Conservation of A-to-I RNA editing in bowhead whale and pig

RNA editing is a post-transcriptional process in which nucleotide changes are introduced into an RNA sequence, many of which can contribute to proteomic sequence variation. The most common type of RNA editing, contributing to nearly 99% of all editing events in RNA, is A-to-I (adenosine-to-inosine) editing mediated by double-stranded RNA-specific adenosine deaminase (ADAR) enzymes. A-to-I editing at ‘recoding’ sites results in non-synonymous substitutions in protein-coding sequences. Here, we present studies of the conservation of A-to-I editing in selected mRNAs between pigs, bowhead whales, humans and two shark species. All examined mRNAs–NEIL1, COG3, GRIA2, FLNA, FLNB, IGFBP7, AZIN1, BLCAP, GLI1, SON, HTR2C and ADAR2 –showed conservation of A-to-I editing of recoding sites. In addition, novel editing sites were identified in NEIL1 and GLI1 in bowhead whales. The A-to-I editing site of human NEIL1 in position 242 was conserved in the bowhead and porcine homologues. A novel editing site was discovered in Tyr244. Differential editing was detected at the two adenosines in the NEIL1 242 codon in both pig and bowhead NEIL1 mRNAs in various tissues and organs. No conservation of editing of KCNB1 and EEF1A mRNAs was seen in bowhead whales. In silico analyses revealed conservation of five adenosines in ADAR2, some of which are subject to A-to-I editing in bowheads and pigs, and conservation of a regulatory sequence in GRIA2 mRNA that is responsible for recognition of the ADAR editing enzyme.

Temporal Baseline of Essesntial and Non-essential Elements Recorded in Baleen of Western Arctic Bowhead Whale (Balaena mysticetus)

This study established the first baseline of changing elemental concentrations in bowhead whale baleen over time (1958–1999). From previously published stable isotope data, year, season (summer or winter), and location (Beaufort or Bering/Chukchi seas) were attributed to each sample. Thirteen elements (Al, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Se, V, Zn) in baleen from nine subsistence-harvested bowhead whales (n = 138) were detected. Al, Cu, and Fe were the highest concentrations while Cd and V were among the lowest. Our data supports absorption as the main route of exposure to environmental elements rather than biomagnification due to bowhead whales’ low trophic position. A linear mixed-effects model confirmed most elements’ concentrations increased with time, while location and sex were insignificant explanatory factors. These temporal fluctuations were most likely a product of environmental changes due to a warming climate and human activities.

A New Scoring System for use in Capture-Recapture Studies for Bowhead Whales Photographed with Drones

Effective management of animal populations requires knowledge of life history parameters and estimates of population abundance. One method commonly used to estimate abundance is capture/recapture analyses of photographs. Small, relatively inexpensive, rotary-wing drones have become an effective platform for obtaining high-quality aerial photographs of whales. To conduct capture/recapture analyses the animal needs to be defined as marked or unmarked and the photographs must be of high quality. While a system for scoring quality and markedness has previously been developed for bowhead whales (Balaena mysticetus) (Rugh et al. 1998), a revised scoring system was needed to incorporate increased information in photographs taken by drones. We present a revised scoring system that enlarges two of the previously defined areas of the whale examined for markings and incorporates smaller markings into the definition of marked whales. We scored 30 whales using the previous criteria and the revised criteria developed in this paper. More whales were identified as marked (23%) and mark scores were higher for 30% of the zones scored using the new system. Increasing the number of marked whales during capture/recapture studies increases the precision of estimated parameters and permits us to make those estimates with smaller samples of photographs.

Developing a Precautionary Management Approach for the Eastern Canada-West Greenland Population of Bowhead Whales (Balaena mysticetus)

Bowhead whales (Balaena mysticetus L., 1758) of the Eastern Canada-West Greenland population have been hunted by Inuit for millennia. Significant commercial harvests, conducted by European and American whalers for about 400 years, ended ca. 1915. A small co-managed subsistence harvest from this population has occurred inconsistently in Canada and Greenland, since 1996 and 2009, respectively. Since near extirpation from commercial whaling, population size has increased and the Inuit subsistence hunt now requires a harvest management framework that incorporates knowledge of abundance trends, population dynamics, and carrying capacity. Here, we use a model estimate of pre-commercial exploitation abundance to approximate carrying capacity and develop a management framework with reference points and corresponding stock status zones. When applied to recent abundance estimates, our framework indicates that the population is likely within the healthy (N50–N70) zone. Thus, an appropriate management objective is to support continued population increase, with concurrent marginal harvesting, while maintaining the population level above the target reference point (N70) of ca 12,000 whales. However, there remains large uncertainty about current population size and growth rate. The resulting data gaps require a plan for future research to monitor this population in the context of climate changes.

