A Case Study of a Near Vessel Strike of a Blue Whale: Perceptual Cues and Fine-Scale Aspects of Behavioral Avoidance

Szesciorka, Angela R.; Allen, Ann N.; Calambokidis, John; Fahlbusch, James A.; McKenna, Megan F.; Southall, Brandon L.

doi:10.3389/fmars.2019.00761

Cited by 6 publications

(4 citation statements)

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“…5 ). The ability of blue whales to avoid approaching vessels appears to be limited to relatively slow descents/ascents, with no horizontal movements away from a vessel 102 , 103 , therefore, collision events might pose significant threats to survival and recovery 97 for this endangered population. As inner waters of NCP might be considered, at the time, the spot of higher relative and absolute probabilities of negative interactions between blue whales and vessels, management actions are urgently needed to be implemented.…”

Section: Discussionmentioning

confidence: 99%

Defining priority areas for blue whale conservation and investigating overlap with vessel traffic in Chilean Patagonia, using a fast-fitting movement model

Bedriñana‐Romano

Hucke‐Gaete

Viddi

et al. 2021

Sci Rep

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Defining priority areas and risk evaluation is of utmost relevance for endangered species` conservation. For the blue whale (Balaenoptera musculus), we aim to assess environmental habitat selection drivers, priority areas for conservation and overlap with vessel traffic off northern Chilean Patagonia (NCP). For this, we implemented a single-step continuous-time correlated-random-walk model which accommodates observational error and movement parameters variation in relation to oceanographic variables. Spatially explicit predictions of whales’ behavioral responses were combined with density predictions from previous species distribution models (SDM) and vessel tracking data to estimate the relative probability of vessels encountering whales and identifying areas where interaction is likely to occur. These estimations were conducted independently for the aquaculture, transport, artisanal fishery, and industrial fishery fleets operating in NCP. Blue whale movement patterns strongly agreed with SDM results, reinforcing our knowledge regarding oceanographic habitat selection drivers. By combining movement and density modeling approaches we provide a stronger support for purported priority areas for blue whale conservation and how they overlap with the main vessel traffic corridor in the NCP. The aquaculture fleet was one order of magnitude larger than any other fleet, indicating it could play a decisive role in modulating potential negative vessel-whale interactions within NCP.

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Section: Discussionmentioning

confidence: 99%

Defining priority areas for blue whale conservation and investigating overlap with vessel traffic in Chilean Patagonia, using a fast-fitting movement model

Bedriñana‐Romano

Hucke‐Gaete

Viddi

et al. 2021

Sci Rep

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“…First, since using a linear relationship between avoidance response with increasing vessel speed resulted in very similar mortality results as a logistic relationship (Rockwood et al, 2017), we chose to limit our analysis to only the logistic formulation of avoidance. Though the speed-avoidance relationship remains poorly understood (Szesciorka et al, 2019), observations, and analysis have best supported the logistic formulation (Gende et al, 2011). In previous versions of this model (Rockwood et al, 2017), mean ship parameters were calculated across all vessels within a grid cell prior to running the mortality model.…”

Section: Model Frameworkmentioning

confidence: 99%

Modeling Whale Deaths From Vessel Strikes to Reduce the Risk of Fatality to Endangered Whales

