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Implications of <i>Chaoborus</i> pupation and ecdysis in cold water

2001· article· en· W2151353598 on OpenAlexaff
Chantal Ouimet

Bibliographic record

VenueFreshwater Biology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEcdysisPupaBiologyPredationLarvaPredatorEcologyZooplanktonNymphZoologyInstar

Abstract

fetched live from OpenAlex

1. Cold water acted differently to delay and lengthen the pupation period for the larvae of two species of the zooplankton predator Chaoborus (Diptera: Chaoboridae). During Chaoborus pupation, the zooplankton community is released from predation, while the dark‐coloured Chaoborus pupae are more susceptible to their own predators. 2. Fourth instar larvae of Chaoborus americanus and C. trivittatus , collected from an oligotrophic lake, were reared individually at 5 °C in the dark. Chaoborus americanus was also reared at 9 and 12 °C under spring photoperiod conditions (L : D, 16 : 8 h). Individuals were observed through pupation to emergence (ecdysis) or death. 3. Chaoborus americanus pupated at 5, 9 and 12 °C with substantial emergence only at 12 °C. In comparison, C. trivittatus emerged at 5 °C. Light was not a necessary cue for pupation and ecdysis, contrary to previous reports. Cold water delayed the onset and lengthened and increased the variability of the duration of pupation. 4. In Shirley Lake, C. americanus pupated in late June–early July while C. trivittatus pupated first in April and again in June–July. 5. Chaoborus americanus pupae needed a temperature cue to complete ecdysis. The ecdysis temperature threshold helps to explain the difference in pupation timing, and the geographical distribution, of C. americanus and its relatively inflexible life history contrasted with C. trivittatus . Delayed predator pupation in years with low spring temperature can affect the community dynamics of the prey.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.995

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)0.0060.000

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 head0.012
GPT teacher head0.235
Teacher spread0.223 · 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 designObservational
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

Citations13
Published2001
Admission routes1
Has abstractyes

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