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A test of Tyler’s Line – response of chironomids to a pH gradient in Tasmania and their potential as a proxy to infer past changes in pH

2010· article· en· W2127151231 on OpenAlexafffund
Andrew Rees, Les C. Cwynar

Bibliographic record

VenueFreshwater Biology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicFreshwater macroinvertebrate diversity and ecology
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEcologyIndicator valueTaxonSpecies richnessChironomidaeInvertebrateLake ecosystemEcosystemBiology

Abstract

fetched live from OpenAlex

Summary 1. Tyler’s Line delimits two distinct limnological provinces that reflect differences in climate, geology and vegetation in Tasmania. Lakes west of Tyler’s Line are typically acidic and dystrophic with relatively shallow euphotic zones, whereas eastern lakes are circumneutral and oligotrophic or ultra‐oligotrophic, allowing deeper penetration of light. Consequently, Tyler’s Line defines a boundary where species assemblages change over a relatively short distance. 2. A survey of 48 Tasmanian lakes was undertaken to identify indicator taxa of the two limnological provinces and breakpoints along the pH gradient where shifts in taxa occur. Chironomidae (Diptera) were used because they are ideal candidates for lake classification. 3. Three independent methods (geographical position, piecewise linear regression, two‐way indicator species analysis) verified that chironomids accurately reflect the environmental variables defining Tyler’s Line at lake and catchment scales. Chironomid genera are often speciose, and members of the same genus can have markedly different responses to a given environmental variable. Although the types of taxa changed along the pH gradient, richness did not. This finding contrasts with many studies from the northern hemisphere but accords with other studies from Australia. 4. Models of pH, developed using both partial least squares and weighted averaging partial least squares, can be used to understand past natural variability of pH in Tasmania and to test hypotheses regarding the timing, magnitude and source of contamination in impacted aquatic ecosystems.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
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 science0.0000.001
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 head0.007
GPT teacher head0.204
Teacher spread0.197 · 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

Citations22
Published2010
Admission routes2
Has abstractyes

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