Stuck in a corner: Anthropogenic noise threatens narwhals in their once pristine Arctic habitat

Experimental noise and light pollution alter prey detection in a nocturnal bird of prey

Urban expansion has led to ever increasing noise and light pollution, which impairs the audio-visual perception of wild animals and drives changes in key activities and behaviours. Nocturnal predators may be especially affected in detecting prey, with potentially dramatic consequences for their fitness. However, the combined effects of noise and light pollution on predator performance are still mostly unstudied. We experimentally exposed tawny owls (Strix aluco), nocturnal acoustic raptors, to traffic noise and artificial light. We provided both visual and acoustic prey cues to assess potential non-additive effects among multiple sensory stressors on the ability to detect prey. We found that, in control conditions, owls responded equally to both acoustic and visual prey cues. In contrast, noise and light individually decreased owls' ability to locate acoustic, but not visual, prey cues. When owls were exposed to noise and light combined also visual detection worsened, but not beyond the additive expectation. Conversely, the presence of light seemingly buffered the negative impact of noise on acoustic detection, suggesting an antagonistic interaction. Our findings show that both anthropogenic noise and light affect the hunting behaviour of a nocturnal avian predator, but with a stronger effect on acoustic than visual detection, suggesting that the magnitude of their disruptive impact might depend on the type of prey cue. This implies that sensory pollution might lead to increased reliance on sight-oriented hunting strategies. Importantly, our study shows that the co-occurrence of noise and light can have complex and unexpected impacts on behaviour, underscoring the importance of examining sensory pollution in a multimodal context.

Putting the health in hidden Markov models: incorporating allostatic load indices into movement ecology analyses

Individual animal health assessments are a key consideration for conservation initiatives. Environmental shifts associated with climate change, such as documented rises in pathogen emergence, predation pressures and human activities, create an increasingly stressful world for many species and have been linked with marked changes in movement behaviour. Even in healthy individuals, variations in allostatic load, the cumulative effects of long-term stress, may alter behavioural priorities over time. Here, we aimed to build links between animal health assessment information and movement ecology, using narwhals in the Canadian Arctic as a case study. A composite stress index was developed to incorporate multiple available health (e.g. health assessments), stress (e.g. hormones) and body condition metrics from clinically healthy individuals, and applied within the framework of widely used hidden Markov modelling of animal movement data. Individuals with a higher composite stress index tended to prioritize behaviours indicative of a stress response, including increasing the probability of transitioning to transiting behaviour as compared to those with a lower stress index. By incorporating a composite stress index that synthesizes multiple health indices in a flexible framework, we highlight that including information indicative of allostatic load may be important in explaining variation in behaviour, even for seemingly healthy animals. The modelling framework presented here highlights a flexible approach to incorporate health assessment information and provides an approach that is widely applicable to existing and future work on a range of species.

Shipping traffic through the Arctic Ocean: Spatial distribution, seasonal variation, and its dependence on the sea ice extent

The reduction in sea ice cover with Arctic warming facilitates shipping through remarkably shorter shipping routes. Automatic identification system (AIS) is a powerful data source to monitor Arctic Ocean shipping. Based on the AIS data from an online platform, we quantified the spatial distribution of shipping through this area, its intensity, and the seasonal variation. Shipping was heterogeneously distributed with power-law exponents that depended on the vessel category. We contextualized the estimated exponents with the analytical distribution of a transit model in one and two dimensions. Fishing vessels had the largest spatial spread, while narrower shipping routes associated with cargo and tanker vessels had a width correlated with the sea ice area. The time evolution of these routes showed extended periods of shipping activity through the year. We used AIS data to quantify recent Arctic shipping, which brings an opportunity for shorter routes, but likely impacting the Arctic ecosystem.

Accurate species classification of Arctic toothed whale echolocation clicks using one-third octave ratios

Passive acoustic monitoring has been an effective tool to study cetaceans in remote regions of the Arctic. Here, we advance methods to acoustically identify the only two Arctic toothed whales, the beluga (Delphinapterus leucas) and narwhal (Monodon monoceros), using echolocation clicks. Long-term acoustic recordings collected from moorings in Northwest Greenland were analyzed. Beluga and narwhal echolocation signals were distinguishable using spectrograms where beluga clicks had most energy >30 kHz and narwhal clicks had a sharp lower frequency limit near 20 kHz. Changes in one-third octave levels (TOL) between two pairs of one-third octave bands were compared from over one million click spectra. Narwhal clicks had a steep increase between the 16 and 25 kHz TOL bands that was absent in beluga click spectra. Conversely, beluga clicks had a steep increase between the 25 and 40 kHz TOL bands that was absent in narwhal click spectra. Random Forest classification models built using the 16 to 25 kHz and 25 to 40 kHz TOL ratios accurately predicted the species identity of 100% of acoustic events. Our findings support the use of echolocation TOL ratios in future automated click classifiers for acoustic monitoring of Arctic toothed whales and potentially for other odontocete species.