The algal growth-limiting nutrient of lakes located at Mexico’s Mesa Central
Bibliographic record
Abstract
This paper reports on the algal growth-limiting nutrients of five lakes located on Mexico’s Mesa Central - a topic poorly known in the regional limnology of Mexico. The five case studies involved three contiguous watersheds of Michoacán State and provided a trophic state variation from mesotrophic to hypereutrophic; the case studies included Lakes Zirahuén, Pátzcuaro, Teremendo, Cuitzeo and the Cointzio Reservoir. The fieldwork involved the collection of physical and chemical data (including nutrients) from each case study during the dry and rainy seasons of 2010. Additionally, water samples (1 L) were obtained and filtered (0.45 µm) in the laboratory to keep the nutrient content available for bioassays. The chemical analyses suggested a phosphorus (P) limitation in the Cointzio Reservoir, Lake Teremendo and Lake Zirahuén relative to an N:P>16:1. There was a nitrogen (N) limitation at three sampling stations of Lake Pátzcuaro, with an N:P<16:1. As result of the bioassays conducted in July 2012, the Cointzio Reservoir and Lake Teremendo appeared to be P-limited and Lake Pátzcuaro appeared to be N-limited at three sampling stations. Lake Zirahuén showed seasonal variation, with an N limitation during the dry season and a P limitation during the wet season. Those cases with similar results from both methods confirmed the limiting nutrient identification. Lake Cuitzeo, Lake Zirahuén (dry season), and the shallowest sampling station in Lake Pátzcuaro produced unclear results because of divergent outcomes. In terms of the algal growth potential, the Cointzio Reservoir remained unaltered from one season to the next. However, for most of the lakes (with the exception of Lake Pátzcuaro sites 2 and 4), the rainy season provided a dilution effect. Effective lake management depends on a clear recognition of such elements that are in control of the aquatic productivity. In the area of Michoacán, both N and P may act as limiting nutrients.
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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 | 0.001 |
| 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".