Lauren McWhinnie

A growing and increasingly globalised human population, requiring the movement of goods and commodities, is placing increasing demands on the maritime industry, resulting in a concurrent increase in global shipping activities. This has consequences for the marine environment, particularly for species vulnerable to the impacts of vessel traffic. For example, vessel collisions can result in sub‐lethal or fatal injuries for marine mammals, whilst vessel noise can cause acoustic masking that effectively reduces an animal's listening space, potentially impacting their communication, navigation and foraging capacity. While a number of parallel approaches to mapping collision risk to large whales have arisen, these methods vary in their focus, usually on either co‐occurrence, collision probability, or probability of mortality. However, little attention has been given to the implications of methodological choice and data selection on subsequent risk predictions. To assess differences between these approaches, we used a standardised input dataset comprised of telemetry‐point data from tagged bowhead whales, and satellite‐based Automated Identification System (AIS) data of spatial vessel movements covering the Davis‐Baffin Arctic Marine Area. We applied this data to eight different, previously published analyses for deriving areas of vessel risk. We found that the choice of risk mapping approach affected the location, and total area, identified as ‘high risk’, and that more computationally complex approaches did not necessarily equate to different predictions. There was considerable variation in the total area of ‘high risk’ predicted within each map (range = 20–42,246 km²). Synthesis and Applications. The results underscore the importance of methodological transparency, informed data selection and careful interpretation when predicting collision risk. We provide practical recommendations for enhancing transparency when predicting risk, and discuss choice of approach suitable for different situations or management applications. It is critical that managers and policy makers are aware of the implications of applying different approaches when interpreting risk evaluation outputs.

The rapid emergence of new marine developments (e.g., marine renewables, port infrastructure) alongside the substantial growth of existing industries has ultimately resulted in an unprecedented increase in anthropogenic structures within the marine environment over the previous century. Knowledge of whether marine species interact with, avoid, or accommodate and adapt to such structures is essential to ensure that further development of marine environments do not compromise conservation objectives of marine species. This article documents one such interaction. Herein, we describe the observation of a harbour seal (Phoca vitulina) seeking refuge from a group of foraging killer whales (Orcinus orca) within a blue (aka common) mussel (Mytilus edulis) farm. Aerial video footage (38 min 27 s) was collected using an unmanned aerial system during an encounter at an aquaculture site in Gulberwick Bay, Shetland, UK. Analysis of the footage showed the killer whale group spent 73.7% of the total encounter time exhibiting predatory associated behaviours and that they were observed interacting with the mussel farm infrastructure only during “predation activity” for a total of 26 min 52 s (72.8%). The harbour seal interacted with the mussel farm infrastructure during re- and proactive anti-predator behaviour and when exhibiting fatigue for 27 min 59 s, 94.4% of the total time the seal was observed. It is clear that both marine and terrestrial predator–prey interactions are increasingly occurring in settings that are in some way defined by the Anthropocene. The implications of this are discussed, including potential entanglement risk and human-altered “landscapes of fear.” As comprehension of the potential effects of human-altered risk grows, such knowledge should be taken into consideration prior to further modification of marine habitats.