Andreas Scheidegger

Big data analysis of animal movements in aquatic ecosystems with acoustic telemetry

The paper applies Bayesian inference to large acoustic telemetry datasets to improve movement pattern analysis and residency estimation in aquatic ecosystems.

Animal geolocation with convolution algorithms in Julia and R via Wahoo.jl

The paper introduces Wahoo.jl, a Julia package for animal geolocation using convolution algorithms, and demonstrates its application to tracking data from acoustic and depth tags.

Animal tracking with particle algorithms for conservation

This paper improves animal movement modeling using particle algorithms to enhance MPA design and conservation efforts for flapper skates.

patter: particle algorithms for animal tracking in R and Julia

The paper introduces the patter package for Bayesian state-space modeling of animal tracking data, demonstrating its use in reconstructing movement paths and analyzing space use.

Particle algorithms for animal movement modelling in autonomous receiver networks

This paper introduces a Bayesian filtering-smoothing algorithm for animal movement modelling in autonomous receiver networks, showing it outperforms heuristic methods in accuracy and flexibility.