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Record W2278967416 · doi:10.1002/lno.10248

Metabolic and physiochemical responses to a whole-lake experimental increase in dissolved organic carbon in a north-temperate lake

2015· article· en· W2278967416 on OpenAlexaff
Jacob A. Zwart, Nicola Craig, Patrick T. Kelly, Stephen D. Sebestyen, Christopher T. Solomon, Brian C. Weidel, Stuart E. Jones

Bibliographic record

VenueLimnology and Oceanography · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsMcGill University
Fundersnot available
KeywordsDissolved organic carbonEnvironmental scienceEcosystemPelagic zoneThermoclineTemperate climateHeterotrophCarbon cycleEcologyEnvironmental chemistryChemistryGeologyBiology

Abstract

fetched live from OpenAlex

Over the last several decades, many lakes globally have increased in dissolved organic carbon (DOC), calling into question how lake functions may respond to increasing DOC. Unfortunately, our basis for making predictions is limited to spatial surveys, modeling, and laboratory experiments, which may not accurately capture important whole-ecosystem processes. In this article, we present data on metabolic and physiochemical responses of a multiyear experimental whole-lake increase in DOC concentration. Unexpectedly, we observed an increase in pelagic gross primary production, likely due to a small increase in phosphorus as well as a surprising lack of change in epilimnetic light climate. We also speculate on the importance of lake size modifying the relationship between light climate and elevated DOC. A larger increase in ecosystem respiration resulted in an increased heterotrophy for the treatment basin. The magnitude of the increase in heterotrophy was extremely close to the excess DOC load to the treatment basin, indicating that changes in heterotrophy may be predictable if allochthonous carbon loads are well-constrained. Elevated DOC concentration also reduced thermocline and mixed layer depth and reduced whole-lake temperature. Results from this experiment were quantitatively different, and sometimes even in the opposite direction, from expectations based on cross-system surveys and bottle experiments, emphasizing the importance of whole-ecosystem experiments in understanding ecosystem response to environmental change.

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)0.000
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 score0.232
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.010
GPT teacher head0.209
Teacher spread0.198 · 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

Citations61
Published2015
Admission routes1
Has abstractyes

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