Indigenous astronomical knowledge based seasonal weather forecast: evidence from Borana Oromo pastoralists of Southern Ethiopia.

Indigenous knowledge is still widely used by communities around the world to overcome social-ecological challenges. Borana Oromo pastoralists of Southern Ethiopia have been searching for future weather phenomena using their indigenous knowledge. This study examines indigenous knowledge-based seasonal weather forecasts through using observable physical and temporal patterns of astronomic objects. Data were generated through using focus group discussion, experimental knowledgeable groups and direct observation in the year 2021. The finding reveals that Borana Oromo pastoralists commonly define physical and temporal outlooks of the Moon that are changed and/ or displayed periodically within a range of varying contexts. The observation of the Moon features have been offering sufficient lapse time in a more than/within ahead of a season/ and is relatively more accurate than the other traditional forecasting objects. The study showed that both temporal and spatial dimensions of the forecasting were actually happened in Ganna (March to May rainfall), Adolessa dry season (June to September) and Hgayya rainfall (October to November) seasons of 2021. This indigenous weather forecasting practices are still regularly used in every livelihood decision making process. However, this indigenous weather knowledge of Borana Oromo pastoralists of Southern Ethiopia is not yet mainstreamed in the formal institutional structures. Curtailments of mobility, severity of drought, weakening of traditional institution, leaving of traditional life style and death of the knowledgeable elders are the major factors that are challenging the potential effects of the indigenous weather forecasting indicators of the features of moon in the study area.

High aboveground carbon stock of African tropical montane forests.

Tropical forests store 40-50 per cent of terrestrial vegetation carbon1. However, spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests2. Owing to climatic and soil changes with increasing elevation3, AGC stocks are lower in tropical montane forests compared with lowland forests2. Here we assemble and analyse a dataset of structurally intact old-growth forests (AfriMont) spanning 44 montane sites in 12 African countries. We find that montane sites in the AfriMont plot network have a mean AGC stock of 149.4 megagrams of carbon per hectare (95% confidence interval 137.1-164.2), which is comparable to lowland forests in the African Tropical Rainforest Observation Network4 and about 70 per cent and 32 per cent higher than averages from plot networks in montane2,5,6 and lowland7 forests in the Neotropics, respectively. Notably, our results are two-thirds higher than the Intergovernmental Panel on Climate Change default values for these forests in Africa8. We find that the low stem density and high abundance of large trees of African lowland forests4 is mirrored in the montane forests sampled. This carbon store is endangered: we estimate that 0.8 million hectares of old-growth African montane forest have been lost since 2000. We provide country-specific montane forest AGC stock estimates modelled from our plot network to help to guide forest conservation and reforestation interventions. Our findings highlight the need for conserving these biodiverse9,10 and carbon-rich ecosystems.

Occurrence of heavy metal in water, soil, and plants in fields irrigated with industrial wastewater in Sabata town, Ethiopia.

Industrial wastes have been increasingly discharged into water and soil, and causing environmental pollution in Ethiopia. This study examined the occurrence of heavy metal in water, soil, and plants in fields irrigated with industrial wastewater in Sabata town, Ethiopia. The composite samples of soil, water, and vegetables were collected accordingly to determine the concentration of heavy metals (Cu, Pb, Zn, Mn, and Ni) in each system during dry and wet seasons. The concentration of heavy metal was assayed using atomic absorption spectrophotometry. The data were statistically analyzed using one-way ANOVA. The heavy metal concentration was decreased in the order of Pb > Mn > Ni > Cu > Zn, Mn > Ni > Pb > Cu > Zn, and Ni > Pb > Mn > Cu > Zn in the water, soil, and vegetables in the area respectively. The variation of levels of heavy metal in the water, soil, and vegetable might be because of the effect of heavy metal speciation and valence, industry types, vegetable types and tissues, and soil. The bioconcentration factor of heavy metals was higher than that one for copper, signifying the increased probability of health risk for those who are consuming vegetables grown in the area. Thus, the government should take this into account and devise mitigation strategies through the implementation of heavy metal removal systems from contaminated water and soil, waste management strategies of recycling, centralized or decentralized treatment plant, changing of industrial residual into biogas production, and awareness creation for the society.