This study assessed and classified the phytoremediation potentials of selected plant species around gold mining areas in restoring the environments contaminated by heavy metals. The geographic focuses of the study were the Golden Pride Gold Mine (GPGM) and Geita Gold Mine (GGM) in Tanzania. The shoots and roots of plant species surrounding the mining areas and the samples of associated soils were collected and analysed for total concentrations of lead (Pb), chromium (Cr), cadmium (Cd), copper (Cu), arsenic (As), manganese (Mn) and nickel (Ni) using Atomic Absorption Spectrophotometer (AAS) and UV-VIS spectrophotometry. Results indicated that the soils from study areas were loamy textured and slightly acid (pH 6.1-6.5), soil organic carbon and organic matter were low (0.6-2.0%), total nitrogen was very low (<0.10%), phosphorous ranged from low (6-12 mg kg À1 soil) to high (13-25 mg kg À1 soil), and cation exchange capacity ranged from low (6.0-12.0 cmol (þ) kg À1 soil) to medium (12.1-25.0 cmol (þ) kg À1 soil). In assessing heavy metals using plant parts, the roots of giant rats-tail grass (Sporobolus pyramidalis) accumulated highest Pb (757.78 μg g À1 ), Creeping Blepharis (Blepharis maderaspatensis) the Cd (158.11 μg g À1 ), lantana (Lantana camara) the As (68.61 μg g À1 ), and leuceana (Leucaena leucocephala) accumulated higher Mn (2734.61 μg g À1 ) and Ni (4464.33 μg g À1 ). In shoots, L. leucocephala accumulated higher Cr (1276.67 μg g À1 ) and higher Cu (2744.44 μg g À1 ) in L. camara. Although S. pyramidalis, M. repens, L. camara, B. maderaspatensis and L. leucocephala are likely to pose hazards to herbivores (grazing animals) while entering the food chain, they are still potential hyperaccumulators thus can be used to decontaminate metalliferous affected soils. Blepharis maderaspatensis has never been reported anywhere as Pb, Cd, Cu, Mn and Ni uptake plant hence this can be regarded as a new finding.

This study monitored land cover change in the mining sites of Golden Pride Gold Mine (GPGM) and Geita Gold Mine (GGM), Tanzania. The satellite data for land cover classification for the years 1997, 2010 and 2017 were obtained from the United States Geologic Survey Departments (USGS) online database and were analyzed using Arc GIS 10 software. Supervised classification composed of seven classes namely forest, bushland, agriculture, water, bare soil, urban area and grassland, was designed for this study, in order to classify Landsat images into thematic maps. In addition, future land cover changes for the year 2027 were simulated using a Cellular Automata (CA)-Markov model after validating the model using the Land Cover for the year 2017. The results from the LULC analysis showed that forest was the most dominant land cover type in 1997 at GPGM and GGM covering 510 ha (52.1%) and 9833 ha (49.7%) respectively. In 2017, the forest area decreased and the bushland replaced forest to be the most dominant land cover type covering 219 ha (22.4%) for GPGM and 8878 ha (44.9%) for GGM. Based on the CA-Markov model, a predicted land cover map for 2027 was dominated by forest covering 340 ha (34.7%) and 8639 ha (43.7%) for GPGM and GGM respectively. An overall accuracy and kappa coefficient for GPGM were 74.7% and 70.2% respectively and for GGM were 71.4% and 66.1% respectively. Thus, land cover changes resulting from mining activities involve reduction of forest land hence endangers biodiversity. GIS and remote sensing technologies are potential to detect the trend of changes and predict future land cover. The findings are crucial as it provides basis for land use planning and intensifies monitoring programs in the mining areas of

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Seasonal variations in proteins, vitamin A, vitamin C, carbohydrates and minerals (Ca, Fe, Na, K and P) for seven most grazed and four most browsed plant species were assessed using laboratory analysis to determine what nutrient resources were available to grazers and browsers inhabiting the Saanane Island. The results indicated great seasonal variations in proteins, vitamin A, vitamin C and carbohydrates which were statistically significant with P < 0.01, F 3.444 at DF 5. Similarly, the minerals (Ca, Fe, Na, K and P) showed greater seasonal variations with K and P being higher during wet season, while Na and Fe were higher in dry season. The levels of proteins, vitamins, fibres and minerals were well above daily dietary requirements for grazers and browsers. These results suggested that both grazers and browsers were benefiting from seasonal differences in terms of available resources at disposal as animal health is regulated by levels of proteins and vitamins available in grazing and browsing materials.  Keywords: Forage Quality, Minerals, Protein Saanane, Seasonality, Vitamin.