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Record W2345380874 · doi:10.4081/jlimnol.2016.1353

Mechanisms underlying recovery of zooplankton in Lake Orta after liming

2016· article· en· W2345380874 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Limnology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsYork University
Fundersnot available
KeywordsZooplanktonRotiferEcologyPersistence (discontinuity)CrustaceanCladoceraBiologySpecies richnessPlanktonInvertebrateWater columnPredationEnvironmental science

Abstract

fetched live from OpenAlex

<p>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 (<em>Bythotrephes</em> and <em>Leptodora</em>) 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.</p>

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.014
GPT teacher head0.229
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it