Distribution patterns of blue whale (Balaenoptera musculus) and shipping off southern Sri Lanka

Priyadarshana, Tilak; Randage, Sameera Madusanka; Alling, A.; Calderan, Susannah; Gordon, Jonathan; Leaper, Russell; Porter, Lindsay

doi:10.1016/j.rsma.2015.08.002

Cited by 31 publications

(47 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, the major shipping route linking the Arabian Sea and Europe goes through the Gulf of Aden before entering the Red Sea and Suez Canal. Shipping traffic is also high off southwestern India and Priyadarshana et al (2016) found consistently high densities of blue whales off Sri Lanka in one of the world's busiest shipping routes.…”

Section: Discussionmentioning

confidence: 99%

Predicting cetacean distributions in data‐poor marine ecosystems

Redfern

Moore

Fiedler

et al. 2017

Diversity and Distributions

View full text Add to dashboard Cite

Aim Human activities are creating conservation challenges for cetaceans. Spatially explicit risk assessments can be used to address these challenges, but require species distribution data, which are limited for many cetacean species. This study explores methods to overcome this limitation. Blue whales (Balaenoptera musculus) are used as a case study because they are an example of a species that have well-defined habitat and are subject to anthropogenic threats.Location Eastern Pacific Ocean, including the California Current (CC) and eastern tropical Pacific (ETP), and northern Indian Ocean (NIO).Methods We used 12 years of survey data (377 blue whale sightings and c. 225,400 km of effort) collected in the CC and ETP to assess the transferability of blue whale habitat models. We used the models built with CC and ETP data to create predictions of blue whale distributions in the data-poor NIO because key aspects of blue whale ecology are expected to be similar in these ecosystems. Results We found that the ecosystem-specific blue whale models performed well in their respective ecosystems, but were not transferable. For example, models built with CC data could accurately predict distributions in the CC, but could not accurately predict distributions in the ETP. However, the accuracy of models built with combined CC and ETP data was similar to the accuracy of the ecosystem-specific models in both ecosystems. Our predictions of blue whale habitat in the NIO from the models built with combined CC and ETP data compare favourably to hypotheses about NIO blue whale distributions, provide new insights into blue whale habitat, and can be used to prioritize research and monitoring efforts.Main conclusions Predicting cetacean distributions in data-poor ecosystems using habitat models built with data from multiple ecosystems is potentially a powerful marine conservation tool and should be examined for other species and regions.

show abstract

Section: Discussionmentioning

confidence: 99%

Predicting cetacean distributions in data‐poor marine ecosystems

Redfern

Moore

Fiedler

et al. 2017

Diversity and Distributions

View full text Add to dashboard Cite

show abstract

“…Similarly, research on whale populations in the waters off Sri Lanka suggests that shifting current shipping lanes 15 nautical miles south of their existing location would reduce blue whale ( Balaenoptera musculus ) ship strike interactions by 95% (Priyadarshana et al . ). In areas undergoing rapid environmental change, such as polar regions, the IMO is working with the International Whaling Commission and the Arctic Council, an intergovernmental forum, to implement mitigation strategies aimed at reducing the risk of ship strikes and shipping noise disturbances (Arctic Council ).…”

Section: Mitigation Of Marine Road Consequences For Whalesmentioning

confidence: 97%

“…In addition, specifically for North Atlantic right whales, a US regulation known as the "Ship Strike Rule" defined Seasonal Management Areas, which are intended as a means to reduce vessel collisions, as well as Dynamic Management Areas, which help to minimize whale mortality by accounting for the species' interannual distribution (van der Hoop et al 2015). Similarly, research on whale populations in the waters off Sri Lanka suggests that shifting current shipping lanes 15 nautical miles south of their existing location would reduce blue whale (Balaenoptera musculus) ship strike interactions by 95% (Priyadarshana et al 2015). In areas undergoing rapid environmental change, such as polar regions, the IMO is working with the International Whaling Commission and the Arctic Council, an intergovernmental forum, to implement mitigation strategies aimed at reducing the risk of ship strikes and shipping noise disturbances (Arctic Council 2015).…”

Section: Mitigation Within the Marine Roadmentioning

confidence: 99%

Consequences of global shipping traffic for marine giants

Pirotta

Grech

Jonsen

et al. 2018

Frontiers in Ecol & Environ

105

View full text Add to dashboard Cite

Shipping routes in the ocean are analogous to terrestrial roads, in that they are regularly used thoroughfares that concentrate the movement of vessels between multiple locations. We applied a terrestrial road ecology framework to examine the ecological impacts of increased global shipping on “marine giants” (ie great whales, basking sharks [Cetorhinus maximus], and whale sharks [Rhincodon typus]). This framework aided in identifying where such “marine roads” and marine giants are likely to interact and the consequences of those interactions. We also reviewed known impacts of shipping routes on these species, and then applied the road ecology framework to detect unknown and potentially threatening processes. In the marine environment, such a framework can be used to incorporate knowledge of existing shipping impacts into management practices, thereby reducing the detrimental effects of future expansion of shipping routes on marine giants.

show abstract

“…Expanding on this concept, other groups (Dransfield et al 2014;Jensen et al 2015) have looked specifically at traffic lanes (considering their usage rates via AIS), comparing the lanes with habitats to determine whether conservation might be better served by modifications to the traffic lanes. Marine mammal sighting data have also been used for comparison with AIS, where available, in place of generalized habitat information (Chion et al 2012;Guzman et al 2013;Lagueux et al 2011;Priyadarshana et al 2016). Spatial risk assessment treatments of AIS vessel traffic data with respect to marine mammal strikes have been computed along two general themes.…”

Section: Ais and Strike Riskmentioning

confidence: 99%

Past, present, and future of the satellite-based automatic identification system: areas of applications (2004–2016)

Fournier

Hilliard²,

Rezaee

et al. 2018

WMU J Marit Affairs

View full text Add to dashboard Cite

In 2016, the world shipping fleet grew by 3.5%. Even if the annual growth rate remains at its lowest since 2013, the global situation is still in overcapacity (UNCTAD 2016). Ninety percent of global trade, by volume, is done by sea. Monitoring this fleet helps with vessel navigation, informing to help avoid critical situations such as collisions, accidents leading to oil pollution, grounding, or ships in distress, but also because traffic management in congested areas is essential. For system wide management, in regions such as MPAs (marine protected areas), conservation is the key factor, and movements can be monitored and analyzed in order to determine illegal or suspicious activities, or in order to limit and/or divert traffic, to mitigate the risks to species subject to protection. It is among these efforts that the automatic identification system (AIS) can play a key role. Since 2004, this VHF transceiver-based reporting system, imposed by the International Maritime Organization (IMO), has shifted from a traditional vessel identification device to a tool used in a wide variety of applications. The most common uses are safety and security; these issues are quite visible in the media and may touch more people on a global scale (e.g., piracy, oil spills). Over the years, AIS has become, especially with the emergence of the satellite-based capture of the signal in 2011, a widely used tool for developing applications such as fisheries monitoring, marine conservation, air pollution forecasting and modeling, ballast water monitoring, invasive species transport, and many more. In this paper, we propose to review the peerreviewed publications related to the uses and applications of the AIS.

show abstract

Distribution patterns of blue whale (Balaenoptera musculus) and shipping off southern Sri Lanka

Cited by 31 publications

References 22 publications

Predicting cetacean distributions in data‐poor marine ecosystems

Predicting cetacean distributions in data‐poor marine ecosystems

Consequences of global shipping traffic for marine giants

Past, present, and future of the satellite-based automatic identification system: areas of applications (2004–2016)

Contact Info

Product

Resources

About