlantic salmon (Salmo salar) smolt passage behaviour is further used to demonstrate how PMC-TOA can be combined with post-processing models to produce high-resolution tracks. The resulting tracks are compared against those resulting from YAPS and TDOA positioning. The PMC-TOA model was shown to work well as either (i) a pre-processing step to remove reflected transmissions from time-of-arrival datasets, or (ii) a fast and accurate positioning method when paired with a post-processing state-space model. Positions returned by the model can be further used for animal movement statistics, allowing researchers to test the effects of experimental or environmental factors on the fine-scaled movement behaviours of aquatic animals in acoustically challenging environments.

Nyckelord

acoustic telemetry; animal movement statistics; aquatic tracking; movement ecology; population Monte Carlo; telemetry tracking; time-of-arrival positioning

Publicerad i

Methods in Ecology and Evolution
2025, volym: 16, nummer: 4, sidor: 775-785
Utgivare: WILEY

SLU författare

UKÄ forskningsämne

Ekologi

Publikationens identifierare

  • DOI: https://doi.org/10.1111/2041-210X.14508

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/142728