Abstract:The Dabus Wetland complex in the highlands of Ethiopia is within the headwaters of the Nile Basin and is home to significant ecological communities and rare or endangered species. Its many interrelated wetland types undergo seasonal and longer-term changes due to weather and climate variations as well as anthropogenic land use such as grazing and burning. Mapping and monitoring of these wetlands has not been previously undertaken due primarily to their relative isolation and lack of resources. This study investigated the potential of remote sensing based classification for mapping the primary vegetation groups in the Dabus Wetlands using a combination of dry and wet season data, including optical (Landsat spectral bands and derived vegetation and wetness indices), radar (ALOS PALSAR L-band backscatter), and elevation (SRTM derived DEM and other terrain metrics) as inputs to the non-parametric Random Forest (RF) classifier. Eight wetland types and three terrestrial/upland classes were mapped using field samples of observed plant community composition and structure groupings as reference information. Various tests to compare results using different RF input parameters and data types were conducted. A combination of multispectral optical, radar and topographic variables provided the best overall classification accuracy, 94.4% and 92.9% for the dry and wet season, respectively. Spectral and topographic data (radar data excluded) performed nearly as well, while accuracies using only radar and topographic data were 82-89%. Relatively homogeneous classes such as Papyrus Swamps, Forested Wetland, and Wet Meadow yielded the highest accuracies while spatially complex classes such as Emergent Marsh were more difficult to accurately classify. The methods and results presented in this paper can serve as a basis for development of long-term mapping and monitoring of these and other non-forested wetlands in Ethiopia and other similar environmental settings.

Macrophytes play critical ecological role in inland water bodies, especially in shallow systems. Water hyacinth (Eichhornia crassipes) is an invasive plant species introduced to Ethiopian water bodies around the mid 20 th century with recently exacerbated devastating ecological and economic consequences. Here we report the impact of the invasive plant species on macrophyte species assemblage and biodiversity in Lake Abaya, southwestern Ethiopia. We compared four sites in Lake Abaya, two hyacinth infested and two non-infested, each site consisting of 15 plots. Our results showed that water hyacinth affects the macrophyte community composition, abundance and diversity negatively. Even though some macrophyte species from the Poaceae and Cyperaceae families appear to coexist with the alien plant, the invasive species has reduced macrophyte abundance and diversity at the infested sites, and in some cases changed the community to nearly monotypic flora. Our data affirm that water hyacinth has the potential to alter macrophyte composition, abundance and diversity in the wider Ethiopian aquatic ecosystems. A broad & closer, systematic and comprehensive look at the short and long term consequences of its expanding invasion within the framework of specific local environmental, ecological and societal conditions is long-overdue.

No abstract

No abstract