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Abstract There is growing interest in floating offshore wind turbine (FOWT) technology, where turbines are installed on floating structures anchored to the seabed, allowing wind energy development in areas unsuitable for traditional fixed-platform turbines. Responsible development requires monitoring the impact of FOWTs on marine wildlife, such as whales, throughout the operational lifecycle of the turbines. Distributed acoustic sensing (DAS)—a technology that transforms fiber-optic cables into vibration sensor arrays—has been demonstrated for acoustic monitoring of whales using seafloor telecommunications cables. However, no studies have yet evaluated DAS performance in dynamic, engineered environments, such as floating platforms or moving vessels with complex, dynamic strain loads, despite their relevance to FOWT settings. This study addresses that gap by deploying DAS aboard a boat in Monterey Bay, California, where a fiber-optic cable was lowered using a weighted and suspended mooring line, enabling vertical deployment. Humpback whale vocalizations were captured and identified in the DAS data, noise sources were identified, and DAS data were compared to audio captured by a standalone hydrophone attached to the mooring line and a nearby hydrophone on a cabled observatory. This study is unique in: (1) deploying DAS in a vertical deployment mode, where noise from turbulence, cable vibrations, and other sources posed additional challenges compared to seafloor DAS applications; (2) demonstrating DAS in a dynamic, nonstationary setup, which is uncommon for DAS interrogators typically used in more stable environments; and (3) leveraging looped sections of the cable to reduce the noise floor and mitigate the effects of excessive cable vibrations and strain. This research demonstrates DAS’s ability to capture whale vocalizations in challenging environments, highlighting its potential to enhance underwater acoustic monitoring, particularly in the context of renewable energy development in offshore environments. 

Abstract BackgroundIn ecosystems influenced by strong seasonal variation in insolation, the fitness of diverse taxa depends on seasonal movements to track resources along latitudinal or elevational gradients. Deep pelagic ecosystems, where sunlight is extremely limited, represent Earth’s largest habitable space and yet ecosystem phenology and effective animal movement strategies in these systems are little understood. Sperm whales (Physeter macrocephalus) provide a valuable acoustic window into this world: the echolocation clicks they produce while foraging in the deep sea are the loudest known biological sounds on Earth and convey detailed information about their behavior. MethodsWe analyze seven years of continuous passive acoustic observations from the Central California Current System, using automated methods to identify both presence and demographic information from sperm whale echolocation clicks. By integrating empirical results with individual-level movement simulations, we test hypotheses about the movement strategies underlying sperm whales’ long-distance movements in the Northeast Pacific. ResultsWe detect foraging sperm whales of all demographic groups year-round in the Central California Current System, but also identify significant seasonality in frequency of presence. Among several previously hypothesized movement strategies for this population, empirical acoustic observations most closely match simulated results from a population undertaking a “seasonal resource-tracking migration”, in which individuals move to track moderate seasonal-latitudinal variation in resource availability. DiscussionOur findings provide evidence for seasonal movements in this cryptic top predator of the deep sea. We posit that these seasonal movements are likely driven by tracking of deep-sea resources, based on several lines of evidence: (1) seasonal-latitudinal patterns in foraging sperm whale detection across the Northeast Pacific; (2) lack of demographic variation in seasonality of presence; and (3) the match between simulations of seasonal resource-tracking migration and empirical results. We show that sperm whales likely track oceanographic seasonality in a manner similar to many surface ocean predators, but with dampened seasonal-latitudinal movement patterns. These findings shed light on the drivers of sperm whales’ long-distance movements and the shrouded phenology of the deep-sea ecosystems in which they forage. 

Among tremendous biodiversity within the California Current Ecosystem (CCE) are gigantic mysticetes (baleen whales) that produce structured sequences of sound described as song. From six years of passive acoustic monitoring within the central CCE we measured seasonal and interannual variations in the occurrence of blue (Balaenoptera musculus), fin (Balaenoptera physalus), and humpback (Megaptera novaeangliae) whale song. Song detection during 11 months of the year defines its prevalence in this foraging habitat and its potential use in behavioral ecology research. Large interannual changes in song occurrence within and between species motivates examination of causality. Humpback whales uniquely exhibited continuous interannual increases, rising from 34% to 76% of days over six years, and we examine multiple hypotheses to explain this exceptional trend. Potential influences of physical factors on detectability – including masking and acoustic propagation – were not supported by analysis of wind data or modeling of acoustic transmission loss. Potential influences of changes in local population abundance, site fidelity, or migration timing were supported for two of the interannual increases in song detection, based on extensive local photo ID data (17,356 IDs of 2,407 individuals). Potential influences of changes in foraging ecology and efficiency were supported across all years by analyses of the abundance and composition of forage species. Following detrimental food web impacts of a major marine heatwave that peaked during the first year of the study, foraging conditions consistently improved for humpback whales in the context of their exceptional prey-switching capacity. Stable isotope data from humpback and blue whale biopsy samples are consistent with observed interannual variations in the regional abundance and composition of forage species. This study thus indicates that major interannual changes in detection of baleen whale song may reflect underlying variations in forage species availability driven by energetic variations in ecosystem state. 

