Small Boreal Lake Ecosystem Evolution under the Influence of Natural and Anthropogenic Factors: Results of Multidisciplinary Long-Term Study
Bibliographic record
Abstract
Small aquatic ecosystems of the boreal zone are known to be most sensitive indicators of on-going environmental change as well as local anthropogenic pressure, while being highly vulnerable to external impacts. Compared to rather detailed knowledge of the evolution of large and small lakes in Scandinavia and Canada, and large lakes in Eurasia, highly abundant small boreal lakes of northwest Russia have received very little attention, although they may become important centers of attraction of growing rural population in the near future. Here we present the results of a multidisciplinary, multi-annual study of a small boreal humic lake of NW Russia. A shallow (3 m) and a deep (16 m) site of this lake were regularly sampled for a range of chemical and biological parameters. Average multi-daily, summer-time values of the epilimnion (upper oxygenated) layer of the lake provided indications of possible trends in temperature, nutrients, and bacterio-plankton concentration that revealed the local pollution impact in the shallow zone and overall environmental trend in the deep sampling point of the lake. Organic phosphorus, nitrate, and lead were found to be most efficient tracers of local anthropogenic pollution, especially visible in the surface layer of the shallow site of the lake. Cycling of trace elements between the epilimnion and hypolimnion is tightly linked to dissolved organic matter speciation and size fractionation due to the dominance of organic and organo-ferric colloids. The capacity of lake self-purification depends on the ratio of primary productivity to mineralization of organic matter. This ratio remained >1 both during winter and summer periods, which suggests a high potential of lake recovery from the input of allochthonous dissolved organic matter and local anthropogenic pollution.
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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 | 0.000 |
| 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) | 0.000 | 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".