Estimated abundances of cetacean species in the Northeast Atlantic from Norwegian shipboard surveys conducted in 2014-2018

A ship-based mosaic survey of Northeast Atlantic cetaceans was conducted over a 5-year period between 2014–2018. The area surveyed extends from the North Sea in the south (southern boundary at 53oN), to the ice edge of the Barents Sea and the Greenland Sea. Survey vessels were equipped with 2 independent observer platforms that detected whales in passing mode and applied tracking procedures for the target species, common minke whales (Balaenoptera acutorostrata acutorostrata). Here we present abundance estimates for all non-target species for which there were sufficient sightings. We estimate the abundance of fin whales (Balaenoptera physalus) to be 11,387 (CV=0.17, 95% CI: 8,072–16,063), of humpback whales (Megaptera novaeangliae) to be 10,708 (CV=0.38, 95% CI: 4,906–23,370), of sperm whales (Physeter macrocephalus) to be 5,704 (CV=0.26, 95% CI: 3,374–9,643), of killer whales (Orcinus orca) to be 15,056 (CV=0.29, 95% CI: 8,423–26,914), of harbour porpoises (Phocoena phocoena) to be 255,929 (CV=0.20, 95% CI: 172,742–379,175), dolphins of genus Lagenorhynchus to be 192,767 (CV=0.25, 95% CI: 114,033–325,863), and finally of northern bottlenose whales (Hyperoodon ampullatus) to be 7,800 (CV=0.28, 95% CI: 4,373–13,913). Additionally, our survey effort in the Norwegian Sea in 2015 contributed to the 6th North Atlantic Sightings Survey (NASS) and the survey was extended into the waters north and east of Iceland around Jan Mayen island. This NASS extension, along with our Norwegian Sea survey in 2015, was used to estimate the abundance of fin whales, humpback whales, and sperm whales. All estimates presented used mark-recapture distance sampling techniques and were thus corrected for perception bias. Our estimates do not account for additional variance due to distributional shifts between years or biases due to availability or responsive movement.publishedVersio

Estimated abundances of cetacean species in the Northeast Atlantic from two multiyear surveys conducted by Norwegian vessels between 2002-2013

Two shipboard line-transect surveys of the Northeast Atlantic were conducted between 2002–2007 and 2008–2013 to meet the ongoing requirements of the Revised Management Procedure (RMP) for common minke whales (Balaenoptera acutorostrata acutorostrata) developed by the International Whaling Commission’s Scientific Committee. Here we present estimated abundances for non-target species for which there were sufficient sightings, including fin whales (Balaenoptera physalus), humpback whales (Megaptera novaeangliae), sperm whales (Physeter macrocephalus), killer whales (Orcinus orca), harbour porpoises (Phocoena phocoena), and dolphins of genus Lagenorhynchus. The 2 surveys were conducted using a multiyear mosaic survey design with 2 independent observer platforms operating in passing mode, each with 2 observers. The abundances of Lagenorhynchus spp. from the 2002–2007 survey were estimated using single-platform standard distance sampling methods because of uncertainty in identifying duplicate sightings. All other estimates were derived using mark-recapture distance sampling techniques applied to a combined-platform dataset of observations, correcting for perception bias. Most notably, we find that the abundance of humpback whales, similar in both survey periods, has doubled since the 1990s with the most striking changes occurring in the Barents Sea. We also show that the pattern in distribution and abundance of fin whales and sperm whales is consistent with our earlier surveys, and that abundances of small odontocete species, which were not estimated in earlier surveys, show stable distributions with some variation in their estimates. Our estimates do not account for distributional shifts between years or correct for biases due to availability or responsive movement.publishedVersio

A fluke encounter: first record of the blue whale (Balaenoptera musculus) within the central North Sea, United Kingdom

Despite holding the accolade as the largest animal ever to live on planet earth and ubiquitously inhabiting the world's major oceans, an acute paucity of information surrounds the geographical distribution and migration phenology of the endangered blue whale (Balaenoptera musculus) in the northeast Atlantic. Current migration and distribution information derived from robust scientific studies is required to ensure the formulation and implementation of successful conservation measures with a vision to support the ongoing recovery of the northeast Atlantic population. At 10:21 (UTC) on the 9th of November 2020, two blue whales were observed at position 55°13.99′N, 01°13.62′W, 18 km off the coast of the UK in the central North Sea just north of Newcastle at a water depth of 76 m. This is the first paper that has confirmed an account of live blue whales frequenting shallow waters of the central North Sea and represents a new area of occurrence within the accepted range of the northeast Atlantic population, an area in which sightings are extremely rare and may provide insight into the intricacies of migration routes and behaviour.publishedVersio

How does the extent of student-active learning in engineering programmes influence students’ perceived learning outcomes?

