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Regulation of spatial and temporal variability of carbon flux in six hard‐water lakes of the northern Great Plains

2009· article· en· W2147595831 on OpenAlexafffund
Kerri Finlay, Peter R. Leavitt, B. Wissel, Yves T. Prairie

Bibliographic record

VenueLimnology and Oceanography · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversité du Québec à MontréalUniversity of Regina
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Regina
KeywordsFlux (metallurgy)Environmental scienceSpatial variabilityProductivityBiomass (ecology)Primary productionEcosystemRedfield ratioWater columnHydrology (agriculture)Atmospheric sciencesCarbon cycleNitrogenEnvironmental chemistryNutrientEcologyChemistryBiologyGeologyPhytoplankton

Abstract

fetched live from OpenAlex

Six hard‐water lakes were sampled May‐August for 14 yr in a 52,000 km 2 catchment to identify the mechanisms that regulate the spatial and temporal variability of net atmospheric exchange of CO 2 of lakes on the Northern Great Plains. Annual mean daily fluxes ranged from ‐100 to >200 mmol C m −2 d −1 , while p CO 2 values varied between 0.3 and 5500 Pa. We observed periods of net CO 2 2 uptake (1995, 2000) and release (1998, 2006) resulting in synchronous variations in net CO 2 flux among lakes. Furthermore, p CO 2 , pH, and chemical enhancement of CO 2 influx all varied coherently among sites. Interannual variation in net CO 2 flux and p CO 2 was correlated strongly with pH, correlated weakly with other physical and chemical conditions, and was uncorrelated to algal biomass, productivity, or ecosystem respiration. In contrast, spatial variability of water‐column p CO 2 was correlated negatively to concentrations of soluble reactive phosphorus, total dissolved nitrogen, pH, and gross primary productivity, suggesting an important role of lake metabolism at large spatial scales. Finally, comparison with an additional 20 saline lakes demonstrated that changes in mean annual pH, p CO 2 , and CO 2 flux during 2002‐2007 were coherent in diverse lakes within a region of >100,000 km 2 and suggest that climatic control of pH and p CO 2 had an unexpectedly great effect on net CO 2 flux through productive hard‐water lake ecosystems.

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 score0.034
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.168
Teacher spread0.162 · 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

Citations136
Published2009
Admission routes2
Has abstractyes

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