Mechanisms underlying recovery of zooplankton in Lake Orta after liming
Bibliographic record
Abstract
The goal of this study was to improve the understanding of the large-scale mechanisms underlying the recovery of the zooplankton of Lake Orta from historical contamination, following reduced input of ammonia and metals and the subsequent 1989/90 liming intervention. The industrial pollution had been severe and long-lasting (1929-1990). Zooplankton biodiversity has improved, but most of the new taxa appearing in our counts are rotifers, while many calanoids and the large cladoceran predators (Bythotrephes and Leptodora) that are common in the nearby Lake Maggiore, were still absent from Lake Orta 17 years after liming. To aid understanding of the large-scale mechanisms controlling changes in annual richness, we assessed the annual persistence (P) of Crustacea and Rotifera taxa as an estimator of whether propagules that survived introduction, as result of the natural recolonization process, also thrived. We found that the rate of introduction of zooplankton colonists and their persistence in the water column of Lake Orta changed from 1971 to 2007. New rotifer taxa appeared in the lake after the mid-1980s, when discharge of toxic substances decreased, but their annual persistence was low (P<0.5) until the turn of the century. The numerical values of rotifer and crustacean persistence in Lake Orta were unexpectedly high in 2001 and 2007 (0.55 and 0.72 for rotifers, 0.85 and 0.86 for crustacean, respectively), much higher than in limed lakes in Sudbury, Canada, and in adjacent Lake Maggiore. We hypothesize this could be related to the lack of Cladoceran predators and zooplanktivorous fish in the pelagic waters of Lake Orta.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".