scholarly journals Understanding Effects of Whale-Watching Vessel Noise on Humpback Whale Song in the North Pacific Coast of Colombia With Propagation Models of Masking and Acoustic Data Observations

2021 ◽  
Vol 8 ◽  
Author(s):  
Maria Paula Rey-Baquero ◽  
Laura Valentina Huertas-Amaya ◽  
Kerri D. Seger ◽  
Natalia Botero-Acosta ◽  
Andrea Luna-Acosta ◽  
...  
Keyword(s):  
Marine Mammals ◽  
Large Scale ◽  
Humpback Whale ◽  
Propagation Model ◽  
Anthropogenic Noise ◽  
Whale Watching ◽  
Southern Limit ◽  
Acoustic Data ◽  
Communication Space ◽  
Vessel Noise

Soundscapes with minimal anthropogenic noise sources are key for the survival and effective communication of marine mammals. The Gulf of Tribugá is part of the breeding ground for humpback whale Stock G. Currently, no large-scale infrastructure exists on the Gulf's coastline, making it an area with high biodiversity and little anthropogenic noise. Whale-watching is one of the few human activities that contributes to the soundscape. By Morro Mico, on the southern limit of the Utría Natural National Park, an Ecological Acoustic Recorder (EAR, Oceanwide Science Institute) was deployed in the Gulf to record samples of acoustic activity from October to November 2018. It recorded for 10-min intervals with 20-min lapses for a duty cycle of 33.3%. One of the common peak frequencies of humpback whale song units from these recordings was used as input to an acoustic propagation model using the parabolic equation to simulate the communication space of a humpback whale when zero, one, and two boats are present. GPS positions of theodolite data from various whale watching scenarios in the Gulf were used to inform the models. Model results indicate that humpback whale song communication space could be reduced by as much as 63% in the presence of even one whale-watching boat. The boats traveling through the Gulf are the same as those used in whale-watching, and their engine noise while passing Morro Mico coincided with song structural and temporal changes observed in the acoustic data. Combining in situ data with acoustic models can advance the understanding of the spatio-temporal acoustic reactions of whales when their vocalizations are masked by boat noise. This project serves as an approximation of how humpback whale Stock G may respond to whale-watching vessel noise in the Gulf of Tribugá.

Vessel noise cuts down communication space for vocalizing fish and marine mammals

2017 ◽  
Vol 24 (4) ◽  
pp. 1708-1721 ◽  
Author(s):  
Rosalyn L. Putland ◽  
Nathan D. Merchant ◽  
Adrian Farcas ◽  
Craig A. Radford
Keyword(s):  
Marine Mammals ◽  
Communication Space ◽  
Vessel Noise

Recommendations for Sustainable Cetacean-Based Tourism in French Territories: A Review on the Industry and Current Management Actions

2020 ◽  
Vol 15 (3) ◽  
pp. 211-235
Author(s):  
Josephine Chazot ◽  
Ludovic Hoarau ◽  
Pamela Carzon ◽  
Jeanne Wagner ◽  
Stéphanie Sorby ◽  
...  
Keyword(s):  
Marine Mammal ◽  
Marine Mammals ◽  
French Polynesia ◽  
Legal Framework ◽  
Whale Watching ◽  
Cetacean Species ◽  
Commercial Activities ◽  
Management Actions ◽  
Overseas Territories ◽  
Socioeconomic Benefits

Whale-watching activities provide important socioeconomic benefits for local communities and constitute powerful platform incentives for marine mammals' protection or more broadly marine environments. However, these activities can cause adverse effects on targeted populations, with considerable downside associated risks of injuries and fatality for whale watchers during inwater interactions. France with its overseas territories has the second largest exclusive economic zone (EEZ), in which more than half of existing cetacean species are encountered. In these territories, recreational and commercial whale watching, including swim-with cetacean activities, have recently developed. Yet few studies focused on these activities and their associated impacts across French territories, leading to an unclear assessment of the situation. To address this issue, we reviewed cetaceans' occurrence within the French EEZ, whale-watching industry, targeted species, local management of marine mammal-based tourism activities, and regulations in France mainland and some overseas territories (Reunion Island, Mayotte, and French Polynesia). Fortyeight species are encountered in the French EEZ, and 15 are targeted by whale-watching activities. A total of 185 operators, including 34% offering swim-with-cetaceans tours, offered trips in France and overseas in 2019. While several more or less restrictive regulations exist locally, our results indicate that French's national legal framework for marine mammals' protection remains inadequate and insufficient to cope with the recent development of this activity. As conservation biologists, managers, and stakeholders from these French territories, we cooperated to provide general guidelines for a sustainable development of whale watching at a national scale. We urge (1) to legally acknowledge and regulate whale-watching commercial activities; (2) to create a national legal framework regarding whale watching and swim-with marine mammals practices, while accounting for local distinctiveness and disparities across regions; (3) to conduct more research to evaluate local short- and long-term impacts on targeted marine mammal populations as well as the socioeconomic benefits; and (4) to reinforce synergetic relations between the different stakeholders.

