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Record W4413902105 · doi:10.3389/frish.2025.1672665

Editorial: Patterns, causes and consequences of intraspecific variation in environmental tolerance in fishes

2025· editorial· en· W4413902105 on OpenAlexaboutno aff
David J. McKenzie, Katja Anttila

Bibliographic record

VenueFrontiers in Fish Science · 2025
Typeeditorial
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsnot available
Fundersnot available
KeywordsIntraspecific competitionVariation (astronomy)BiologyEcologyZoology

Abstract

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Intraspecific variation in functional traits of organisms is a fundamental component of biodiversity, which is of particular significance in an era of human-induced rapid environmental change (HIREC) (Bolnick et al., 2011; Mimura et al., 2017; Sih et al., 2011). The vulnerability of fish species to environmental stresses will be influenced by the extent of intraspecific variation in functional traits, especially variation in traits of physiological tolerance (Anttila et al., 2013; Babin & Rees, 2025; McKenzie et al., 2020; Nati et al., 2021). Possessing a broad range of tolerance phenotypes among populations, and also within them, can reduce a species’ immediate sensitivity to environmental stressors through a number of ecological mechanisms (Bennett et al., 2019; Bolnick et al., 2011). If there is a link between phenotypic variation and underlying genetic diversity in the species, this can foster adaptability and evolvability over the longer term, by providing genotypes for selection as the environment changes (Bennett et al., 2019; Moran et al., 2016; Pacifici et al., 2015). Furthermore, plasticity during early development can sometimes help to cope with stressors encountered in later life, and parents can even pass on this tolerance via intergenerational plasticity involving non-genetic inheritance (Audet et al., 2025). When fish species are challenged by environmental stressors, such as those that arise HIREC, population sensitivity and adaptability will be major determinants of a species’ relative vulnerability and resilience (Bolnick et al., 2011; Pacifici et al., 2015). There is a need, therefore, for research to understand patterns, causes and consequences of intraspecific variation in environmental tolerance in fishes. This Research Topic comprises two review articles and three original research articles, in the field of fish experimental biology.Hypoxia (low dissolved oxygen) is a major environmental stressor for fishes, which is growing in extent and severity due to HIREC (Sampaio et al., 2021). Babib and Rees review and synthesize research on intraspecific variation in hypoxia tolerance in fishes. They discuss major metrics of hypoxia tolerance, from physiological such as the critical oxygen partial pressure (Pcrit) for regulation of standard metabolic rate, to behavioural such as the oxygen tension that elicits aquatic surface respiration. Importantly they review how tolerances vary 1) among different geographic locations; 2) among genetic strains; 3) with acclimation, and 4) among individuals. Intraspecific variation in hypoxia tolerance is wide-ranging at scales from populations down to individuals, and driven by both genetic and environmental (plastic) factors. The crucial message is that different fish species/populations utilize different strategies for tolerance, which depend on evolutionary history and environmental context. There is an urgent need for greater standardization of methods, attention to negative and individual-level data, and development of new, ecologically meaningful metrics. Future research is important because understanding which traits predict survival under hypoxic episodes can inform conservation, aquaculture strain selection, and management strategies.Along with hypoxia, thermal stress due to global warming is another major challenge to fishes (Little et al., 2020). Nati and co-authors investigated patterns of variation in tolerance of hypoxia and warming among the three genetic populations of European seabass Dicentrarchus labrax, that occupy the Atlantic, and Western and Eastern Mediterranean. Tolerance was evaluated as sub-lethal physiological metrics such as Pcrit (or critical oxygen saturation, Scrit) and critical thermal maximum for swimming (CTSmax) (Blasco et al., 2024). The populations exhibited complex patterns of variation with no clear evidence that tolerance varied as might be expected from broadscale thermal gradients across their ranges. Among individuals, there was no clear evidence of functional associations between tolerance of hypoxia versus warming, or of a dependence of tolerance on body size or metabolic rate. Nonetheless, the results are useful in identifying the most robust populations to farm in cage mariculture of this species, a major industry that must adapt to HIREC. Patterns of interpopulation variation in tolerance of acute warming were also the focus of the study by Zillig and co-authors, on populations of chinook salmon Oncorhynchus tshawytscha from seven restocking hatcheries that span diverse ecoregions along the West Coast of the United States. Thermal tolerance was evaluated as critical thermal maximum (CTmax) in juveniles of each population acclimated to three temperatures, to test the thermal trade-off hypothesis, whereby individuals or populations with higher absolute tolerance have a reduced capacity for acclimation of tolerance. There was evidence of the trade-off among individuals but not when comparing populations. Among populations, tolerance was broadly related to their latitudinal range and natural rearing temperatures. The results can help identify hatchery populations at risk of thermal stress, and highlight the need to consider populational diversity when projecting responses to HIREC by economically important species.The report by Hoots and co-authors considers an altogether different type of stress in fishes, the social environment of gregarious species. The study manipulated social groupings of juvenile inanga Galaxias maculatus, a temperate estuarine fish, to demonstrate that both social environment and metabolic rates mediate individual diversity in growth performance. The effects were context-dependent and question the assumption that slow growers are typically subordinate. These results are interesting from a fundamental perspective but also have implications for selecting fast growth phenotypes in aquaculture or stock enhancement.In the final contribution, Audet and co-authors synthesize two decades of collaborative research on brook charr, Salvelinus fontinalis, in a tribute to the great fish biologist Louis Bernatchez. The research focuses on charr strains and ecotypes from Québec, Canada, which differ in life history strategies such as being either resident or migratory. It has investigated how genetic, epigenetic and environmental factors have interacted to shape broad diversity in the populations’ developmental and physiological plasticity. The populations differ markedly in their responses to environmental change and their adaptive potential, such that conservation planning for brook charr in an era of HIREC requires population-specific approaches. The review demonstrates that the brook charr is an excellent model to understand how interactions of genome and environment can sustain phenotypic plasticity in fishes in a rapidly changing world.Overall, the contributions demonstrate that exploring intraspecific diversity in tolerance of environmental stressors in fishes has fundamental biological interest but also important potential applications for management and conservation of fish diversity, and of the resources that fishes represent to humans. We would like to thank the contributors, we hope that readers will find the articles interesting and useful in their own fish biology research.

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)0.005
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.035
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0050.002
Science and technology studies0.0020.002
Scholarly communication0.0060.004
Open science0.0050.002
Research integrity0.0110.011
Insufficient payload (model declined to judge)0.0350.019

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 head0.006
GPT teacher head0.207
Teacher spread0.201 · 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 designNot applicable
Domainnot available
GenreEditorial

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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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