Abstract: The practice of equipping free-living animals with data loggers to study their behavior in-situ dates back to the 1930s. Since then, remarkable advances in sensor miniaturization, power efficiency, data storage, and wireless communication have transformed the field. They are widely used in ecology and conservation to collect detailed information on animal movements, behavior, physiology, and the environments they inhabit. Despite these advances, scaling biologging studies remain constrained by data recovery in remote regions lacking cellular infrastructure. Researchers typically face a trade-off between two imperfect approaches: lower-cost archival tags suitable for short-term deployments (days to weeks), which require labor-intensive manual retrieval, and satellite tags designed for long-term deployments (months), which enable remote data transmission but remain prohibitively expensive for large sample sizes. In this seminar, I present two systems that I developed to address these limitations. Each system targets one side of this trade-off and aims to facilitate larger-scale, cost-effective deployments. First, I introduce ALERT (Automatic LoRa-Enabled Radio Tracker), a custom-built radiotelemetry system incorporating Long Range Wide Area Network (LoRaWAN) communication. ALERT automates the recovery of traditional archival biologgers by continuously scanning for non-coded VHF signals, detecting tagged individuals using an adaptable algorithm, and wirelessly transmitting presence data to a central gateway for real-time monitoring. The system was fieldtested at Atka Bay, Antarctica, from November 2024 to January 2025, where it successfully alerted researchers in real time to the return of emperor penguins (Aptenodytes forsteri) equipped with archival loggers and VHF transmitters, thereby facilitating efficient tag recovery. Second, I present a low-cost, mesh-capable IoT tag that I developed as an alternative to long-term satellite telemetry. Designed for multi-month deployments on central-place foragers such as emperor penguins, the system records GPS data locally and relies on LoRa-based peer-to-peer communication to exchange data opportunistically when tagged individuals encounter one another. As animals return to their colony during breeding, incubation, and chick-rearing phases, accumulated data is automatically offloaded to a central gateway via LoRaWAN. In this part of the seminar, I present the conceptual framework, agent-based modeling used to assess feasibility, the design and prototyping of the first tag version, and initial validation tests conducted on a surrogate species, highlighting the potential of a cooperative telemetry network to enable scalable, cost-effective long-term biologging in remote environments. By integrating mechanical design, the latest IoT technologies, and ecological insight, this work advances biologging toward low-cost, scalable solutions tailored for remote and logistically challenging environments. By removing key logistical and financial constraints, these approaches enable larger-scale data collection and provide a stronger empirical foundation for understanding and conserving remote ecosystems.

Abstract: Oceanography is an inherently interdisciplinary field, with many interconnected processes of varying spatiotemporal scales contributing to a dynamic ocean environment. Underwater acoustics is a valuable tool for studying these oceanographic processes, as environmental variability greatly influences acoustic propagation and scattering. The work in this dissertation follows an interdisciplinary approach to explore the multifaceted connections between acoustics and different branches of oceanography. An autonomous underwater vehicle (AUV) was used to study physical, biological, and geological oceanography and their joint acoustic effects as part of the New England Shelf Break Acoustics (NESBA) experiment. The AUV, a modified REMUS 600 equipped with an onboard 2.5-4.5 kHz transducer and towed hydrophone array, was deployed among a network of oceanographic and transceiver moorings. Acoustic signals transmitted and received throughout this network were used to analyze the physical links between environmental variability and acoustic propagation and scattering effects. These contributions further highlight the versatile role of AUVs in advancing ocean acoustic research.

In this work, the AUV was first localized using an acoustics-based multi-channel backpropagation approach, as accurate localization of the vehicle is crucial for contextualizing the AUV data. This process involved back-propagating acoustic wavefronts between the AUV source and mooring hydrophones, as well as signals transmitted from a ship-towed source to the AUV array. Analyses on physical oceanographic uncertainty and mooring tilt were performed to further improve the localization result and understand the influence of environmental uncertainty. Next, the same AUV acoustic dataset was used to explore mid-frequency 3D bathymetric reflection and scattering at a submarine landslide. Computational acoustic modeling, including ray tracing and parabolic equation models, were used to recreate the complex seafloor-interacting acoustic arrival patterns observed in the data, with the final data-model comparison showing evidence of 3D out-of-plane acoustic reflection and scattering. Finally, mid-frequency biological attenuation of a mesopelagic deep scattering layer (DSL) was investigated. A swimbladdered-fish scattering model was used to estimate DSL biological attenuation, which was then applied to a comparison of two acoustic propagation paths traveling through and avoiding the layer, respectively. The final results emphasize the joint influence of biological scattering and physical oceanographic uncertainty on sound propagation.