DeepSData
Dataset guide · Economics & social science

A comparative analysis of life-history features and adaptive strategies of Arctic and subarctic seal species - who will win the climate change challenge?

This dataset contains life-history trait data for four seal species (ringed, bearded, harp, harbour) in the Canadian Arctic, published by Fisheries and Oceans Canada, based on Inuit subsistence harvests.

AccessFree to access
LicenceLicense statement is still being checked
ProducerFisheries and Oceans Canada

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Economics & social scienceFree to access

Key facts

InstitutionFisheries and Oceans Canada
CoverageCanadian Arctic
Time spanSee official page
Scale4 files

Contents & fields

The dataset includes data from a 2024 study published in Canadian Journal of Zoology, covering species, location, harvest date, sex, age, standard length, girth, fat depth, teste size, parity status, pregnancy status, corpora lutea (n), corpus albicans (n), follicles (n). The data are raw, unfiltered, and unprocessed historical data provided by harvesters, not screened for outliers.

  • species——Seal species
  • location——Sampling location
  • harvest date——Date of harvest
  • sex——Sex
  • age——Age
  • standard length——Standard length
  • girth——Girth
  • fat depth——Fat depth
  • teste size——Teste size
  • parity status——Parity status
  • pregnancy status——Pregnancy status
  • corpora lutea (n)——Number of corpora lutea

Research uses

Suitable for ecological and conservation biology research on range shifts, life-history strategy comparisons, and adaptive evolution of Arctic and subarctic seal species under climate change.

Information comes from the source page. Please check that page for current details and terms.

Keywords

Arctic sealslife historyclimate changeCanadaFisheries and Oceans CanadaInuit harvest

Access and licence

Licence: License statement is still being checked · Source page
Rights details not yet verified
| Free to access

Why this is hard to get on your own

When obtaining raw observational data on Arctic seal life history, challenges include scattered data sources, incomplete field descriptions, and the need to screen outliers.

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