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Fish can shrink under harsh living conditions

2010· article· en· W2102489907 on OpenAlexfundno aff
Ari Huusko, Aki Mäki‐Petäys, Morten Stickler, Heikki Mykrä

Bibliographic record

VenueFunctional Ecology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersNatural Resources Canada
KeywordsBiologyJuvenileCompensatory growth (organ)VertebrateFish <Actinopterygii>EcologyEctothermPopulationOncorhynchusIndeterminate growthZoologyFisheryDemography

Abstract

fetched live from OpenAlex

1. Growth of the body length in vertebrates is well known to be unidirectional, with organisms progressively increasing in body size as they become older. However, there is evidence that body length shrinkage is a survival strategy for some vertebrates under unfavourable environmental conditions. Here we report both experimental and field evidence that the body length of young stream-dwelling salmonids can decrease in winter. 2. In examining how juvenile salmonid fish responded to harsh environmental conditions, we were faced with unexpected and previously undocumented observations in terms of growth performance, indicating that fish do shrink in harsh winter conditions. Young salmonids showed significant shrinking of individual body length, up to 10% of the body length, over the course of winter. The dynamics of the growth in length of these fish can be explained by a combination of anorectic stress and environmental conditions. Under stable, sheltered underwater conditions fish were best able to maintain positive growth in length. 3. We propose that growth in body length of a vertebrate animal can be temporally negative, individuals suffering from nutritional deficits shrinking in their length in addition to losing their body mass. There is circumstantial evidence that subsequent compensatory growth can have unexpected and dramatic longer-term costs. Experimental approaches, both field- and laboratory based, are sorely needed to reveal how common a phenomenon negative structural growth is among animals, and what the consequences are for individual performance, and, furthermore, for population dynamics.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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)0.0860.002

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 head0.009
GPT teacher head0.204
Teacher spread0.195 · 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; both teacher heads agree on what is shown here.

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

Citations41
Published2010
Admission routes1
Has abstractyes

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