et al. 2021

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Vessel strikes have been documented around the world and frequently figure as a top human cause of large whale mortality. The shipping lanes in the Santa Barbara Channel, California and nearby waters have some of the highest predicted whale mortality from vessel strikes in the United States waters of the eastern Pacific. Beginning in 2007, National Oceanographic and Atmospheric Administration requested voluntary vessel speed reductions (VSRs) for vessels greater than 300 GT traveling in the Santa Barbara Channel shipping routes to decrease whale mortality from ship strikes. We employed a ship strike model using whale density data and automatic identification system (AIS) vessel data to estimate mortality under several management scenarios. To assess the effect of the VSR on strike mortality, we bootstrapped speeds from vessels greater than 19 m long that transited when no VSR was in place. Finally, we calculated the predicted mortality for hypothetical cooperation scenarios by artificially adding speed caps post-hoc to real vessel transits. For 2012–2018, we estimated that in our study area on average during summer/fall (June–November) 8.9 blue, 4.6 humpback, and 9.7 fin whales were killed from ship strikes each year (13–26% greater than previously estimated). We evaluated winter/spring (January–April) humpback mortality for the first time, resulting in an estimate of 5.7 deaths on average per year. Poor cooperation with the VSR led to low (5% maximum) to no reductions in the estimated number of strike mortalities. Evaluating potential scenarios showed that if 95% cooperation occurred in the lanes, whale deaths there would decrease by 22–26%. Adding VSRs with similar cooperation levels at the northern end of the Santa Barbara Channel and south of Channel Islands National Marine Sanctuary could decrease estimated strike mortalities in those areas by 30%. If VSRs were added and cooperation reached 95% there and in the lanes, we estimate a 21–29% decrease in vessel strike mortalities could be attained relative to estimated mortality in the entire study area. To decrease the vessel strike related whale mortalities in this region, we recommend expanding the VSR areas and increasing cooperation voluntarily, or considering mandatory speed limits if desired cooperation levels cannot otherwise be met.

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“…Locations that were closer than 500 m to the vessel were also rejected because of the possibility of responsive movement. This distance was chosen based on qualitative observations during the voyages, on the analysis of Lesage et al (2017), who noted behavioural changes in blue whales in the St. Lawrence estuary Canada when vessels were within 400 m, and research by Szesciorka et al (2019) who reported a change in surfacing behaviour as a ship approached within 300m.…”

Section: Fine-scale Movement Within Track (Swim Speed and Heading)mentioning

confidence: 99%

Surfacing rates, swim speeds, and patterns of movement of Antarctic blue whales

et al. 2023

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During three surveys in the austral summers of 2013, 2015, 2019, data on Antarctic blue whale blow rates, dive times, swim speeds, and broadscale movements were collected using video photogrammetric tracking and intra-voyage photo-identification. A total of 24.4 hours of video observations were suitable for blow interval or movement analysis. Similar to other blue whale populations, Antarctic blue whale dive behaviour comprised a sequence of short dives followed by a long dive with a mean dive time for short dives of 17.6 s, and a mean long dive time of 189.3 s. Two separate methods were used to estimate the average blow rate for Antarctic blue whales, giving estimates of 59.7 and 63.2 blows per hour. The overall mean swim speed over the course of all suitable video track segments was 1.59 ms-1, but there were significant differences between years in the mean of the overall movement rate for each track; average movement rates were lower in 2015 compared to 2013 and 2019 (0.90 ms-1, 1.84 and 1.55 ms-1 respectively), with higher rates of turning in 2015. In 2019, there was faster overall movement through the study area in a consistent direction. The total number of photo-identified blue whales re-sighted intra-season in 2013 was nine (out of 50 identified individuals); in 2015 it was seven (out of 46); in 2019 two (out of 25). Whales remained for several days with little overall movement within the 2015 study area, whereas they were moving through the study area in 2019, which would explain the low number of intra-season resights. The predominant heading in 2019 was towards the area of Antarctic blue whale concentrations at the entrance to the Ross Sea observed in previous years. The photo-identification data also show a high proportion of resighted whales with coherent movements. This suggests that Antarctic blue whales might travel together, at least over periods of several days or sometimes up to a month. The differences between behaviours in 2015 and 2019 in particular may be related to differences in the characteristics of krill swarms between the study areas.

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A Case Study of a Near Vessel Strike of a Blue Whale: Perceptual Cues and Fine-Scale Aspects of Behavioral Avoidance

Abstract: Whale Uses Cues to Avoid Ship-Strike integration of these methods and technologies demonstrates the capacity for detailed behavioral studies of blue whales and other highly mobile marine megafauna, which will contribute to more informed evaluation and mitigation strategies.

Cited by 6 publications

References 50 publications

Defining priority areas for blue whale conservation and investigating overlap with vessel traffic in Chilean Patagonia, using a fast-fitting movement model

Defining priority areas for blue whale conservation and investigating overlap with vessel traffic in Chilean Patagonia, using a fast-fitting movement model

Modeling Whale Deaths From Vessel Strikes to Reduce the Risk of Fatality to Endangered Whales

Surfacing rates, swim speeds, and patterns of movement of Antarctic blue whales

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