Spatiotemporal Response and Phytopotential of <i>Typha domingensis</i> for Management of Aquatic Metal Pollution on the Central African Copperbelt
Bibliographic record
Abstract
ABSTRACT Anthropogenically accelerated metal pollution of lotic systems draining mining landscapes remains a global concern due to its non‐degradability and ecotoxic nature. Nevertheless, the efficacy of macrophytes as indicators and remediators of metal(loid) pollutants in aquatic ecosystems in mining regions is recognised globally. However, in the mineral‐rich Central African Copperbelt (CACB), there is limited research on the effectiveness of macrophytes for mining pollution management. Therefore, this study investigated the phytopotential of Typha domingensis Pers. (Typhaceae), as a nature‐based approach for managing aquatic metal(loid) pollution on the CACB. A total of 252 samples each for sediment and T. domingensis were collected monthly between May 2022 and April 2023 from seven streams in the Kansanshi sub‐catchment of the CACB and analysed to evaluate the spatiotemporal variability of the phytoindication and phytoremediation potential of T. domingensis for As, Cu, Pb and Zn in stream sediments. Metal(loid)s in T. domingensis at 71% of the streams were predominantly accumulated in the below‐ground biomass with mean concentrations of 3–6 mg/kg As, 9–259 mg/kg Cu, 25–36 mg/kg Pb and 38–69 mg/kg Zn. The BAF was above 1 for As (0.8–2.6), Pb (10.7–24.3) and Zn (1.4–4.3), indicating T. domingensis as an accumulator of these elements but an excluder for Cu (BAF < 1). Additionally, TF was above 1 for As (1.5–2.0), Pb (1.4–1.5) and Zn (1.0–2.0), indicating the macrophyte's extraction efficacy. For Cu (TF < 1), the limited translocation characterised T. domingensis as a potential metal phytostabiliser. Similar seasonal trends for BAF and TF for As, Cu, Pb and Zn were also observed. Therefore, the spatiotemporal response of T. domingensis as a phytoindicator and phytoremediator of metal contaminants in sediments should be considered in the nature‐based management of CACB's aquatic ecosystems.
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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".