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  • 2020-2023  (5)
  • 1
    Publication Date: 2022-02-18
    Description: Aquatic environments encompass the world’s most extensive habitats, rich with sounds produced by a diversity of animals. Passive acoustic monitoring (PAM) is an increasingly accessible remote sensing technology that uses hydrophones to listen to the underwater world and represents an unprecedented, non-invasive method to monitor underwater environments. This information can assist in the delineation of biologically important areas via detection of sound-producing species or characterization of ecosystem type and condition, inferred from the acoustic properties of the local soundscape. At a time when worldwide biodiversity is in significant decline and underwater soundscapes are being altered as a result of anthropogenic impacts, there is a need to document, quantify, and understand biotic sound sources–potentially before they disappear. A significant step toward these goals is the development of a web-based, open-access platform that provides: (1) a reference library of known and unknown biological sound sources (by integrating and expanding existing libraries around the world); (2) a data repository portal for annotated and unannotated audio recordings of single sources and of soundscapes; (3) a training platform for artificial intelligence algorithms for signal detection and classification; and (4) a citizen science-based application for public users. Although individually, these resources are often met on regional and taxa-specific scales, many are not sustained and, collectively, an enduring global database with an integrated platform has not been realized. We discuss the benefits such a program can provide, previous calls for global data-sharing and reference libraries, and the challenges that need to be overcome to bring together bio- and ecoacousticians, bioinformaticians, propagation experts, web engineers, and signal processing specialists (e.g., artificial intelligence) with the necessary support and funding to build a sustainable and scalable platform that could address the needs of all contributors and stakeholders into the future.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
    Location Call Number Limitation Availability
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  • 2
    Publication Date: 2022-01-04
    Description: Species distribution models (SDMs) relate species information to environmental conditions to predict potential species distributions. The majority of SDMs are static, relating species presence information to long-term average environmental conditions. The resulting temporal mismatch between species information and environmental conditions can increase model inference’s uncertainty. For SDMs to capture the dynamic species-environment relationships and predict near-real-time habitat suitability, species information needs to be spatiotemporally matched with environmental conditions contemporaneous to the species’ presence (dynamic SDMs). Implementing dynamic SDMs in the marine realm is highly challenging, particularly due to species and environmental data paucity and spatiotemporally biases. Here, we implemented presence-only dynamic SDMs for four migratory baleen whale species in the Southern Ocean (SO): Antarctic minke, Antarctic blue, fin, and humpback whales. Sightings were spatiotemporally matched with their respective daily environmental predictors. Background information was sampled daily to describe the dynamic environmental conditions in the highly dynamic SO. We corrected for spatial sampling bias by sampling background information respective to the seasonal research efforts. Independent model evaluation was performed on spatial and temporal cross-validation. We predicted the circumantarctic year-round habitat suitability of each species. Daily predictions were also summarized into bi-weekly and monthly habitat suitability. We identified important predictors and species suitability responses to environmental changes. Our results support the propitious use of dynamic SDMs to fill species information gaps and improve conservation planning strategies. Near-real-time predictions can be used for dynamic ocean management, e.g., to examine the overlap between habitat suitability and human activities. Nevertheless, the inevitable spatiotemporal biases in sighting data from the SO call for the need for improving sampling effort in the SO and using alternative data sources (e.g., passive acoustic monitoring) in future SDMs. We further discuss challenges of calibrating dynamic SDMs on baleen whale species in the SO, with a particular focus on spatiotemporal sampling bias issues and how background information should be sampled in presence-only dynamic SDMs. We also highlight the need to integrate visual and acoustic data in future SDMs on baleen whales for better coverage of environmental conditions suitable for the species and avoid constraints of using either data type alone.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
    Format: application/pdf
    Format: application/pdf
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  • 3
    Publication Date: 2022-11-08
