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Record W2944352793 · doi:10.1002/esp.4646

Empirical observations and numerical modelling of tides, channel morphology, and vegetative effects on accretion in a restored tidal marsh

2019· article· en· W2944352793 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEarth Surface Processes and Landforms · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsUniversity of British Columbia
FundersU.S. Army Corps of EngineersDivision of Ocean SciencesMaryland Sea Grant, University of MarylandMaryland Environmental ServiceNational Science Foundation
KeywordsMarshGeologyEstuarySalt marshBayOceanographySedimentHydrology (agriculture)Channel (broadcasting)Accretion (finance)Environmental scienceTidal rangeWetlandGeomorphologyEcology

Abstract

fetched live from OpenAlex

Abstract Tidal marshes form at the confluence between estuarine and marine environments where tidal movement regulates their developmental processes. Here, we investigate how the interplay between tides, channel morphology, and vegetation affect sediment dynamics in a low energy tidal marsh at the Paul S. Sarbanes Ecosystem Restoration Project at Poplar Island. Poplar Island is an active restoration site where fine‐grained material dredged from navigation channels in the upper Chesapeake Bay are being used to restore remote tidal marsh habitat toward the middle bay (Maryland, USA). Tidal currents were measured over multiple tidal cycles in the inlets and tidal creeks of one marsh at Poplar Island, Cell 1B, using Acoustic Doppler Current Profilers (ADCP) to estimate water fluxes throughout the marsh complex. Sediment fluxes were estimated using acoustic backscatter recorded by ADCPs and validated against total suspended solid measurements taken on site. A high‐resolution geomorphic survey was conducted to capture channel cross sections and tidal marsh morphology. We integrated simple numerical models built in Delft3d with empirical observations to identify which eco‐geomorphological factors influence sediment distribution in various channel configurations with differing vegetative characteristics. Channel morphology influences flood‐ebb dominance in marshes, where deep, narrow channels promote high tidal velocities and incision, increasing sediment suspension and reducing resilience in marshes at Poplar Island. Our numerical models suggest that accurately modelling plant phenology is vital for estimating sediment accretion rates. In‐situ observations indicate that Poplar Island marshes are experiencing erosion typical for many Chesapeake Bay islands. Peak periods of sediment suspension frequently coincide with the largest outflows of water during ebb tides resulting in large sediment deficits. Ebb dominance (net sediment export) in tidal marshes is likely amplified by sea‐level rise and may lower marsh resilience. We couple field observations with numerical models to understand how tidal marsh morphodynamics contribute to marsh resilience. © 2019 John Wiley & Sons, Ltd.

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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 score0.240
Threshold uncertainty score0.311

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 head0.019
GPT teacher head0.229
Teacher spread0.210 · 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