Effects of physical ecosystem engineering and herbivory on intertidal community structure
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 317:29-39 (2006) - doi:10.3354/meps317029 Effects of physical ecosystem engineering and herbivory on intertidal community structure Christopher D. G. Harley1,2,* 1University of Washington, Department of Zoology, Seattle, Washington 98105-1800, USA 2Present address: Department of Zoology, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada *Email: harley@zoology.ubc.ca ABSTRACT: Physical ecosystem engineers play dominant roles in a wide variety of communities. While many of the direct, positive effects of ecosystem engineers are readily apparent, the roles of engineers are often mediated by indirect interactions stemming from the facilitation of one or a few key species. Although direct and indirect effects are both critical drivers of community dynamics, they are rarely considered together with regards to ecosystem engineering. In the present study barnacle and herbivorous gastropod densities are experimentally manipulated to investigate the direct positive effects of habitat provision by barnacles as well as indirect effects mediated by molluscan grazers. Molluscan grazers (Littorina spp.) and herbivorous arthropods were positively influenced by the presence of barnacles. Arthropod abundance and species richness were lower when Littorina spp. were present. This pattern was not influenced by barnacle cover, suggesting that competition among herbivore functional groups was strong but independent of biogenic habitat complexity. In addition, Littorina spp. had strong negative effects on the filamentous alga Urospora penicilliformis, but this effect was only seen in the absence of barnacles. Finally, Littorina spp. reduced the recruitment of the principal habitat-forming barnacle Balanus glandula, suggesting that Littorina spp. may mediate a negative feedback loop in B. glandula population dynamics. Given the ubiquity of ecosystem engineers, similar combinations of direct and indirect influences may have far-reaching consequences for community dynamics and species richness in a wide range of systems. KEY WORDS: Balanus glandula · Biogenic habitat structure · Chthamalus dalli · Competition · Facilitation · Grazing · Littorina plena · Recruitment Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 317. Online publication date: July 18, 2006 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2006 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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".