MétaCan
Menu
Back to cohort
Record W142491001

Population genetics and behavioural ecology of North Atlantic minke whales (Balaenoptera acutorostrata)

2009· dissertation· en· W142491001 on OpenAlexaboutno aff
Pia Anderwald

Bibliographic record

VenueDurham e-Theses (Durham University) · 2009
Typedissertation
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersFoundation Dr. Joachim de GiacomiSchweizerische StudienstiftungNational Geographic Society
KeywordsMinke whaleEcologyForagingBalaenopteraPopulationHabitatBaleenGeographyBiologyFisheryWhale
DOInot available

Abstract

fetched live from OpenAlex

Regional habitat use by a species, dictated by the spatial and temporal availability of resources, influences its distribution patterns and ultimately population genetic structure. Seasonal migrations between geographically separated breeding and feeding areas, as occur in many baleen whales, can complicate these relationships. Here I try to integrate the population structure of minke whales over the whole North Atlantic with regional habitat use and behavioural adaptations to a particular summer feeding ground, the Hebrides off West Scotland. Whereas no genetic differentiation could be found between separate feeding areas as far apart as Canada, the UK and Svalbard, using microsatellites and mtDNA, the presence of two cryptic breeding populations was detected, which form mixed assemblages on feeding grounds across the North Atlantic. This implies fidelity to at least two breeding grounds irrespective of proximity to feeding areas, i.e. extensive seasonal migrations (over half the North Atlantic or more), which may require a re-assessment of current management stocks. These findings were consistent with the mobility and flexibility in habitat use and behaviour observed within the Hebrides. Results from Generalized Additive Models indicated that minke whale distribution was dependent largely on temporally variable parameters (temperature in spring, chlorophyll concentration in autumn), besides depth and, to a lesser extent, topography. However, fine-scale foraging behaviour was dictated primarily by the strength and direction of tidal currents. Distribution patterns according to environmental parameters changed through the season, but were largely consistent between the entire Hebrides (cell resolution of 4min) and a smaller core study area (2min), and over a time period of 15 years. Significantly higher sighting rates in areas of likely sandeel presence in spring, but not during the rest of the season, combined with prey samples from the core study area consisting almost entirely of sprat in August/September, indicate a switch in diet between early and late season and are consistent with the changes in habitat use. Site fidelity within the core study area was high only during periods of high feeding activity, but low at other times and between years, so that individual specializations to fine-scale feeding areas, as observed off Washington State, seem unlikely. Significant interannual changes in minke sighting rates between 2003-07, both within the core study area and over the entire Hebrides, were paralleled by changes in phytoplankton concentration, local sprat landings by the fishing fleet, and seabird breeding success and numbers counted at sea, particularly common guillemots. Auks were also the seabird guild that minke whales were most likely to associate with during foraging, taking advantage of tight bait-balls concentrated by them. The significant relationships with primary productivity make bottom-up control the most likely scenario for dictating concentrations of whale and seabird prey species in West Scotland. The ability to switch between different prey according to their availability through the season, and a distribution influenced by temporally variable parameters (temperature and chlorophyll concentration), combined with adjustments in foraging activity dependent on variable conditions at fine spatial scales (tides), enable minke whales to optimise exploitation of patchy prey concentrations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.210
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueDurham e-Theses (Durham University)Same topicMarine animal studies overviewFrench-language works237,207