Predator-prey interactions in marine ecosystems are dynamically structured by light, which is exemplified by diel vertical migrations of low-trophic level organisms. At high latitudes, the long winter nights provide foraging opportunities for marine predators targeting vertically migrating prey closer to the surface at night while minimizing energy expenditure, but there is limited documentation of such diel patterns under extreme light regimes. To address this knowledge gap, we recorded the diving behavior of 17 harbour porpoises just south of the Arctic circle in West Greenland, from summer to winter. Unlike classical diel vertical migration, the porpoises dove three times deeper at night and the frequency of deep dives (>100 m) increased tenfold as they entered the darkest months. The daily mean depth was negatively correlated with daylength, confirming this reverse diel migration and suggesting an increased activity—presumably to target prey at greater depths—when approaching the polar night. Our findings illustrate a light-mediated strategy in which harbour porpoises would maximize energy gain during long periods of darkness while minimizing energy expenditure by accessing vertically migrating prey, which are otherwise inaccessible in deep waters. Extreme light regimes observed at high latitudes are therefore critical in structuring pelagic communities and food webs.

(a) Animal instrumentation

Between 2012 and 2014, 17 harbour porpoises were live-captured on the continental shelf approximately 50 km south-west of Maniitsoq, West Greenland (Fig. 1). Following Nielsen’s et al.’s procedure19, the individuals were instrumented with two types of satellite transmitters (SPLASH and MK10, Wildlife Computers, Redmond, WA, USA). Details on the tagging procedure and tag’s specifications can be found in Nielsen et al. (2019). The study was performed with permission from the Government of Greenland, permit no. 2012-069733, Doc. 1265044.

(b) Identification of diel patterns

All analyses were conducted using R software version 4.3.0 [39]. To investigate diel patterns in the diving behavior, sunlight phases (times of sunrise, dusk, day, dawn and sunset) were extracted at each individual’s location using the suncalc package [40] in R . For the five tags that were retrieved, no coordinates were stored in the tags. Satellite-relayed Argos coordinates (from the low-resolution datasets) were therefore matched to the high-resolution data based on the closest date and time for each individual. Diving behavior variables (mean dive depth, maximum dive depth, median dive depth and dive duration) were then compared between the different phases (dawn, day, dusk and night). During midnight sun in summer, dawn and dusk are not always identifiable due to rapid sunsets and sunrises during long periods of daylight. For this reason, diurnal and nocturnal dives were instead compared by merging dawn, dusk and night into the same “nighttime” category. Times of sunrise and sunset were then used to derive the daylength for each tracking day and each individual.

To map the day-night regimes in relation to the porpoises’ locations in West Greenland, solar elevation was extracted individually at each location and for the corresponding date. Based on the solar elevation angle (i.e., position of the sun in relation to the horizon), three phases were identified: day (solar elevation >0°), twilight (between 0 and -18°) and night (<0°). 

(c) Investigation of the relationship between daylength and dive depth

A series of Generalized Additive Models (GAM) were performed to relate the daylength to the daily dive depth or the harbour porpoises using the mgcv package. Dives were defined as deeper than 5 m and longer than 20 sec. Three separate models were tested using three diving behavior metrics summarized daily: mean, median and maximum depth. The short tracking duration of four individuals precluded the identification of seasonal patterns and they were therefore excluded from this analysis. Pairwise correlation between all covariates were first investigated (SI Fig. 1). To account for the inter-individual variability, individual’s ID was added as a random factor on both the slope and the intercept. Individual response curves were then generated for each harbor porpoise. The residuals were then inspected using diagnostic plots for each model.