A climosequence of chronosequences in southwestern Australia
Bibliographic record
Abstract
Abstract To examine how climate affects soil development and nutrient availability over long timescales, we studied a series of four long-term chronosequences along a climate gradient in southwestern Australia. Annual rainfall ranged from 533 mm to 1185 mm (water balance from –900 mm to +52 mm) and each chronosequence included Holocene (≤6.5 ka), Middle Pleistocene (120–500 ka), and Early Pleistocene (∼2000 ka) dunes. Vegetation changed markedly along the climosequence, from shrubland at the driest site to Eucalyptus forest at the wettest. The carbonate and P content of the parent sand declined along the climosequence, presumably linked to variation in offshore productivity. However, soil development and associated nutrient status followed remarkably consistent patterns along the four chronosequences. Pedogenesis involved decalcification and secondary carbonate precipitation in Holocene soils and leaching of iron oxides from Middle Pleistocene soils, ultimately yielding bleached quartz sands on the oldest soils. Along all chronosequences soil pH and total P declined, while C:P and N:P ratios increased, consistent with the predicted shift from N to P limitation of vegetation during ecosystem development. The expected unimodal pattern of leaf area index was most pronounced along wetter chronosequences, suggesting an influence of climate on the expression of retrogression. The four chronosequences do not appear to span a pedogenic climate threshold, because exchangeable phosphate and base cations declined consistently during long-term pedogenesis. However, the proportion of the total P in organic form was greater along wetter chronosequences. We conclude that soils and nutrient availability on the coastal sand plains of southwestern Australia change consistently during long-term pedogenesis, despite marked variation in modern vegetation and climate. The four chronosequences provide a rare soil-age × climate framework within which to study long-term ecosystem development.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".