Native plant species screening for phytogeochemical exploration in the Zambian Copperbelt

Abstract

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.

HIGHLIGHTS • 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.