Dryland soil salinity and seasonal effects on leaf and xylem sap ecophysiological characteristics of native plant species
Bibliographic record
Abstract
The objective of this 3-year study was to investigate the relationships between soil salinity and ecophysiological responses of C3 and C4 native plant species around Lake Altham and Lake Coyrecup (both are salt lakes in Western Australia), and to evaluate their potential for use in the remediation of salt-affected soils. Three shrubs (Atriplex vesicaria, Tecticornia lepidosperma and T. indica) that grew in highly saline soil of average Na concentration greater than 300 mM had higher leaf δ13C and δ15N ratios. These species also had higher Na-to-K and Na-to-Ca ratios in both their leaves and stem xylem sap, indicating that these species accumulate high amounts of sodium in their tissues. In contrast, tree species Eucalyptus loxophleba, Casuarina obesa and Acacia acuminata grew in soil of average Na concentration of less than 100 mM and had lower values of δ15N, δ13C, Na content, and Na-to-K ratio in their leaves. These species also had lower xylem Na-to-K and Na-to-Ca ratios. Seasonal effects were observed in leaf total N content, leaf Na, xylem sap Na-to-K ratio and xylem sap Na-to-Ca ratio. Strong and significant positive correlations (r > 0.75; P < 0.01) were observed between soil Na concentration and ecophysiological responses, such as leaf Na contents, leaf δ15N, xylem sap Na, xylem Na-to-K ratio and xylem Na-to-Ca ratio. Overall, Atr. vesicaria, T. lepidosperma, T. indica and Santalum acuminatum are good candidates for remediation of highly saline 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 | 0.000 | 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) | 0.001 | 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".