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Record W2745447841

Beach wrack communities within a commercially harvested coastline of the Salish Sea

2016· article· en· W2745447841 on OpenAlexaboutno aff
Jessica J. Holden, Shaun MacNeil, Sarah E. Dudas, Brian Charles Kingzett, Francis Juanes

Bibliographic record

VenueWestern CEDAR (Western Washington University) · 2016
Typearticle
Languageen
FieldEngineering
TopicMarine and Offshore Engineering Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyOceanographyFisheryEnvironmental scienceGeologyBiology
DOInot available

Abstract

fetched live from OpenAlex

Accumulations of beach-cast seaweeds and other matter, collectively known as wrack, are a common and ecologically important occurrence along coastal regions worldwide. Between the unincorporated communities of Deep Bay and Bowser, on the east coast of Vancouver Island, beach wrack is primarily composed of an introduced species of red algae called Mazzaella japonica, which became the target of a commercial beach-cast harvest in 2007. Little is known, however, about the ecological role of M. japonica in this recipient system. Furthermore, literature on the effects of harvesting beach-cast seaweed is limited. The goal of this research was therefore threefold: 1) To quantify the contribution of M. japonica to wrack inputs within the harvest region; 2) to explore how wrack characteristics influence macrofauna communities; and 3) to determine if the commercial removal of beach-cast seaweeds has a detectable effect on wrack characteristics and macrofauna community structure. To answer these questions we monitored a series of permanent transects at six sites across the harvest region, from November 2014 until March 2015. We recorded as much as 853 kg (±99.8 SE) of wrack per meter of shoreline, 63 % to 82% of which was identified as M. japonica across sites. Despite the removal of 674.5 tonnes of beach-cast seaweeds, we found that the trends in wrack biomass were similar between both harvested and unharvested locations. Macrofauna communities differed significantly between study sites, as well as with the age class, depth, and total biomass of the wrack from which they were sampled.

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 score0.457
Threshold uncertainty score0.989

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 science0.0010.001
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 head0.016
GPT teacher head0.192
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.

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

Citations0
Published2016
Admission routes1
Has abstractyes

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