The random forest can reduce the variance of regression predictors through bagging while leaving the bias mostly unchanged. In general, the bias is not negligible and consequently bias correction is necessary. The default bias correction method implemented in the R package randomForest often works poorly. Several approaches have been developed which in general outperform the R default. However, little work has been done to com- prehensively evaluate the performance of these methods and thus guide users to select an appropriate method for bias correction. This paper fills this gap by providing an informa- tive ranking of these bias correction methods based on an extensive numerical study. We further offered practical suggestions on the application of the winner of these methods and suggested a visualization technique to help users decide when bias correction is needed. Journal of Statistical Research 2022, Vol. 56, No. 2, pp. 115-131 

Background: Large-scale memorial development has become a growing trend around the world. While numerous studies have tracked the effects of such development on objective measures of community welfare, far less is known about the social effects of memorial tourist attractions on communities where they are placed. This study explores one such impact: how do changes in the social and physical landscape as a result of memorial tourist development affect residents’ perceptions of the crime rate in their community? Methods: Secondary crime data was coupled with a longitudinal residential survey (n=135), measuring actual and perceived crime rates before and after the attraction’s opening. Results: While race, income, and political party affiliation predicted pre-opening beliefs, post-opening perceptions of crime change were associated with prior beliefs, residential status, media consumption, and median income. When compared against the objective crime change, residential status was the only predictor of inaccurate perceptions of both property and violent crime. Conclusions: Aspects of residents’ immediate communities bias their ability to accurately perceive crime change after the opening of a public memorial. The findings encourage researchers to take a more holistic, and yet nuanced, look at the effects of tourism on communities where they are placed. In the present case, such perceptions may have a significant impact on whether or not the objectives of the memorial developers are met. Given the current wave of memorial development worldwide, these findings may contribute to the success or failure of these efforts. 

Phytoplankton communities residing in the open ocean, the largest habitat on Earth, play a key role in global primary production. Through their influence on nutrient supply to the euphotic zone, open-ocean eddies impact the magnitude of primary production and its spatial and temporal distributions. It is important to gain a deeper understanding of the microbial ecology of marine ecosystems under the influence of eddy physics with the aid of advanced technologies. In March and April 2018, we deployed autonomous underwater and surface vehicles in a cyclonic eddy in the North Pacific Subtropical Gyre to investigate the variability of the microbial community in the deep chlorophyll maximum (DCM) layer. One long-range autonomous underwater vehicle (LRAUV) carrying a third-generation Environmental Sample Processor (3G-ESP) autonomously tracked and sampled the DCM layer for four days without surfacing. The sampling LRAUV’s vertical position in the DCM layer was maintained by locking onto the isotherm corresponding to the chlorophyll peak. The vehicle ran on tight circles while drifting with the eddy current. This mode of operation enabled a quasi-Lagrangian time series focused on sampling the temporal variation of the DCM population. A companion LRAUV surveyed a cylindrical volume around the sampling LRAUV to monitor spatial and temporal variation in contextual water column properties. The simultaneous sampling and mapping enabled observation of DCM microbial community in its natural frame of reference. 

The urgency for remote, reliable and scalable biodiversity monitoring amidst mounting human pressures on ecosystems has sparked worldwide interest in Passive Acoustic Monitoring (PAM), which can track life underwater and on land. However, we lack a unified methodology to report this sampling effort and a comprehensive overview of PAM coverage to gauge its potential as a global research and monitoring tool. To address this gap, we created the Worldwide Soundscapes project, a collaborative network and growing database comprising metadata from 416 datasets across all realms (terrestrial, marine, freshwater and subterranean). 

The deep chlorophyll maximum (DCM) layer is an ecologically important feature of the open ocean. The DCM cannot be observed using aerial or satellite remote sensing; thus, in situ observations are essential. Further, understanding the responses of microbes to the environmental processes driving their metabolism and interactions requires observing in a reference frame that moves with a plankton population drifting in ocean currents, i.e., Lagrangian. Here, we report the development and application of a system of coordinated robots for studying planktonic biological communities drifting within the ocean. The presented Lagrangian system uses three coordinated autonomous robotic platforms. The focal platform consists of an autonomous underwater vehicle (AUV) fitted with a robotic water sampler. This platform localizes and drifts within a DCM community, periodically acquiring samples while continuously monitoring the local environment. The second platform is an AUV equipped with environmental sensing and acoustic tracking capabilities. This platform characterizes environmental conditions by tracking the focal platform and vertically profiling in its vicinity. The third platform is an autonomous surface vehicle equipped with satellite communications and subsea acoustic tracking capabilities. While also acoustically tracking the focal platform, this vehicle serves as a communication relay that connects the subsea robot to human operators, thereby providing situational awareness and enabling intervention if needed. Deployed in the North Pacific Ocean within the core of a cyclonic eddy, this coordinated system autonomously captured fundamental characteristics of the in situ DCM microbial community in a manner not possible previously.