Dynamics of primary productivity in relation to submerged vegetation of a shallow, eutrophic lagoon: a field and mesocosm study
Bibliographic record
Abstract
Abstract Aquatic ecosystems nowadays are under constant pressure, either from recent or historical events. In most systems with increased nutrient supply, submerged macrophytes got replaced by another stable state, dominated by phytoplankton as main primary producer. Yet, reducing the nutrient supply did not yield the aimed goal of restored habitats for submerged macrophytes in systems worldwide. The question arises, why submerged macrophytes do not re-colonize, and if they are actually competitive. Therefore, primary production assays were conducted in ex-situ bentho-pelagic mesocosms and compared to the actual ecosystem, a turbid brackish lagoon of the southern Baltic Sea. Mesocosm were either manipulated to be colonized by macrophytes, or stayed phytoplankton dominated. Oxygen evolution was monitored over a period of five months in 5 min (mesocosms) to 10 min (ecosystem) intervals. Surface and depth-integrated production was calculated to analyse seasonal and areal resolved production patterns. It was found that macrophyte mesocosms were more stable, when considering only surface O 2 production. However, calculating depth-integrated production resulted in net-heterotrophy in both shallow mesocosms approaches and the actual ecosystem. This heterotrophy is likely mediated by sediment respiration and POC accumulation in mesocosms, and a low share of productive to respiring water column in the actual ecosystem. Therefore, it seems unlikely that macrophytes will re-settle, as constant net-heterotrophy may allow for high-nutrient turnover at sediment-water interfaces and within the water column, favouring phytoplankton. Changes within the ecosystem cannot be expected without further restoration measures within and in the systems proximity.
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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 | 0.000 |
| 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) | 0.001 | 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".