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Record W4280543396 · doi:10.1242/jeb.216440

Global change and physiological challenges for fish of the Amazon today and in the near future

2022· review· en· W4280543396 on OpenAlexafffund
Adalberto Luís Val, Chris M. Wood

Bibliographic record

VenueJournal of Experimental Biology · 2022
Typereview
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsMcMaster UniversityUniversity of British Columbia
FundersFundação de Amparo à Pesquisa do Estado do AmazonasCiência sem FronteirasConselho Nacional de Desenvolvimento Científico e TecnológicoNatural Sciences and Engineering Research Council of CanadaCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsAmazon rainforestBiogeochemistryDissolved organic carbonBlackwaterDeforestation (computer science)Flood mythEnvironmental scienceClimate changeFreshwater fishEcologyFish <Actinopterygii>Hydrology (agriculture)FisheryGeographyBiologyGeology

Abstract

fetched live from OpenAlex

Amazonia is home to 15% (>2700, in 18 orders) of all the freshwater fish species of the world, many endemic to the region, has 65 million years of evolutionary history and accounts for 20% of all freshwater discharge to the oceans. These characteristics make Amazonia a unique region in the world. We review the geological history of the environment, its current biogeochemistry and the evolutionary forces that led to the present endemic fish species that are distributed amongst three very different water types: black waters [acidic, ion-poor, rich in dissolved organic carbon (DOC)], white waters (circumneutral, particle-rich) and clear waters (circumneutral, ion-poor, DOC-poor). The annual flood pulse is the major ecological driver for fish, providing feeding, breeding and migration opportunities, and profoundly affecting O2, CO2 and DOC regimes. Owing to climate change and other anthropogenic pressures such as deforestation, pollution and governmental mismanagement, Amazonia is now in crisis. The environment is becoming hotter and drier, and more intense and frequent flood pulses are now occurring, with greater variation between high and low water levels. Current projections are that Amazon waters of the near future will be even hotter, more acidic, darker (i.e. more DOC, more suspended particles), higher in ions, higher in CO2 and lower in O2, with many synergistic effects. We review current physiological information on Amazon fish, focusing on temperature tolerance and ionoregulatory strategies for dealing with acidic and ion-poor environments. We also discuss the influences of DOC and particles on gill function, the effects of high dissolved CO2 and low dissolved O2, with emphasis on water- versus air-breathing mechanisms, and strategies for pH compensation. We conclude that future elevations in water temperature will be the most critical factor, eliminating many species. Climate change will likely favour predominantly water-breathing species with low routine metabolic rates, low temperature sensitivity of routine metabolic rates, high anaerobic capacity, high hypoxia tolerance and high thermal tolerance.

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)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.143
GPT teacher head0.344
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
GenreReview

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

Citations43
Published2022
Admission routes2
Has abstractyes

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