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Record W4416407318 · doi:10.3390/jmse13112207

Harvest Recovery of a North Atlantic Intertidal Seaweed, Ascophyllum nodosum: Experimental Design Issues

2025· article· en· W4416407318 on OpenAlexaffabout
Allison A. Snow, David Porter, David J. Garbary, H. Vandermeulen

Bibliographic record

VenueJournal of Marine Science and Engineering · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsAscophyllumIntertidal zoneFucalesHoldfastBiomass (ecology)HabitatCanopyEcosystem

Abstract

fetched live from OpenAlex

As the global demand for seaweed products increases, resource managers, conservation groups, and other stakeholders strive to protect wild seaweed populations and the ecosystem services they provide from the damaging effects of over-harvesting. Ascophyllum nodosum (rockweed) is a slow-growing, intertidal brown alga of the North Atlantic that is commercially harvested for crop biostimulants, soil conditioners, and other products. Rockweed is considered a foundation species due to its high abundance, tall canopy, habitat characteristics, and role in detrital food webs. Rockweed shoots survive after harvesting if the holdfast remains intact, but rates of canopy and biomass recovery depend on the intensity of harvesting. In Maine, USA, and eastern Canada, little is known about how harvesting rockweed at various intensities affects recovery rates of algal height or biomass. Herein, we evaluate published studies and suggest improved experimental designs. Most experimental studies focus on a single harvest event, often with incomplete data on control plots, amount of biomass removed, or previous harvesting history at study sites. Much has been learned from previous work, but more rigorous studies are needed to develop harvest recommendations that address both commercial and conservation-related goals. Importantly, experimental studies of the effects of repeated harvesting on rockweed beds are lacking.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.255
Threshold uncertainty score0.299

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 communication0.0000.000
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 head0.010
GPT teacher head0.205
Teacher spread0.196 · 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
Published2025
Admission routes2
Has abstractyes

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