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Record W4414926894 · doi:10.1016/j.gexplo.2025.107914

Native plant species screening for phytogeochemical exploration in the Zambian Copperbelt

2025· article· en· W4414926894 on OpenAlexfundno aff
Pumulo Mukube, Stephen Syampungani, Lerato Machogo-Phao, Murray W. Hitzman

Bibliographic record

VenueJournal of Geochemical Exploration · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Biodiversity
Canadian institutionsnot available
FundersNational Science and Technology CouncilCopperbelt UniversityScience Foundation IrelandNational Research FoundationInternational Development Research CentreDepartment of Science and Innovation, South Africa
KeywordsTrace elementNative plantPopulationBiomass (ecology)Organic matterSoil waterPlant speciesSoil test

Abstract

fetched live from OpenAlex

Trace element analysis of plant tissues can aid mineral exploration for sediment hosted Cu-Co deposits in the Zambian Copperbelt (ZCB). This study was conducted at the Mitumba prospect, an area in the ZCB known to have copper minerals but no historical mining activities, to identify native plant species and their tissues that are most indicative of mineralized zones. Field inventory and ecological analysis identified 22 native plant species from 12 different families, of which Fabaceae (36.4%) was dominant. At species level and based on the coating index, we identified several predominant species, among them, Haumaniastrum katangense (Lamiaceae), Aframomum angustifolium (Zingiberaceae), Brachystegia boehmii (Fabaceae), and Diplorynchus condilocarpon (Apocynaceae). Sampling was undertaken of soils and plant organs above the known mineralized zone and at control points outside of the mineralized area. Most species translocated Cu from the roots to the aboveground biomass as indicated by translocation factors (TF) > 1 but only three species, namely, Haumaniastrum katangense , Aframomum angustifolium and Diplorynchus condilocarpon can both translocate and bioconcentrate (BCF > 1) bioavailable Cu from the rhizosphere, making them ideal candidates for phytogeochemical exploration. Only Haumaniastrum katangense and Aframomum angustifolium accumulated Co. Plant roots and leaves demonstrate significant Cu anomalism and show a wider population of anomalous values compared to the soils. Statistical and machine learning techniques both indicate significant relationships between soil Cu concentration and the content of Cu in plant roots and leaves highlighting soil pH, organic matter and clay content as the major physicochemical variables influencing metal bioavailability in soil-plant systems. • Trace element analysis of plant tissues can aid locating orebodies. • Haumaniastrum katangense, Aframomum angustifolium and Diploryhncus condilocarpon are copper indicators. • Haumanastrum katangense and Aframomum angustifolium also accumulate cobalt. • Machine learning algorithms effectively elucidate soil-plant relationships. • Soil pH, organic matter and clay content influences metal bioavailability.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.258

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.049
GPT teacher head0.262
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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