BENTHIC AND PLANKTONIC ALGAL COMMUNITIES IN A HIGH ARCTIC LAKE: PIGMENT STRUCTURE AND CONTRASTING RESPONSES TO NUTRIENT ENRICHMENT<sup>1</sup>
Bibliographic record
Abstract
We investigated the fine pigment structure and composition of phytoplankton and benthic cyanobacterial mats in Ward Hunt Lake at the northern limit of High Arctic Canada and the responses of these two communities to in situ nutrient enrichment. The HPLC analyses showed that more than 98% of the total pigment stocks occurred in the benthos. The phytoplankton contained Chrysophyceae, low concentrations of other protists and Cyanobacteria (notably picocyanobacteria), and the accessory pigments chl c 2 , fucoxanthin, diadinoxanthin, violaxanthin, and zeaxanthin. The benthic community contained the accessory pigments chl b , chl c 2 , and a set of carotenoids dominated by glycosidic xanthophylls, characteristic of filamentous cyanobacteria. The black surface layer of the mats was rich in the UV‐screening compounds scytonemin, red scytonemin‐like, and mycosporine‐like amino acids, and the blue‐green basal stratum contained high concentrations of light‐harvesting pigments. In a first bioassay of the benthic mats, there was no significant photosynthetic or growth response to inorganic carbon or full nutrient enrichment over 15 days. This bioassay was repeated with increased replication and HPLC analysis in a subsequent season, and the results confirmed the lack of significant response to added nutrients. In contrast, the phytoplankton in samples from the overlying water column responded strongly to enrichment, and chl a biomass increased by a factor of 19.2 over 2 weeks. These results underscore the divergent ecophysiology of benthic versus planktonic communities in extreme latitudes and show that cold lake ecosystems can be dominated by benthic phototrophs that are nutrient sufficient despite their ultraoligotrophic overlying waters.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".