Microzooplankton grazing before, during and after a cyanobacterial bloom in Vancouver Lake, Washington, USA
Bibliographic record
Abstract
AME Aquatic Microbial Ecology Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials AME 64:163-174 (2011) - DOI: https://doi.org/10.3354/ame01514 Microzooplankton grazing before, during and after a cyanobacterial bloom in Vancouver Lake, Washington, USA Jennifer Boyer, Gretchen Rollwagen-Bollens*, Stephen M. Bollens School of Earth and Environmental Sciences, Washington State University Vancouver, Vancouver, Washington 98686, USA *Corresponding author. Email: rollboll@vancouver.wsu.edu ABSTRACT: We conducted 16 dilution experiments from April 2008 to January 2009 to estimate microzooplankton grazing and intrinsic phytoplankton growth rates before, during and after a bloom of filamentous cyanobacteria in Vancouver Lake, Washington, USA. Intrinsic phytoplankton growth rates were low in April (~0.4 d−1), increased to a maximum (1.2 d−1) in May, and then declined to zero and became negative in June and early July, prior to a phytoplankton bloom dominated by cyanobacteria (Aphanizomenon flos-aquae). Phytoplankton growth rates rose as the bloom progressed, reaching rates >1.0 d−1 in August and September, then declined through autumn. Spring microzooplankton grazing rates were low (−0.3 to 0.3 d−1), then became substantially negative (−1.1 to −1.5 d−1) preceding the chlorophyll a bloom. During the bloom, grazing rates quickly increased to a maximum of 0.8 d−1 and remained high as the bloom declined. Microzooplankton grazing specifically on cyanobacteria was high in spring (1.0 d−1), negative just before the bloom (−0.7 d−1 to −1.0 d−1), and low in autumn (0.3 to 0.7 d−1). Negative grazing on cyanobacteria immediately before the bloom may have been due to preferential grazing on other co-occurring prey, thus enabling the bloom to form, while higher grazing rates on cyanobacteria, especially on Aphanizomenon flos-aquae, in autumn is likely to have contributed to the bloom's decline. These findings show that microzooplankton can potentially influence cyanobacterial blooms directly and indirectly through grazing. KEY WORDS: Microzooplankton · Grazing · Aphanizomenon flos-aquae · Harmful algal bloom · Eutrophication · Cyanobacteria Full text in pdf format PreviousNextCite this article as: Boyer J, Rollwagen-Bollens G, Bollens SM (2011) Microzooplankton grazing before, during and after a cyanobacterial bloom in Vancouver Lake, Washington, USA. Aquat Microb Ecol 64:163-174. https://doi.org/10.3354/ame01514 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in AME Vol. 64, No. 2. Online publication date: September 01, 2011 Print ISSN: 0948-3055; Online ISSN: 1616-1564 Copyright © 2011 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".