environmental-dna-sampling-from-whale-watching-vessels-for-cetacean

Environmental DNA Sampling from Whale-Watching Vessels for Cetacean Monitoring

Environmental DNA (eDNA) offers a non-invasive approach for monitoring cetaceans, yet its widespread application from operational platforms requires ...

University of Iceland's Húsavík Research Center, Húsavík, Iceland

Biodiversity in the oceans has dramatically declined since the beginning of the industrial era, with accelerated loss of marine biodiversity impairing the ocean's capacity to maintain vital ecosystem services. A few organisms epitomize the damaging and long-lasting effects of anthropogenic exploitation: Some whale species, for instance, were brought to the brink of extinction, with their population sizes reduced to such low levels that may have caused a significant disruption to their reproductive dynamics and facilitated hybridization events. The incidence of hybridization is nevertheless believed to be rare, and very little information exists on its directionality. Here, using genetic markers, we show that all but one whale hybrid sample collected in Icelandic waters originated from the successful mating of male fin whale and female blue whale, thus suggesting unidirectional hybridization. We also demonstrate for the first time the existence of a second-generation adult (male) hybrid resulting from a backcross between a female hybrid and a pure male fin whale. The incidence of hybridization events between fin and blue whales is likely underestimated and the observed unidirectional hybridization (for F1 and F2 hybrids) is likely to induce a reproductive loss in blue whale, which may represent an additional challenge to its recovery in the Atlantic Ocean compared to other rorquals.

Evidence of unidirectional hybridization and second-generation adult hybrid between the two largest animals on Earth, the fin and blue whales.

Male harbor seals (Phoca vitulina) produce stereotypic underwater roars during the mating season. It remains unclear to what extent roar structures vary due to predation levels. Here, seal roars from waters with many (Iceland) and few (Denmark and Sweden) predators were compared. Most Icelandic roars included a long pulse train and a pause. Icelandic roars occurred less frequently, lasted longer (20.3 ± 6.5 s), and were recorded with lower received sound levels (98.3 ± 8.9 dB re 1 μPa root mean square) than roars from Denmark and Sweden. Local extrinsic factors may shape sound production in harbor seals more than previously reported.

Are Icelandic harbor seals acoustically cryptic to avoid predation?

Governments are increasingly monitoring meso- and microplastic (M/MP) pollution in surface waters to develop cost-effective solutions. While citizen science is widely used in programs like the EU's Marine Litter Watch and NOAA's sampling in the U.S., these efforts primarily focus on macro litter, leaving gaps in M/MP data, especially in under-sampled regions like Icelandic waters. This study addresses this gap through a citizen science initiative (2019-2023) that monitored M/MP pollution in the "Northeast Iceland Hope Spot." Fifty-eight trawl samples were collected from whale-watching and expedition vessels using a low-tech aquatic debris instrument (LADI) or a high-speed AVANI trawl. M/MP were present in 86 % of samples, with an average density of 0.02 ± 0.03 particles/m. Concentrations varied significantly between sites (p = 0.005), peaking in Grímsey (0.070 ± 0.03 particles/m), followed by Eyjafjörður (0.006 ± 0.04 particles/m) and Skjálfandi Bay (0.004 ± 0.03 particles/m). Mesoplastics comprised 44 % and microplastics 56 %, primarily polyethylene (47 %) and polypropylene (39 %)-common materials in fishing gear and household plastics. These findings suggest that local currents and fishing activities influence M/MP distribution. Comparison with previous studies validates the use of the presented citizen science methods for tracking floating M/MP in coastal waters and highlights their value in shaping marine conservation policies, particularly in vulnerable subarctic ecosystems.

Validating citizen science for community-driven microplastic monitoring and marine protection in Northeast Iceland's Hope Spot.

In this study, we compared the established MaxEnt and a more novel deep learning approach for modeling the distribution of humpback whales () in north Iceland. We examined the mechanisms, structures, and optimization techniques of both approaches, highlighting their differences and similarities. Monthly distribution models for Skjálfandi Bay were created, from 2018 until 2021, using presence-only sighting data and satellite remote sensing data. Search efforts and boat tracklines were utilized to create pseudo-absence points for both models. Additionally, the trained models were used to create distribution projections for the year 2022, solely based on the available environmental data. We compared the results using the established area under the curve value. The findings indicate that both approaches have their limitations and advantages. MaxEnt does not allow continuous updating within a time series, yet it mitigates the risk of overfitting by employing the maximum entropy principle. The deep learning model is more likely to overfit, but the larger weight network increases the model's capability to capture complex relationships and patterns. Ultimately, the results show that the deep learning model had a higher predictive performance in modeling both current and future humpback whale distributions. Both modeling approaches have inherent limitations, such as the low resolution of the input data, spatial biases, and the inability to fully capture the entire complexity of natural processes. Despite this, deep learning showed promising results in modeling the distribution of humpback whales and prompts further research in different study areas and applications for other mobile animal species.

Comparative Analysis of MaxEnt and Deep Learning Approaches for Modeling Humpback Whale Distribution in North Iceland.

Latitudinal gradient can influence ecosystem dynamics and species distribution, yet the influence on some aspects, such as intra-species diversity, is less well understood. The large-scale distribution of harbour porpoises () in the Northeast Atlantic, indicates that ecological adaptations within the species might be greater than currently recognised. This study investigates variation in foraging behaviour using long-term passive acoustic monitoring data collected between 2009 and 2023 from Iceland, Sweden, Ireland, and France. In each area, Generalised Additive Models (GAMs) were used to investigate the influence of large-scale environmental variables (water temperature, salinity, primary production, diel phase and daylength) on foraging behaviour. Our results show variability and complexity in foraging and differences in temporal patterns between areas. In the northernmost regions, with the largest variation in daylight, foraging behaviour was related to diel phase, with primarily nocturnal foraging recorded during the year, but with predominantly diurnal foraging in Iceland during late fall. In the southernmost regions, less effect of diel phase on foraging was found. Harbour porpoises in Sweden and Iceland exhibited increased day-round foraging during calving periods, highlighting the role of reproductive energetics in behavioural adaptations, and the complexity and importance of foraging during different seasons. Our findings underscore the influence of environmental drivers in shaping foraging strategies, supporting the concept that harbour porpoises optimise these based on local conditions and prey availability. Using long-term datasets, spanning broad geographical and temporal scales, this study contributes to the wider ecological understanding of animals with extensive latitudinal distributions, highlighting intra-species variance and the need for region-specific conservation and management.

Large-Scale Passive Acoustic Monitoring Data Shows Seasonal and Diel Diversity in Foraging Behaviour of Harbour Porpoises Within Their Distributional Range in the Northeast Atlantic.

Article	Year
Evidence of unidirectional hybridization and second-generation adult hybrid between the two largest animals on Earth, the fin and blue whales. Evolutionary applications\| PubMed ID: 33664778	2021
Are Icelandic harbor seals acoustically cryptic to avoid predation? JASA express letters\| PubMed ID: 36154560	2021
Validating citizen science for community-driven microplastic monitoring and marine protection in Northeast Iceland's Hope Spot. Marine pollution bulletin\| PubMed ID: 39938198	2025
Comparative Analysis of MaxEnt and Deep Learning Approaches for Modeling Humpback Whale Distribution in North Iceland. Ecology and evolution\| PubMed ID: 40109551	2025
Large-Scale Passive Acoustic Monitoring Data Shows Seasonal and Diel Diversity in Foraging Behaviour of Harbour Porpoises Within Their Distributional Range in the Northeast Atlantic. Ecology and evolution\| PubMed ID: 41328419	2025

Marianne H. Rasmussen

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