scholarly journals Predicting sample success for large‐scale ancient DNA studies on marine mammals

2021 ◽  
Author(s):  
Xénia Keighley ◽  
Maiken Hemme Bro‐Jørgensen ◽  
Hans Ahlgren ◽  
Paul Szpak ◽  
Marta Maria Ciucani ◽  
...  
Keyword(s):  
Ancient Dna ◽  
Marine Mammals ◽  
Large Scale

scholarly journals Combining Regional Habitat Selection Models for Large-Scale Prediction: Circumpolar Habitat Selection of Southern Ocean Humpback Whales

2021 ◽  
Vol 13 (11) ◽  
pp. 2074
Author(s):  
Ryan R. Reisinger ◽  
Ari S. Friedlaender ◽  
Alexandre N. Zerbini ◽  
Daniel M. Palacios ◽  
Virginia Andrews-Goff ◽  
...  
Keyword(s):  
Habitat Selection ◽  
Predictive Models ◽  
Regional Variation ◽  
Large Scale ◽  
Predictive Performance ◽  
Humpback Whale ◽  
Machine Learning Algorithms ◽  
Humpback Whales ◽  
Environmental Covariates ◽  
Animal Habitat

Machine learning algorithms are often used to model and predict animal habitat selection—the relationships between animal occurrences and habitat characteristics. For broadly distributed species, habitat selection often varies among populations and regions; thus, it would seem preferable to fit region- or population-specific models of habitat selection for more accurate inference and prediction, rather than fitting large-scale models using pooled data. However, where the aim is to make range-wide predictions, including areas for which there are no existing data or models of habitat selection, how can regional models best be combined? We propose that ensemble approaches commonly used to combine different algorithms for a single region can be reframed, treating regional habitat selection models as the candidate models. By doing so, we can incorporate regional variation when fitting predictive models of animal habitat selection across large ranges. We test this approach using satellite telemetry data from 168 humpback whales across five geographic regions in the Southern Ocean. Using random forests, we fitted a large-scale model relating humpback whale locations, versus background locations, to 10 environmental covariates, and made a circumpolar prediction of humpback whale habitat selection. We also fitted five regional models, the predictions of which we used as input features for four ensemble approaches: an unweighted ensemble, an ensemble weighted by environmental similarity in each cell, stacked generalization, and a hybrid approach wherein the environmental covariates and regional predictions were used as input features in a new model. We tested the predictive performance of these approaches on an independent validation dataset of humpback whale sightings and whaling catches. These multiregional ensemble approaches resulted in models with higher predictive performance than the circumpolar naive model. These approaches can be used to incorporate regional variation in animal habitat selection when fitting range-wide predictive models using machine learning algorithms. This can yield more accurate predictions across regions or populations of animals that may show variation in habitat selection.

scholarly journals Epimeletic behaviour in a Southern Resident Killer Whale (Orcinus orca)

2021 ◽  
Vol 134 (4) ◽  
pp. 316-320
Author(s):  
Taylor Shedd ◽  
Allison Northey ◽  
Shawn Larson
Keyword(s):  
Marine Mammals ◽  
Killer Whale ◽  
The United States ◽  
Small Population ◽  
Orcinus Orca ◽  
Salish Sea ◽  
The People ◽  
Species At Risk Act ◽  
Prey Scarcity ◽  
Vessel Noise

Southern Resident Killer Whale (SRKW, Orcinus orca) may be found year round in the Salish Sea. These orcas comprise three matrilineal pods (J, K, and L) and were listed as Endangered under the Canadian Species at Risk Act in 2003 and under the United States Endangered Species Act in 2005 because of prey scarcity, vessel noise and disturbance, small population size, and exposure to toxins. Since 1993, the Whale Museum has been operating Soundwatch, a boater education program for vessels. Soundwatch personnel are on the water in the central Salish Sea throughout the summer educating boaters on how to maneuver near marine mammals legally and documenting vessel regulation violations and marine mammal presence and behaviour. Starting on 24 July 2018, Soundwatch documented an adult female SRKW of J pod (J35) carrying a dead neonate calf. J35 continued to carry her dead calf for 17 consecutive days covering ~1600 km. Her story riveted the attention of the people of the Salish Sea as well as people around the world, evoking empathy for J35 and her loss as well as the plight of the Endangered SRKW population. Here, we tell her story and evaluate whether the behaviour J35 displayed toward her dead calf was an example of epimeletic behaviour, animal grief.

