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Record W2121915146 · doi:10.1073/pnas.1414752112

Phytoplankton adapt to changing ocean environments

2015· article· en· W2121915146 on OpenAlexaff
Andrew J. Irwin, Zoe V. Finkel, Frank Müller‐Karger, Luis Tróccoli

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsMount Allison University
Fundersnot available
KeywordsPhytoplanktonClimate changeEcosystemEnvironmental scienceEcologyLimitingMarine ecosystemNutrientEnvironmental changeOceanographyBiologyGeology

Abstract

fetched live from OpenAlex

Model projections indicate that climate change may dramatically restructure phytoplankton communities, with cascading consequences for marine food webs. It is currently not known whether evolutionary change is likely to be able to keep pace with the rate of climate change. For simplicity, and in the absence of evidence to the contrary, most model projections assume species have fixed environmental preferences and will not adapt to changing environmental conditions on the century scale. Using 15 y of observations from Station CARIACO (Carbon Retention in a Colored Ocean), we show that most of the dominant species from a marine phytoplankton community were able to adapt their realized niches to track average increases in water temperature and irradiance, but the majority of species exhibited a fixed niche for nitrate. We do not know the extent of this adaptive capacity, so we cannot conclude that phytoplankton will be able to adapt to the changes anticipated over the next century, but community ecosystem models can no longer assume that phytoplankton cannot adapt.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score0.167

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.245
Teacher spread0.203 · 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 teacher head, 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

Citations161
Published2015
Admission routes1
Has abstractyes

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