BENTHIC ALGAL PRODUCTION ACROSS LAKE SIZE GRADIENTS: INTERACTIONS AMONG MORPHOMETRY, NUTRIENTS, AND LIGHT
Bibliographic record
Abstract
Attached algae play a minor role in conceptual and empirical models of lake ecosystem function but paradoxically form the energetic base of food webs that support a wide variety of fishes. To explore the apparent mismatch between perceived limits on contributions of periphyton to whole-lake primary production and its importance to consumers, we modeled the contribution of periphyton to whole-ecosystem primary production across lake size, shape, and nutrient gradients. The distribution of available benthic habitat for periphyton is influenced by the ratio of mean depth to maximum depth (DR = z/ z(max)). We modeled total phytoplankton production from water-column nutrient availability, z, and light. Periphyton production was a function of light-saturated photosynthesis (BPmax) and light availability at depth. The model demonstrated that depth ratio (DR) and light attenuation strongly determined the maximum possible contribution of benthic algae to lake production, and the benthic proportion of whole-lake primary production (BPf) declined with increasing nutrients. Shallow lakes (z < or =5 m) were insensitive to DR and were dominated by either benthic or pelagic primary productivity depending on trophic status. Moderately deep oligotrophic lakes had substantial contributions by benthic primary productivity at low depth ratios and when maximum benthic photosynthesis was moderate or high. Extremely large, deep lakes always had low fractional contributions of benthic primary production. An analysis of the world's largest lakes showed that the shapes of natural lakes shift increasingly toward lower depth ratios with increasing depth, maximizing the potential importance of littoral primary production in large-lake food webs. The repeatedly demonstrated importance of periphyton to lake food webs may reflect the combination of low depth ratios and high light penetration characteristic of large, oligotrophic lakes that in turn lead to substantial contributions of periphyton to autochthonous production.
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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 | 0.000 |
| 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 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".