scholarly journals Body size information in large-scale acoustic bat databases

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5370 ◽  
Author(s):  
Caterina Penone ◽  
Christian Kerbiriou ◽  
Jean-François Julien ◽  
Julie Marmet ◽  
Isabelle Le Viol
Keyword(s):  
Body Size ◽  
Large Scale ◽  
Principal Component ◽  
Acoustic Signals ◽  
Species Traits ◽  
Climatic Variables ◽  
Characteristic Frequencies ◽  
Acoustic Data ◽  
Forearm Length ◽  
Broad Scale

Background Citizen monitoring programs using acoustic data have been useful for detecting population and community patterns. However, they have rarely been used to study broad scale patterns of species traits. We assessed the potential of acoustic data to detect broad scale patterns in body size. We compared geographical patterns in body size with acoustic signals in the bat species Pipistrellus pipistrellus. Given the correlation between body size and acoustic characteristics, we expected to see similar results when analyzing the relationships of body size and acoustic signals with climatic variables. Methods We assessed body size using forearm length measurements of 1,359 bats, captured by mist nets in France. For acoustic analyses, we used an extensive dataset collected through the French citizen bat survey. We isolated each bat echolocation call (n = 4,783) and performed automatic measures of signals, including the frequency of the flattest part of the calls (characteristic frequency). We then examined the relationship between forearm length, characteristic frequencies, and two components resulting from principal component analysis for geographic (latitude, longitude) and climatic variables. Results Forearm length was positively correlated with higher precipitation, lower seasonality, and lower temperatures. Lower characteristic frequencies (i.e., larger body size) were mostly related to lower temperatures and northern latitudes. While conducted on different datasets, the two analyses provided congruent results. Discussion Acoustic data from citizen science programs can thus be useful for the detection of large-scale patterns in body size. This first analysis offers a new perspective for the use of large acoustic databases to explore biological patterns and to address both theoretical and applied questions.

scholarly journals The Large Scale Machine Learning in an Artificial Society: Prediction of the Ebola Outbreak in Beijing

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Peng Zhang ◽  
Bin Chen ◽  
Liang Ma ◽  
Zhen Li ◽  
Zhichao Song ◽  
...  
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Ebola Virus ◽  
Virus Disease ◽  
Propagation Model ◽  
Propagation Mechanism ◽  
Chinese Government ◽  
Emergency Plans ◽  
Artificial Society ◽  
The City

Ebola virus disease (EVD) distinguishes its feature as high infectivity and mortality. Thus, it is urgent for governments to draw up emergency plans against Ebola. However, it is hard to predict the possible epidemic situations in practice. Luckily, in recent years, computational experiments based on artificial society appeared, providing a new approach to study the propagation of EVD and analyze the corresponding interventions. Therefore, the rationality of artificial society is the key to the accuracy and reliability of experiment results. Individuals’ behaviors along with travel mode directly affect the propagation among individuals. Firstly, artificial Beijing is reconstructed based on geodemographics and machine learning is involved to optimize individuals’ behaviors. Meanwhile, Ebola course model and propagation model are built, according to the parameters in West Africa. Subsequently, propagation mechanism of EVD is analyzed, epidemic scenario is predicted, and corresponding interventions are presented. Finally, by simulating the emergency responses of Chinese government, the conclusion is finally drawn that Ebola is impossible to outbreak in large scale in the city of Beijing.

Shanghai West Railway Station’s Design Based on Communication Space and Ecological Integration

2014 ◽  
Vol 584-586 ◽  
pp. 439-442
Author(s):  
Lu Wan ◽  
Yu Chen Guo ◽  
Yuan Yi Wei
Keyword(s):  
Functional Connectivity ◽  
Large Scale ◽  
Current Situation ◽  
Service Area ◽  
Low Density ◽  
Logistics Industry ◽  
Communication Space ◽  
Logistics Enterprises ◽  
Hotel Service ◽  
The City

This paper provided an overview that the city should be designed from the functional, connectivity, accessibility and other aspects of the city considering the current situation of obsolete facility and out of order around the Shanghai West Railway Station. It emphasized that the resources of Shanghai West Railway Station’s Zhenru area shall be integrated while the Zhenru center of Shanghai in Caoyang-street and the railway cargo terminal should be built. It proposed that the city should put emphasize on the development of modern logistics industry along with the construction of business office area, large-scale logistics enterprises gather, hotel service area and low density of cultural facilities.

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