Through the project “Technology Education of the Future” (FTS), NTNU has developed a framework for re-design of its study programmes in technology and engineering. One of the main findings is the need for a broader, more multidimensional view of graduate competence, showcasing the need to fully integrate training of several important non-technical professional skills in future programmes. To enable such integration, student-active pedagogical methods in combination with integrated learning principles are often seen as key tools. This paper quantitatively investigates to what extent study programmes’ facilitation of active student participation actually makes a difference to perceived learning outcomes across a variety of competence areas. The research question under consideration is “How does the extent of student-active learning in engineering programmes influence students’ perceived learning outcomes?” Using statistical analysis of data from a national student survey, correlation was investigated between students’ perception of how well active student participation is facilitated by the teaching in their study programmes, and their self-evaluated learning outcomes in 10 different competence areas. Regression analysis was done based directly on individual student responses and on responses averaged over study programmes. The results show statistically significant positive correlation for most competence areas. Students’ perception of how well their programmes facilitate active student participation is found in good agreement with actual known programme characteristics. The results thus provide quantitative indication that improving facilitation of student-active learning in engineering programmes indeed improves learning outcomes for a broad set of future-relevant competence areas

Consideration of measurement errors for the Norwegian common minke whale (Balaenoptera acutorostrata acutorostrata) surveys

A discrete measurement error model for radial distance and angle to detected objects in line transect surveys is considered. This approach directly quantifies the effect of measurement error on the estimated effective strip half-width. We apply the method to experimental data collected over the period 2008-2013 in North Atlantic both under the assumption of multiplicative and additive measurement errors. Our results indicate that the abundance estimates considering the measurement error are consistently larger than the abundance estimates without any measurement error correction.publishedVersio

Holistic sustainability: advancing interdisciplinary building design through tools and data in Denmark

Sustainable housing and buildings constitute a fundamental part of the future urban fabric. This study aims at clarifying how different actors employ parameters of sustainability in building design and what enables the holistic perspective of the interrelating social, economic and environmental parameters. Interviews with building developers and designers show that decision support tools are used late in the design process and commonly focused on single parameters of sustainability. The analysis shows how practitioners of the planning and early design phases operate at general levels of geometrical clusters and volumes but must continuously evaluate each project from the perspective of the specifications of end-users and the public, to ensure holistic sustainability. This opposing relationship between need and availability of general and specific data, however, challenges the implementation of holistic sustainability. Advancing the interdisciplinary, holistic building design requires systematic aggregation of data from executed projects of this data into applicable rules-of-thumb. In parallel, future tools for simulation and dialogue must employ a broader scope of sustainability parameters. The conceptual frameworks of data and tools presented in this study can be used as a backdrop for developing sectora

Equipment to tag, track and collect biopsies from whales and dolphins : the ARTS, DFHorten and LKDart systems

Funding Information: A special thanks to all the members of the 3S team, and to FFI, for support during the development of the ARTS–DTAG setup. Furthermore, special acknowledgement to ICR (Institute of Cetacean Research, Japan) for the development of the new ARTS carrier (ARTSTBC).Of all animals considered subjects for instrumentation for behavioral or physiological studies, cetaceans probably represent the greatest challenge to the engineer and biologist. The marine environment being harsh to electronics, evasive behavior during tagging approaches and the short time window available to attach instruments, all imply a need for innovative tagging solutions to facilitate better understanding of their life cycle, migration, physiology, behavior, health and genetics. Several animal-attached tag packages holding specific data loggers, e.g., time depth recorders, position, orientation, acoustic and video recorders for short to medium term studies, as well as tags developed for large scale migration telemetry studies are available as off-the-shelf devices, or in many cases as custom made sensor packages. Deployment of those instruments is often the limiting factor for data collection. The Aerial Remote Tag System (ARTS) is a flexible system which can easily be adapted to deploy different tag sensor packages and biopsy collection devices. This paper presents the history and design of the ARTS, and accessories developed for instrumentation and biopsy sampling of cetaceans, such as the recent developed ARTS–LKDart for biopsy sampling. Deployment of archival tags usually requires radio tracking of the instrumented animal, or at least tracking of the tag for recovery. Thus, we also here describe the automatic digital signal processing radio direction finder, the Direction Finder Horten (DFHorten unit).Publisher PDFPeer reviewe

Oceanic drivers of sei whale distribution in the North Atlantic

NRM was supported by Colciencias (Departamento Administrativo de Ciencia, Tecnología e Innovación, Colombia), the University of St Andrews, and NAMMCO.This study investigated the oceanic drivers of sei whale (Balaenoptera borealis) distribution in the central and eastern North Atlantic, and explored how distribution may have changed over almost three decades. Cetacean sightings data were available from Icelandic, Faroese and Norwegian surveys conducted throughout the central and eastern North Atlantic during summer between 1987 and 2015. Effective strip half width was estimated from the data to take account of variation in detection probability. Spatially-referenced environmental variables used as predictors in generalised additive models of sei whale relative density included: relief-related variables seabed depth, slope and aspect; monthly-varying physical oceanographic variables sea surface temperature (SST), mixed layer depth, bottom temperature, salinity, and sea surface height anomaly (SSH); and monthly-varying biological oceanographic variables chlorophyll-a concentration and primary productivity. Preliminary analysis considered which month (March-August) in the dynamic oceanographic variables explained most variability in sei whale density. Models including all variables (“full models”) could only be run for 1998-2015 because data for several variables were missing in earlier years. “Simple models" including only relief-related variables and SST were therefore run for 1987-89, and also for 1998-2015 for comparison. The best-fitting full model for 1998-2015 retained the covariates depth, May SST, May bottom temperature, July salinity, July SSH and July primary productivity. Of these, depth, May SST and July SSH were the strongest predictors of sei whale density. In the simple models for both 1987-89 and 1998-2015, depth (especially), May SST and seabed slope were the strongest predictors of sei whale density. The highest densities of sei whales were predicted in the Irminger Sea and over the Charles-Gibbs Fracture Zone; a pattern driven by large negative SSH, deep water (>1500m) and polar-temperate SST (5-12oC). There was some inter-annual variability in predicted distribution and there appears to be a northward expansion in distribution consistent with prey species responding to ocean warming. The models could be used to predict future distribution of sei whales based on future environmental conditions predicted by climate models.Publisher PDFPeer reviewe