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A biological invasion is a form of biological pollution that is most likely more terrible than chemical pollution. Xanthium spinosum is one of the most invasive alien plant species. However, its abundance and impacts on invaded plant communities have not yet thoroughly studied. This study aimed to investigate the abundance and impacts of X. spinosum on invaded plant communities in the North Shewa Zone, Ethiopia. The study applied the quadrat method, sampling 80 main plots within 1 m2. Differences in mean cover-abundances of X. spinosum across various land types were compared using one-way-ANOVA followed by Tukey’s Honestly Significant Difference (HSD) Test. The results showed that roadsides and flooded areas exhibited the maximum mean cover-abundance of X. spinosum compared to farmland and rangeland. The number of plant species recorded was 106 in the control areas, compared to only 73 in the invaded areas. Hence, the number of plant species decreased by 31.13% in the infested area compared to the control. Thus, X. spinosum was among the factors contributing to the reduction of plant diversity, affecting the sustainability of biodiversity in the study areas. Therefore, implementing management measures against the spread of X. spinosum is to address the ongoing threat to biodiversity. [ABSTRACT FROM AUTHOR]

The dry lowlands of Ethiopia are seasonally affected by long periods of low rainfall and, coinciding with rainfall in the Amhara highlands, flood waters which flow onto the lowlands resulting in damage to landscapes and settlements. In an attempt to convert water from storm generated floods into productive use, this study proposes a methodology using remote sensing data and geographical information system tools to identify potential sites where flood spreading weirs may be installed and farming systems developed which produce food and fodder for poor rural communities. First, land use land cover maps for the study area were developed using Landsat-8 and MODIS temporal data. Sentinel-1 data at 10 and 20 m resolution on a 12-day basis were then used to determine flood prone areas. Slope and drainage maps were derived from Shuttle RADAR Topography Mission Digital Elevation Model at 90 m spatial resolution. Accuracy assessment using ground survey data showed that overall accuracies (correctness) of the land use/land cover classes were 86% with kappa 0.82. Coinciding with rainfall in the uplands, March and April are the months with flood events in the short growing season (belg) and June, July and August have flood events during the major (meher) season. In the Afar region, there is potentially >0.55 m ha land available for development using seasonal flood waters from belg or meher seasons. During the 4 years of monitoring (2015–2018), a minimum of 142,000 and 172,000 ha of land were flooded in the belg and meher seasons, respectively. The dominant flooded areas were found in slope classes of <2% with spatial coverage varying across the districts. We concluded that Afar has a huge potential for flood-based technology implementation and recommend further investigation into the investments needed to support new socio-economic opportunities and implications for the local agro-pastoral communities. [ABSTRACT FROM AUTHOR]