Evidence for biocycling from Ba/Ca, Sr/Ca, and 87Sr/86Sr in soils (Red Brown Earths) from South Australia
Bibliographic record
Abstract
The impact of elemental cycling and biological fractionation in the soil–vegetation system was investigated for 6 Red Brown Earth soil profiles (Xeralfs and Xerults) from South Australia by comparing geochemical and 87Sr/86Sr data from bulk soils, soil exchange pool, and vegetation (grapes). In all 6 soil profiles from 3 different sites, Ba/Ca ratios of vegetation, soil exchange pool, and bulk soils were found to be a more robust biological fractionation indicator than Sr/Ca ratios. In the base-poor soils of the Coonawarra–Padthaway area of South Australia, the degree of weathering of soil material, as estimated by titania and alumina contents, correlated very well with the biological fractionation indicator Ba/Ca. Soil horizons with greater clay and titania content also had higher degrees of biological fractionation. Similar Red Brown Earth soils 400 km north in the Clare Valley showed either no, or poor, biological fractionation signature in their bulk soil. The Clare Valley soils have a stronger colluvial component and are richer in base cations than the Coonawarra and Padthaway sites. The main source of bulk soil material in the base-poor soils of the Coonawarra–Padthaway areas is dust, which has greatly influenced the base cation concentration, Ba/Ca ratios, and the strontium isotope ratios. Soils from Clare Valley, by comparison, are less intensely weathered and are thus not as dependent on dust and biocycling for their base cations. Biological fractionation has not left a discernible signature on the composition of the bulk soil. The exchange pools at all 3 sites are dominated by wetfall–dryfall sources, which in this coastal area are dominated by marine sources. For the base-poor soils of the Coonawarra–Padthaway area, the most likely major source of aeolian detritus is Murray River mud. The fine-grained component of this mud, with its organic matter content, relatively high base cation concentrations, and low strontium isotope ratios (Douglas et al. 1995) appears to have overwhelmed other dust sources and caused a homogenisation of the geochemical signature of fine-grained bulk soils in this area. Subsequent in situ weathering and neoformation following dust deposition were strongly influenced by exchange phase concentrations and ratios and resulted in an enhanced biological fractionation signature of the soils.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".