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Record W2045595485 · doi:10.1007/s11273-010-9206-y

Salt marsh stabilization affects algal primary producers at the marsh edge

2011· article· en· W2045595485 on OpenAlexaff
Mary I. O’Connor, Christy R. Violin, Andrea Antón, Laura M. Ladwig, Michael F. Piehler

Bibliographic record

VenueWetlands Ecology and Management · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsUniversity of British ColumbiaUniversity of British Columbia Hospital
Fundersnot available
KeywordsMarshSalt marshWetlandBenthic zoneSpartina alternifloraSpartinaEnvironmental scienceEcologyAbundance (ecology)Brackish marshEcosystemOceanographyBiologyGeology

Abstract

fetched live from OpenAlex

As sea level rise and human activities erode coastal wetlands, managers rebuild or preserve wetlands that can perform the ecosystem services of a natural system. One increasingly common mitigation activity is the construction of rock sills in the low marsh zone to stabilize marsh elevation. Sills dramatically alter the physical structure of marshes by changing elevation, adding hard substrate and potentially altering the spatial structure of benthic algal communities in and adjacent to the low marsh. We documented differences in benthic algal abundance at the seaward marsh edge in silled and unsilled marshes in North Carolina. We found that sills were associated with reduced standing stocks of benthic algal primary production and reduced macroalgal taxonomic richness, and this difference was driven primarily by differences in macroalgal abundance. We experimentally tested the effect of macroalgal abundance on cordgrass ( Spartina alterniflora ) growth in the low zone of an unmanipulated marsh, and found that macroalgal removal had no effect on final cordgrass abundance. Our study suggests that salt marsh management through the construction of sills in low marsh zones impacts benthic primary production in the low marsh zone, but that benthic algal production does not affect cordgrass growth over a growing season.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.999

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.185
Teacher spread0.177 · 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.

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

Citations12
Published2011
Admission routes1
Has abstractyes

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