Metals Accumulation in grey mangrove (Avicennia marina (Forsk.) Vierh.) inhabiting Tarut Bay, Eastern Saudi Arabia
Bibliographic record
Abstract
Mangrove forests are of special interest because of their metal accumulation potenials as they occur in environments characterized by an excess of toxic ions. In this current study, we investigated the accumulation capacity of (Avicennia marina), a dominant mangrove plant inhabiting Tarut Bay in Eastern Saudi Arabia. Samples comprising mangroves, water and soil from 10 locations of Tarut Bay were analyzed for 8 heavy metals including Boron, Iron, Manganese, Zink, Lead, Nickel, Cadimum and Cupper. In water samples, B (5.5 PPM) was the highest while Cd was absent, also soil samples contained higher B (27.2 PPM), while Cd was lacking in these samples too. Overall, the concentrations of heavy metals were higher in plant shoot as compared to water and soil samples. In plant shoot Cu level was highest (107.22 PPM), while Cd was the lowest in. Our results demonstrate that grey mangrove absorb and accumulate higher quantities of heavy metals and thus play a vital role via cleansing the coastal environment from such harmful heavy metals. Our findings asserted that grey mangrove is a promising candidate for the purpose of Phytostabilization of industrially polluted coastal shores.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".