Soil Phosphorus Speciation and Availability in Meadows and Forests in Alpine Lake Watersheds With Different Parent Materials
Bibliographic record
Abstract
In the Lake Tahoe Basin in California and Nevada (USA), managing nutrient export from watersheds into streams and the lake is a significant challenge that needs to be addressed to improve water quality. Leaching and runoff of phosphorus (P) from soils is a major nutrient source to the lake, and P loading potential from different watersheds varies as a function of landscape and ecosystem properties, and how the watershed is managed. In this research, P availability and speciation in forest and meadow soils in the Lake Tahoe Basin were measured at two watersheds with different parent material types. Soils developed on andesitic parent materials had approximately twice as much total P compared to those developed on granitic parent materials. Regardless of parent material, organic P was 79–92% of the total P in the meadow soils, and only 13–47% in the forest soils. Most of the soil organic P consisted of monoester P compounds, but a significant amount, especially in meadow soils, was diester P compounds (up to 30% of total extracted P). Water extractable P (WEP) concentrations were ~10 times greater in the granitic forest soils compared to the andesitic forest soils, which had more poorly crystalline aluminosilicates and iron oxides that retain P and thus restrict WEP export. In the meadow soils, microbial biomass P was approximately seven times greater than the forest soils, which may be an important sink for P leached from upland forests. Results show that ecosystem and parent material are important attributes that control P speciation and availability in the Lake Tahoe Basin, and that organic P compounds are a major component of the soil P and are available for leaching from the soils. These factors can be used to develop accurate predictions of P availability and more precise forest management practices to reduce P export into Lake Tahoe.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".