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Record W2323578286 · doi:10.1139/cjz-2013-0047

Responses of caribou and reindeer (<i>Rangifer tarandus</i>) to acute food shortages in spring

2013· article· en· W2323578286 on OpenAlexvenueno aff
Daniel P. Thompson, Perry S. Barboza

Bibliographic record

VenueCanadian Journal of Zoology · 2013
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyForageFood shortageAnimal scienceForagingReproductionDry matterReproductive successEconomic shortageEcologyPopulationDemography

Abstract

fetched live from OpenAlex

Migratory caribou and sedentary reindeer (Rangifer tarandus (L., 1758)) can encounter acute food shortages during spring. We examined the response to short-term food restrictions by measuring individual food intake, body mass, and activity of 2-year-old unbred female caribou and reindeer from 25 April to 29 May 2011. Caribou lost 2%–3% of body mass on days when mean dry matter (DM) intakes (60 ± 6 g DM·kg−0.75·d−1) were restricted up to 75%. Caribou regained body mass as intake increased to 98 ± 8 g DM·kg−0.75·d−1 following restriction without a change in digestibility (82%–83%). In reindeer, digestibility increased (78%–83%) as intakes decreased (67–45 g DM·kg−0.75·d−1). Food restriction did not affect activity for either subspecies. We suggest that, at high digestive efficiency, Rangifer have “spare capacity”, to increase DM intake to compensate for lost foraging opportunity or to use patches of emerging high-quality forage. Furthermore, caribou with large fat reserves lost proportionally more body mass, consumed less food, and were less active than leaner caribou. Our data indicate that Rangifer use flexible responses of food intake, digestion, and body condition to maximize survival and reproduction in both migratory and sedentary ecotypes at the end of winter.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.027
GPT teacher head0.313
Teacher spread0.286 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations16
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Zoology→Same topicIndigenous Studies and Ecology→French-language works237,207→