    Description: 〈jats:p〉Bowhead whales (〈jats:italic〉Balaena mysticetus〈/jats:italic〉) of the East Greenland-Svalbard-Barents Sea (Spitsbergen) population are still considered endangered, but knowledge on spatio-temporal distribution patterns and behavioral aspects remains scarce, yet crucial for this population’s conservation. Long-term passive acoustic recordings were collected at five locations in central and eastern Fram Strait (78-79°N, 0-7°E) as part of the Ocean Observing System FRAM (Frontiers in Arctic Marine Monitoring). Data recorded in 2012 and 2016/2017 were analyzed for the acoustic occurrence of bowhead whales at hourly resolution using a combination of automated and manual analyses. Bowhead whales were acoustically present from autumn throughout the winter months (October-February) and occasionally in spring (March-June), supporting hypotheses that Fram Strait is an important overwintering area. Acoustic presence peaked between mid-November and mid-December with bowhead whale calls recorded almost daily, often hourly for several consecutive days. The observed peak in acoustic presence coincided with the presumed mating period of bowhead whales, starting in late winter, indicating that Fram Strait may also serve as a mating area. Detailed analyses of recordings of a single year and location revealed eight distinct bowhead whale song types, comprising simple songs and call sequences. No bowhead whales were recorded in summer (July-September), indicating that they had migrated to summering areas or resided outside the detection range. Compared to previous studies in western Fram Strait, bowhead whale detections in our recordings were less frequent and recorded songs were less complex. The observed regional differences in bowhead whale acoustic behavior across Fram Strait suggest that eastern Fram Strait may represent a less favorable part of the bowhead whale overwintering area.〈/jats:p〉
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
    Format: application/pdf
    Location Call Number Limitation Availability
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  • 4
  • 5
    Publication Date: 2022-06-09
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Parsons, M., Lin, T.-H., Mooney, T., Erbe, C., Juanes, F., Lammers, M., Li, S., Linke, S., Looby, A., Nedelec, S., Van Opzeeland, I., Radford, C., Rice, A., Sayigh, L., Stanley, J., Urban, E., & Di Iorio, L. Sounding the call for a global library of underwater biological sounds. Frontiers in Ecology and Evolution, 10, (2022): 810156, https://doi.org/10.3389/fevo.2022.810156.
    Description: Aquatic environments encompass the world’s most extensive habitats, rich with sounds produced by a diversity of animals. Passive acoustic monitoring (PAM) is an increasingly accessible remote sensing technology that uses hydrophones to listen to the underwater world and represents an unprecedented, non-invasive method to monitor underwater environments. This information can assist in the delineation of biologically important areas via detection of sound-producing species or characterization of ecosystem type and condition, inferred from the acoustic properties of the local soundscape. At a time when worldwide biodiversity is in significant decline and underwater soundscapes are being altered as a result of anthropogenic impacts, there is a need to document, quantify, and understand biotic sound sources–potentially before they disappear. A significant step toward these goals is the development of a web-based, open-access platform that provides: (1) a reference library of known and unknown biological sound sources (by integrating and expanding existing libraries around the world); (2) a data repository portal for annotated and unannotated audio recordings of single sources and of soundscapes; (3) a training platform for artificial intelligence algorithms for signal detection and classification; and (4) a citizen science-based application for public users. Although individually, these resources are often met on regional and taxa-specific scales, many are not sustained and, collectively, an enduring global database with an integrated platform has not been realized. We discuss the benefits such a program can provide, previous calls for global data-sharing and reference libraries, and the challenges that need to be overcome to bring together bio- and ecoacousticians, bioinformaticians, propagation experts, web engineers, and signal processing specialists (e.g., artificial intelligence) with the necessary support and funding to build a sustainable and scalable platform that could address the needs of all contributors and stakeholders into the future.
    Description: Support for the initial author group to meet, discuss, and build consensus on the issues within this manuscript was provided by the Scientific Committee on Oceanic Research, Monmouth University Urban Coast Institute, and Rockefeller Program for the Human Environment. The U.S. National Science Foundation supported the publication of this article through Grant OCE-1840868 to the Scientific Committee on Oceanic Research.
    Keywords: soundscape ; bioacoustics database ; artificial intelligence ; biodiversity ; passive acoustic monitoring ; ecological informatics
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Location Call Number Limitation Availability
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