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Record W4377100160 · doi:10.1242/jeb.245999

Warmer waters make sturgeon think they're sick

2023· article· en· W4377100160 on OpenAlexaboutno aff
Jarren Kay

Bibliographic record

VenueJournal of Experimental Biology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSturgeonLake sturgeonAcipenserHatchlingClimate changeEcologyFisheryBiologyFish <Actinopterygii>Range (aeronautics)GeographyHatching

Abstract

fetched live from OpenAlex

In the lakes and rivers of Manitoba lives the lake sturgeon (Acipenser fulvescens), a large truly prehistoric fish. In years past, this bottom-dwelling fish has been overfished for its meat and eggs, but recent efforts have helped to restore their populations. However, the warming of their waters due to global climate change is causing these sturgeon to face new challenges. Once reaching adulthood, lake sturgeon are hardy and incredibly long lived (the oldest fish caught was estimated to be 125 years old!), but the hatchlings aren't so robust. William Bugg and colleagues from the University of Manitoba, Canada, are trying to determine what happens to the little developing fish when their waters get warmer. Are they in a constant state of stress? And will the warmer waters affect other aspects of their well-being?After obtaining fertilized eggs, the researchers hatched the sturgeon and began the process of getting some of them used to 20°C water. This temperature is within the range that the sturgeon experience in the lakes and rivers early in their development, but these higher temperatures are expected to last longer and get even hotter as the climate changes. The team then measured the expression levels of genes related to stress, including those that are important in fighting off infections. When the fish were raised at 20°C, they had higher levels of mRNA for genes involved in detecting pathogens (bacteria and viruses), the immune system response (to attack the bacteria and viruses) and the stress response. This suggests that being raised in warmer water causes the fish to be stressed and their immune system to respond similarly to the way it does when the fish are sick.So, if the sturgeon were already responding as if they were stressed and sick, what would happen if they really were under attack by bacteria? To answer this, Bugg and colleagues measured the mRNA levels of these same genes after the sturgeon were given doses of bacteria. The sturgeon raised at 20°C couldn't generate as big of a response to these bacterial invaders as sturgeon that were raised at 16°C. This means that sturgeon from warmer waters couldn't fight off bacterial infections as well as those raised in cooler waters. In fact, when given the higher dose of bacteria, 100% of the sturgeon raised in 20°C succumbed to the infection, while only 1.3% of the fish raised at 16°C were unable to fight off the same dose of bacteria.This surprising result led the team to question whether there were other aspects of the sturgeon's stress response or development that were affected by being raised at 20°C. The increased temperature also caused an increase in the levels of the stress hormone cortisol, and a decrease in liver size, which is an indication of the amount of energy stores the fish have. Interestingly, the fish raised at 20°C were bigger, suggesting the sturgeon were putting most of their energy towards growth without reserving as much for energy stores. In this case, having additional energy stores may have helped fish fight off bacterial infections.However, being raised at 20°C did have one potential benefit; it increased the temperature at which fish could function. As the researchers slowly increased the water temperature, they tested the ability of the sturgeon to withstand rising temperatures in the future. Sturgeon raised in warmer waters were able to tolerate hotter water temperatures than those raised at 16°C. So, while our efforts at conserving this important fish species have shown some success, global climate change will present a new and unexpected challenge to these potentially long-lived fish.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.003

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 head0.018
GPT teacher head0.272
Teacher spread0.254 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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