Positive feedback between large-scale disturbance and density-dependent grazing decreases resilience of a kelp bed ecosystem
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 522:1-13 (2015) - DOI: https://doi.org/10.3354/meps11193 FEATURE ARTICLE Positive feedback between large-scale disturbance and density-dependent grazing decreases resilience of a kelp bed ecosystem John M. O'Brien1,*, Robert E. Scheibling1, Kira A. Krumhansl1,2 1Department of Biology, Dalhousie University, Halifax, Nova Scotia B3H 4J1, Canada 2Present address: Hakai Institute, Simon Fraser University, Burnaby, British Columbia V5A 1S6, Canada *Corresponding author: jh876261@dal.ca ABSTRACT: We examined how large-scale disturbances that defoliate kelp beds (outbreaks of an invasive bryozoan, hurricanes) alter local-scale grazing dynamics of an abundant herbivore, the gastropod Lacuna vincta, on the Atlantic coast of Nova Scotia, Canada. From field observations and a 5 wk kelp-thinning experiment that simulated disturbance, we found that snail density and grazing intensity on the kelp Saccharina latissima increased non-linearly with decreasing kelp biomass, as it varied within a site. Grazing intensity on S. latissima also increased non-linearly with decreasing standing kelp biomass across 5 sites spanning 40 km (linear distance) of coast and 2 yr, but we did not find strong support for this relationship for the kelp Laminaria digitata. Intensification of grazing augments the indirect effect of L. vincta on S. latissima (increased blade erosion and fragmentation), and drives it beyond a threshold for further losses of kelp biomass with subsequent storms. This positive feedback between large-scale disturbances and local-scale grazing could reinforce the depletion of kelp and facilitate the establishment of turf-forming algae on Nova Scotian rocky reefs. We conclude that interactions of large external perturbations with local natural perturbations must be considered to understand how drivers of ecosystem change collectively disrupt the balance of top-down and bottom-up forces to cause shifts to unexpected community states. KEY WORDS: Kelp · Turf-forming algae · Feedback · Synergy · Disturbance · Grazing · Hurricanes · Invasive species Full text in pdf format Information about this Feature Article Supplementary material NextCite this article as: O'Brien JM, Scheibling RE, Krumhansl KA (2015) Positive feedback between large-scale disturbance and density-dependent grazing decreases resilience of a kelp bed ecosystem. Mar Ecol Prog Ser 522:1-13. https://doi.org/10.3354/meps11193 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 522. Online publication date: March 02, 2015 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2015 Inter-Research.
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 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) | 0.000 | 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".