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Record W6991935251

Inter-Annual Variation in Eelgrass (Zostera Marina) Distribution and Productivity on Roberts Bank and in Boundary Bay in Southern British Columbia

2016· article· en· W6991935251 on OpenAlexaboutno aff

Bibliographic record

VenueWestern CEDAR (Western Washington University) · 2016
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsnot available
Fundersnot available
KeywordsZostera marinaProductivityBayShoreSeagrassHabitatEstuaryZostera
DOInot available

Abstract

fetched live from OpenAlex

The effects of climate change and other anthropogenic stressors on eelgrass can not be accurately assessed without an understanding of the natural variability within these habitats. Natural and anthropogenic factors have greatly modified the habitat within the Roberts Bank eelgrass meadow over the past 56 years. A causeway, three kilometres in length, was constructed in 1959 that bisected the eelgrass meadow. A second causeway (five kilometres in length) was constructed in 1970 three kilometres north of the first in 1970 which further divided the meadow. Zostera japonica was discovered landward of the Z. marina meadow in the mid 1970s. A review of historical air photographs, orthophotographs, and satellite imagery estimated that the area colonized by Z. marina increased from 449 ha. in 1967 to 964 ha. in 2003. The section of the meadow that is located between two causeways was filmed (digital orthophotos) and ground truthed in 2003 and annually between 2007 and 2014 to assess inter-annual changes in distribution and productivity. Productivity data was analysed from four reference stations in between the causeways and compared with data from two stations west of the causeways, and with two stations in a meadow approximately 26 kilometres to the southeast. Large variations in inter-annual productivity were detected at all sites and trends were generally consistent between locations. Research has shown that eelgrass productivity may be influenced by many large scale environmental factors and near shore oceanic conditions. The inter-annual variation in productivity at the study sites was compared with the Pacific Decadal Oscillation (PDO), sea surface temperature, inter-annual tide height variation, and the onset of daytime spring low tides. The relationship between eelgrass productivity and distribution resulting from variation with these large scale physical influences will be discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.203
Teacher spread0.193 · 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 source (direct Gemma or distilled Codex), 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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