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
Bibliographic record
Abstract
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.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".