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Abiotic and biotic processes in lakes recovering from acidification: the relative roles of metal toxicity and fish predation as barriers to zooplankton re‐establishment

2010· article· en· W1899851446 on OpenAlexaffabout
Amanda Valois, Wendel Keller, Charles W. Ramcharan

Bibliographic record

VenueFreshwater Biology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Toxicology and Ecotoxicology
Canadian institutionsLaurentian University
Fundersnot available
KeywordsZooplanktonAbiotic componentBiotic componentEcologyBiologyPredationDaphniaPerchHabitatPlanktonAquatic ecosystemEnvironmental scienceFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Summary 1. Recovery of acidified aquatic systems may be affected by both abiotic and biotic processes. However, the relative roles of these factors in regulating recovery may be difficult to determine. Lakes around the smelting complexes near Sudbury, Ontario, Canada, formerly affected by acidification and metal exploration, provide an excellent opportunity to examine the factors regulating the recovery of aquatic communities. 2. Substantial recovery of zooplankton communities has occurred in these lakes following declines in acidity and metal concentrations, although toxicity by residual metals still appears to limit survival for many species. Metal bioavailability, not simply total metal concentrations, was very important in determining effects on zooplankton and was associated with a decrease in the relative abundance of cyclopoids and Daphnia spp., resulting in communities dominated by Holopedium gibberum. 3. As chemical habitat quality has improved and fish, initially yellow perch and later piscivores (e.g. smallmouth bass, walleye), have invaded, biotic effects on the zooplankton are also becoming apparent. Simple fish assemblages dominated by perch appear to limit the survival of some zooplankton species, particularly Daphnia mendotae . 4. Both abiotic (residual metal contamination) and biotic (predation from planktivorous fish) processes have very important effects on zooplankton recovery. The re‐establishment of the zooplankton in lakes recovering from stress will require both improvements in habitat quality and the restoration of aquatic food webs.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
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 studies0.0000.001
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 head0.008
GPT teacher head0.223
Teacher spread0.214 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations46
Published2010
Admission routes2
Has abstractyes

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