Wasted effort: recruitment and persistence of kelp on algal turf
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 600:3-19 (2018) - DOI: https://doi.org/10.3354/meps12677 FEATURE ARTICLE Wasted effort: recruitment and persistence of kelp on algal turf Kaitlin E. Burek*, John M. O’Brien, Robert E. Scheibling Department of Biology, Dalhousie University, Halifax, NS, B3H 4R2, Canada *Corresponding author: kaitlin.burek@dal.ca ABSTRACT: Declines in kelp abundance over the past 3 decades have resulted in a shift from luxuriant kelp beds to extensive mats of turf-forming algae in Nova Scotia, Canada. With the reduced availability of open rocky substrate, kelps are increasingly recruiting to turf algae. At 3 sites near Halifax, we found that turf-attached kelp Saccharina latissima was generally restricted to smaller size classes (<50 cm length) than rock-attached kelp at 12 m depth. Turf-attached kelp allocated a greater proportion of biomass to the holdfast (anchoring structure), which differed morphologically from that of rock-attached kelp and had lower attachment strength. To assess how these differences affect survival, we monitored kelp in 2 m diameter plots at 11 m depth over 40 wk at 1 site. Smaller kelps were predominantly turf-attached and larger ones rock-attached in late summer and autumn, but there was near-complete loss of both turf- and rock-attached kelp over winter when wave action was greatest. In a concurrent manipulative experiment at 5 m depth at another site, we transplanted small boulders with turf- or rock-attached kelp to a wave-exposed or protected location. Survival was greater for rock-attached transplants at both locations after 12 wk, with a complete loss of turf-attached kelp in the wave-exposed treatment. Classification based on holdfast morphology showed that 76% of drift kelp within a depositional area at this site was once turf-attached. Low survival of kelps that recruit to turf algae, likely due to wave dislodgement, may represent an important feedback that increases resilience of a turf-dominated state and prevents reestablishment of kelp. KEY WORDS: Kelp · Turf-forming algae · Holdfast · Attachment strength · Recruitment · Feedback Full text in pdf format Information about this Feature Article Supplementary material NextCite this article as: Burek KE, O’Brien JM, Scheibling RE (2018) Wasted effort: recruitment and persistence of kelp on algal turf. Mar Ecol Prog Ser 600:3-19. https://doi.org/10.3354/meps12677 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 600. Online publication date: July 30, 2018 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2018 Inter-Research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".