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This study uses remote sensing and spatial modeling to quantify and analyze land-cover change in one of Cameroon's rich ornithological montane forest biomes, the Kilum/Ijim mountain forest and surrounding watersheds. Change trajectories are identified over the entire watershed for a thirty year period (1978–2008). The role of satellite imagery, biophysical variables, locational context, and household socioeconomics factors in driving land-cover change were assessed. Overall, the documented land cover changes increase provisioning services such as crops and cattle that are characteristic some of the cultural landscapes in the area but may cause an irreversible loss of biodiversity and a depletion of other ecological services provided by forests and shrublands. The explanatory variables of the spatial model suggests that land-cover change in the region is explained many variables including proximity to road and land suitability. The implications for conservation of this area and the need for territorial planning and adapted land-use strategies are discussed.

The analysis of water samples collected in rivers streams across the tea growing areas in Rwanda by using spectroscopy technique MS Instrument has clearly indicate the presence of heavy elements (Al, As, Ba, c, Ca, Cu, Fe, H+, K, Mg, Mn, N, P, S, Si, and Zn) in water samples. The highly concentrated are: Ca (37 - 54.9), C (31.5-36.4), S: 12.9-24.1, Mg: 8.5-14.1, N: 4-11 and K: 5.3-7.8. Those with medium concentration are Si: 3.4-5.4, Cu: 1.1-2.5, Mn: 0.7-1.5, Ba: 0.5-1.03, Fe: 0.6-1 and P: 0.6-0.8. And elements with low concentration are Zn: 0.3-0.76, H+: 0.4-0.66, Al: 0.4-0.6 and As: 0.02-0.5. The pH varies between 5.5- 6.7.Water is acidic and this acidity may be caused by the use of fertilizers and pesticides with high quantity of NPK + Mg. Here we proposed the method that can be applied in order to maintain the quality of drinking water.

In this paper, non timber forest products presence and abundance in the Central zone of Korup National Park (CKNP), South Western Cameroon, are assessed and mapped based on habitats that support them. Sampling was done to identify all potential product plant species in the study area, derive estimates of abundance and describe productive habitats. The results show that, for most of the species, occurrence is not uniformly distributed. The estimated probability of identifying a species rose from 23% to 44% over the range of abundances in the plot. Species with a relatively high abundance were medicinal plants especially Anchomanes difformes.Valuable commercial species such as Irvingia gabonensis and Dacryodes edulis were rare. Some soil variables (Sand, Organic carbon, Clay, etc.) influence their spatial distribution. While there is some clustering, the pattern may be due to random chance (General G Index = 0, Z score =-1.44 standard deviations). Sustainable management of these products is important, both for local livelihoods, and preserving many that are facing rapid depletion.