Deicing Salts; Assessing Distribution, Ion Accumulation in Plants and the Response of Plants to Different Loading Rates and Salt Mixtures
Bibliographic record
Abstract
Deicing salts applied to mountain roads during winter periods provide safe driving conditions but these salts are eventually displaced to roadside areas where they can negatively impact soils, vegetation and water resources. The aim of this study was to confirm the linkage between deicing salt applications and salt accumulation in plants and salt accumulation in soils as a function of distance from roads. We also wantedto determine whether altering the deicing salt composition would lead to a more favorable plant response. In the Mt. Charleston area of southern Nevada, NaCl was applied by the State Department of Transportation in excess of 200 tons per State Highway during the winter prior to this study. Salts sampled with depth and distance from the roads at 15 locations revealed significantly higher salinity levels (p < 0.05) at the 1 m vs. 5 and 10 m distances, with electrical conductivities as high as 37 dSm-1. In Ponderosa pine, Na and Cl concentrations were found to be elevated in needles revealing visual damage, whereas K concentrations were found to be significantly lower in damaged tissue (p < 0.05), resulting in Na/K ratios as high as 300 to 1. In a companion study we investigated the physiological response of 2 year old seedlings of aspen, Gambel oak and Woods’ rose, to different salt loading rates comprised of different mixes of salts (MgSO4, CaCl2 or KCl) at different %NaCl composition (100, 90, 75 and 50%). As the MgSO4 in the salt mix increased, sulfate concentration increased in the leaves of oak (r = 0.73, p < 0.001), reflecting the shift from Cl to SO4 availability. The % SO4 in the leaves of oak revealed a strong linear relationship (r = 0.83 p < 0.001) with leaf weight at final harvest, as well as higher chlorophyll (spad) measurements relative to control (r = 0.89 p < 0.01) and an earlier breaking of dormancy (r = 0.65, p < 0.01), as seedlings with 2.5% SO4 in leaves at harvest broke dormancy 10 days sooner than those oak seedlings with only 1% SO4 in the tissue. Based on results of this study , we believe a 25% substitution of MgSO4 would be worthy of further field evaluations as a significant decline in leaf tissue Na andCl occurred at this level, while concentrations of Ca and SO4 increased.
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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 | 0.002 | 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 | 0.001 |
| 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".