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Record W4367841892 · doi:10.1242/jeb.245004

Northern copepod mitochondria can't beat the heat

2023· article· en· W4367841892 on OpenAlexaff
Brittney G. Borowiec

Bibliographic record

VenueJournal of Experimental Biology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCopepodHabitatEcologyPopulationBiologyMitochondrionZoologyRange (aeronautics)OceanographyCrustaceanBiochemistryGeology

Abstract

fetched live from OpenAlex

How hot is too hot and why is it too hot? Unravelling the physiology of how animals cope with warming environments can tell us a lot about their evolutionary history as well as their current (and future) habitats. One possible mechanism by which an animal's physiology could limit its heat tolerance is if high temperatures interfered with routine but important metabolic processes such as making energy, ATP, by the mitochondria. Copepods, which often live in splash pools above the high tide line, adapt to the peculiarities of their particular pools. The copepod Tigriopus californicus has made its home in rock pools from balmy Mexico to chilly northern California, and has adapted its mitochondria to the vastly differing climes. With beakers of these copepods, descended from various populations, available in the lab, Tim Healy and Ron Burton from the Scripps Institution of Oceanography, USA, compared how quickly the mitochondria from different populations of copepods made ATP when in warm water and how that related to each populations’ natural habitat to find out whether their mitochondria influenced what temperatures they tolerated and, in doing so, their natural habitat ranges.For each population, the researchers isolated mitochondria from several individuals and provided them with all the materials they needed to make ATP. The team then compared how quickly the mitochondria did this at a range of temperatures from 20°C to a scorching 36°C, and found that the mitochondria from copepods from cold climates generally made ATP faster than those from warm climates, especially at temperatures below 25°C; although that was not surprising, because some animals such as copepods can counteract the natural slowing effect of cold temperatures on their metabolism. However, the northern population's mitochondria were also much more sensitive to high temperatures, as their ability to make ATP declined sharply when the temperature was above the mid-30s. Meanwhile, the mitochondria from southern copepods resisted the heat and happily made ATP at temperatures hot enough to hinder making ATP in the northern populations. Taken together, this suggested that the mitochondria of each population are best adjusted to make ATP at the temperatures that they would naturally encounter in the wild. Healy and Burton then turned their attention to figuring out whether the differences in mitochondrial physiology uncovered in the lab contributed to differences in heat tolerance in the wild.The duo compared the temperature at which each population of copepods made ATP half as fast as normal with the temperature at which they stopped swimming, a sign that it was too hot for them, and discovered that the southern populations, whose mitochondria could churn out decent amounts of ATP at relatively high temperatures, also tended to keep swimming at hotter temperatures, supporting the idea that copepods hit their upper temperature limit when their mitochondria stop performing well. This suggested that having ‘southern style’ or ‘northern style’ mitochondria not only impacted which temperatures the copepods could make the most ATP, but also which temperatures they could survive in the wild.Taken together, it is clear that northern populations of copepods like the cold, while southern populations like the heat, and how fast mitochondria can make ATP at these temperatures underlies at least some of this variation. But how copepod mitochondria react to heat does more than distinguish different populations – it also seems to set the maximum temperature where different populations can survive. As animals scramble to respond to the looming threat of climate change, understanding what sets the temperatures an animal can tolerate will be key to understanding why animals live where they do in the present and where they might live in the future.

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)0.002
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 score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.270
Teacher spread0.248 · 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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