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Record W1992600948 · doi:10.2495/dne-v7-n3-274-291

Physical circulation and spatial exchange dynamics in a shallow floodplain wetland

2012· article· en· W1992600948 on OpenAlexvenueno aff
Zati Sharip, Matthew R. Hipsey, Shon Schooler, Richard J. Hobbs

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsnot available
FundersInstitut Penyelidikan Air Kebangsaan Malaysia
KeywordsPelagic zoneEnvironmental scienceWetlandLittoral zoneFloodplainHydrology (agriculture)MacrophyteTransectVegetation (pathology)Water levelAtmospheric sciencesEcologyOceanographyGeologyGeography

Abstract

fetched live from OpenAlex

This paper examines the spatial patterns of water exchange based on water temperature variation between littoral and pelagic zones and compares the patterns in a series of shallow lakes at different water levels. Exchange patterns were assessed by developing isotherms along the transects and estimating the surface energy budget using the vertical temperature profi le and time-series measurements. Our results indicate the presence of density-driven fl ow induced by the differential temperature gradient between littoral areas, which are domi-nated by either fl oating-leaved or submerged vegetation, and the open pelagic region. Persistent stratifi cation was noted in the narrower lakes, which was thought to be due to the presence of dense submerged vegetation that attenuate wind-driven turbulence. In addition, variation of thermal stratifi cation and mixing dynamics between these lakes at different water levels has corresponding effects on the biological and chemical regimes. The circulation contributes to increased transport of the phosphate that could favour submerged species and subsequently induce shifts of macrophyte community composition. The results of this study have implications for the rehabilitation and management of 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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.687
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.229
Teacher spread0.222 · 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

Citations11
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Design & Nature and EcodynamicsSame topicCoastal wetland ecosystem dynamicsFrench-language works237,207