Consequences of global shipping traffic for marine giants

Abstract

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.

Tracking the global reduction of marine traffic during the COVID-19 pandemic

“…In particular, the behaviour of human activities in the ocean have been radically altered by the COVID-19 pandemic, with port restrictions and changes in consumption patterns impacting multiple maritime sectors, most notably fisheries, passenger ferries and cruise ships [7][8][9][10] ; sectors which rely heavily on the movement of people and goods. As with previous economic recessions 11,12 , changes in vessel movement associated with COVID-19 are also likely to result in significant short-and long-term effects on multiple anthropogenic pressures, such air pollution [12][13][14][15] , the spread of invasive alien species 16,17 , or collisions with marine animals 18,19 .…”

Animal-Borne Telemetry: An Integral Component of the Ocean Observing Toolkit

“…Advances made using such approaches are generating new insights about animal movements and their drivers (Rodríguez et al, 2017). The real-time nature of marine animal telemetry can also be used to inform real-time management actions, such as interventions with ship traffic to avoid collisions between marine animals and vessels, and warning beach goers of risk of shark presence (Hazen et al, 2017;Pirotta et al, 2019). This requires real-time integration and analyses of massive amounts of data, something only possible with the assistance of machine learning tools.…”

Assessing the importance of Isle of Man waters for the basking shark Cetorhinus maximus

“…Of concern to basking sharks and the potential for strike risk and disturbance are the threats associated with maritime passages, such as shipping lanes. The risk of vessel strike has been well documented for cetaceans (Van Waerebeek et al 2007, Berman-Kowalewski et al 2010, Tricas & Gill 2011, Halvorsen et al 2012 but not yet quantified for basking sharks (for an overview, see Pirotta et al 2019; for examples of dorsal fin damage from supposed vessel collisions, see Sims et al 2000b, Hall et al 2013. Results of the present study could be used to mitigate threat by identifying areas of high-risk activities and subsequent areas of co-occurrence, allowing decision makers to place sensible management measures on developments (e.g.…”

“…Results of the present study could be used to mitigate threat by identifying areas of high-risk activities and subsequent areas of co-occurrence, allowing decision makers to place sensible management measures on developments (e.g. time-of-day speed restrictions) or im pose speed restrictions or re-route maritime passages (Pirotta et al 2019). To ensure effective protection of basking sharks in IoM waters, seasonal speed restrictions (Speedie et al 2009) or re-routing vessel traffic to avoid basking shark hotspots could be considered (Irvine et al 2014).…”

“…In addition, survey drones could provide a new perspective on basking shark aggregations, which may be linked to breeding (Crowe et al 2018). Additionally, assessing basking shark ship-strike risk could be achieved by comparing animal location data and marine traffic data to identify potential high-risk zones (Hazen et al 2017) and impose adaptive management strategies such as seasonal management areas (Pirotta et al 2019).…”