Disease as a control of sea urchin populations in Nova Scotian kelp beds
Bibliographic record
Abstract
MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 500:149-158 (2014) - DOI: https://doi.org/10.3354/meps10700 Disease as a control of sea urchin populations in Nova Scotian kelp beds Colette J. Feehan*, Robert E. Scheibling Biology Department, Dalhousie University, Halifax, Nova Scotia B3H 4J1, Canada *Corresponding author: colette.feehan@dal.ca ABSTRACT: In Nova Scotia, Canada, periodic outbreaks of amoebic disease (paramoebiasis) cause mass mortality of sea urchins Strongylocentrotus droebachiensis in subtidal barrens. However, in kelp beds, where sea urchins are cryptic and generally less dense than in barrens, disease outbreaks are not readily observed and the importance of disease in regulating these populations is unknown. To determine whether sea urchin populations in kelp beds are controlled by disease, we analyzed population data from kelp beds at a single location (St. Margarets Bay) across a span of 44 yr (1968 to 2012) to compare changes in size structure and density in relation to the timing of disease outbreaks in adjacent sea urchin aggregations and barrens. We found that sea urchin density, maximum test diameter and percentage of adults decreased following disease outbreaks and increased during intervening periods without disease, indicating that disease regulates the population in kelp beds by limiting survival to adulthood. Our results suggest that disease has replaced predation as a major agent controlling sea urchin populations in Nova Scotian kelp beds. KEY WORDS: Strongylocentrotus droebachiensis · Disease · Phase shift · Predation · Kelp beds Full text in pdf format PreviousNextCite this article as: Feehan CJ, Scheibling RE (2014) Disease as a control of sea urchin populations in Nova Scotian kelp beds. Mar Ecol Prog Ser 500:149-158. https://doi.org/10.3354/meps10700 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 500. Online publication date: March 17, 2014 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2014 Inter-Research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".