Zooplankton play critical roles in marine ecosystems, yet their fine-scale behavior remains poorly understood because of the difficulty in studying individuals in situ. Here, we combine biologging with supervised machine learning (ML) to propose a pipeline for studying in situ behavior of larger zooplankton such as jellyfish. We deployed the ITAG, a biologging package with high-resolution motion sensors designed for soft-bodied invertebrates, on eight Chrysaora fuscescens in Monterey Bay, using the tether method for retrieval. By analyzing simultaneous video footage of the tagged jellyfish, we developed ML methods to: (1) identify periods of tag data corrupted by the tether method, which may have compromised prior research findings, and (2) classify jellyfish behaviors. Our tools yield characterizations of fine-scale jellyfish activity and orientation over long durations, and we conclude that it is essential to develop behavioral classifiers on in situ rather than laboratory data.

Anthropogenic noise is now a prominent pollutant increasing in both terrestrial and marine environments. In the ocean, proliferating offshore windfarms, a key renewable energy source, are a prominent noise concern, as their pile driving construction is among the most intense anthropogenic sound sources. Yet, across taxa, there is little information of pile driving noise impacts on organismal fine-scale movement despite its key link to individual fitness. Here, we experimentally quantified the swimming behavior of an abundant squid species (Doryteuthis pealeii) of vital commercial and ecological importance in response to in situ pile driving activity on multiple temporal and spatial scales (thus exposed to differing received levels, or noise-doses). Pile driving induced energetically costly alarm-jetting behaviors in most (69%) individuals at received sound levels (in zero to peak) of 112-123 dB re 1 µm s-2, levels similar to those measured at the kilometer scale from some wind farm construction areas. No responses were found at a comparison site with lower received sound levels. Persistence of swimming pattern changes during noise-induced alarm responses, a key metric addressing energetic effects, lasted up to 14 s and were significantly shorter in duration than similar movement changes caused by natural conspecific interactions. Despite observing dramatic behavioral changes in response to initial pile driving noise, there was no evidence of gait changes over an experiment day. These results demonstrate that pile driving disrupts squid fine-scale movements, but impacts are short-lived suggesting that offshore windfarm construction may minimally impact the energetics of this ecologically key taxon. However, further work is needed to assess potential behavioral and physiological impacts at higher noise levels.

Some delphinids produce a learned, individually specific tonal whistle that conveys identity information to conspecifics . These whistles, termed signature whistles, were first described by Caldwell and Caldwell (1965) and have been studied intensively over the past several decades . In common bottlenose dolphins (Tursiops truncatus) and potentially other species, signature whistles facilitate many ecologically-important behaviors, including individual recognition and maintenance of group cohesion (Janik & Slater, 1998). Additionally, signature whistle contours, or patterns of frequency change over time, can remain stable for several decades, aiding in long-term social bonds (Sayigh et al., 1990). Signature whistles account for approximately 38%-70% of all whistle production in freeswimming animals (Buckstaff, 2004;Cook et al., 2004;Watwood et al., 2005); this percentage can be up to 100% for