Bowhead and beluga whale acoustic detections in the western Beaufort Sea 2008–2018

The Distributed Biological Observatory (DBO) was established to detect environmental changes in the Pacific Arctic by regular monitoring of biophysical responses in each of 8 DBO regions. Here we examine the occurrence of bowhead and beluga whale vocalizations in the western Beaufort Sea acquired by acoustic instruments deployed from September 2008-July 2014 and September 2016-October 2018 to examine inter-annual variability of these Arctic endemic species in DBO Region 6. Acoustic data were collected on an oceanographic mooring deployed in the Beaufort shelfbreak jet at ~71.4°N, 152.0°W. Spectrograms of acoustic data files were visually examined for the presence or absence of known signals of bowhead and beluga whales. Weekly averages of whale occurrence were compared with outputs of zooplankton, temperature and sea ice from the BIOMAS model to determine if any of these variables influenced whale occurrence. In addition, the dates of acoustic whale passage in the spring and fall were compared to annual sea ice melt-out and freeze-up dates to examine changes in phenology. Neither bowhead nor beluga whale migration times changed significantly in spring, but bowhead whales migrated significantly later in fall from 2008–2018. There were no clear relationships between bowhead whales and the environmental variables, suggesting that the DBO 6 region is a migratory corridor, but not a feeding hotspot, for this species. Surprisingly, beluga whale acoustic presence was related to zooplankton biomass near the mooring, but this is unlikely to be a direct relationship: there are likely interactions of environmental drivers that result in higher occurrence of both modeled zooplankton and belugas in the DBO 6 region. The environmental triggers that drive the migratory phenology of the two Arctic endemic cetacean species likely extend from Bering Sea transport of heat, nutrients and plankton through the Chukchi and into the Beaufort Sea.

A comparison of three methods for estimating call densities of migrating bowhead whales using passive acoustic monitoring

Various methods for estimating animal density from visual data, including distance sampling (DS) and spatially explicit capture-recapture (SECR), have recently been adapted for estimating call density using passive acoustic monitoring (PAM) data, e.g., recordings of animal calls. Here we summarize three methods available for passive acoustic density estimation: plot sampling, DS, and SECR. The first two require distances from the sensors to calling animals (which are obtained by triangulating calls matched among sensors), but SECR only requires matching (not localizing) calls among sensors. We compare via simulation what biases can arise when assumptions underlying these methods are violated. We use insights gleaned from the simulation to compare the performance of the methods when applied to a case study: bowhead whale call data collected from arrays of directional acoustic sensors at five sites in the Beaufort Sea during the fall migration 2007–2014. Call detections were manually extracted from the recordings by human observers simultaneously scanning spectrograms of recordings from a given site. The large discrepancies between estimates derived using SECR and the other two methods were likely caused primarily by the manual detection procedure leading to non-independent detections among sensors, while errors in estimated distances between detected calls and sensors also contributed to the observed patterns. Our study is among the first to provide a direct comparison of the three methods applied to PAM data and highlights the importance that all assumptions of an analysis method need to be met for correct inference.

Reconciling Behavioural, Bioenergetic, and Oceanographic Views of Bowhead Whale Predation on Overwintering Copepods at an Arctic Hotspot (Disko Bay, Greenland)

Bowhead whales (Balaena mysticetus) visit Disko Bay, West Greenland in winter and early spring to feed on Calanus spp., at a time of year when the copepods are still mostly in diapause and concentrated in near-bottom patches. Combining past observations of copepod abundance and distribution with detailed observations of bowhead whale foraging behaviour from telemetry suggests that if the whales target the highest-density patches, they likely consume 26–75% of the Calanus standing stock annually. A parallel bioenergetic calculation further suggests that the whales' patch selection must be close to optimally efficient at finding hotspots of high density copepods near the sea floor in order for foraging in Disko Bay to be a net energetic gain. Annual Calanus consumption by bowhead whales is similar to median estimates of consumption by each of three zooplankton taxa (jellies, chaetognaths, and predatory copepods), and much greater than the median estimate of consumption by fish larvae, as derived from seasonal abundance and specific ingestion rates from the literature. The copepods' self-concentration during diapause, far from providing a refuge from predation, is the behaviour that makes this strong trophic link possible. Because the grazing impact of the whales comes 6–10 months later than the annual peak in primary production, and because Disko Bay sits at the end of rapid advective pathways (here delineated by a simple numerical particle-tracking experiment), it is likely that these Calanus populations act in part as a long-distance energetic bridge between the whales and primary production hundreds or thousands of km away.

Contribution to unravel variability in bowhead whale songs and better understand its ecological significance

Since the first studies on bowhead whale singing behaviour, song variations have been consistently reported. However, there has been little discussion regarding variability in bowhead whale singing display and its ecological significance. Unlike the better studied humpback whales, bowhead whales do not appear to share songs at population level, but several studies have reported song sharing within clusters of animals. Over the winter season 2013–2014, in an unstudied wintering ground off Northeast Greenland, 13 song groups sharing similar hierarchical structure and units were identified. Unit types were assessed through multidimensional maps, showing well separated clusters corresponding to manually labelled units, and revealing the presence of unit subtypes. Units presented contrasting levels of variability over their acoustic parameters, suggesting that bowhead whales keep consistency in some units while using a continuum in values of frequency, duration and modulation parameters for other unit types. Those findings emphasise the need to account for variability in song analysis to better understand the behavioural ecology of this endangered species. Additionally, shifting from song toward units or phrase-based analysis, as it has been suggested for humpback whales, offers the opportunity to identify and track similarities in songs over temporal and geographical scales relevant to population monitoring.