Drivers and Implications of Land Use and Land Cover Change in the Central Highlands of Ethiopia: Evidence from Remote Sensing and Socio-demographic Data Integration

This study explores the major drivers of Land-use/Land-cover (LULC) dynamics and the observed   environmental degradation as a response to these changes in the Modjo watershed, central Ethiopia. Data for this study were generated through household survey and supplemented with remotely sensed image interpretation. The data were analyzed using descriptive statistics and remote sensing-based image  processing. The findings of the study revealed that LULC dynamics together with a range of ecological changes are serious environmental problems in the study site. LULC changes are driven by a combination of proximate and underlying drivers such as economic, demographic, biophysical and institutional factors. Bareland expansion, increased surface runoff production and soil erosion are major environmental damages partly attributed to LULC dynamics in the study site. These environmental degradation processes have adverse impacts on local agricultural productivity, water resource availability and food security of communities. Thus, policy responses are needed for integrated natural resource management and livelihood sustainability in the study area.Key words: Ethiopia, Land Use and Land Cover Change, Modjo Watershed, Remote Sensin

How gender- and violence-related norms affect self-esteem among adolescent refugee girls living in Ethiopia.

BACKGROUND: Evidence suggests adolescent self-esteem is influenced by beliefs of how individuals in their reference group perceive them. However, few studies examine how gender- and violence-related social norms affect self-esteem among refugee populations. This paper explores relationships between gender inequitable and victim-blaming social norms, personal attitudes, and self-esteem among adolescent girls participating in a life skills program in three Ethiopian refugee camps. METHODS: Ordinary least squares multivariable regression analysis was used to assess the associations between attitudes and social norms, and self-esteem. Key independent variables of interest included a scale measuring personal attitudes toward gender inequitable norms, a measure of perceived injunctive norms capturing how a girl believed her family and community would react if she was raped, and a peer-group measure of collective descriptive norms surrounding gender inequity. The key outcome variable, self-esteem, was measured using the Rosenberg self-esteem scale. RESULTS: Girl's personal attitudes toward gender inequitable norms were not significantly predictive of self-esteem at endline, when adjusting for other covariates. Collective peer norms surrounding the same gender inequitable statements were significantly predictive of self-esteem at endline (ß = -0.130; p  =  0.024). Additionally, perceived injunctive norms surrounding family and community-based sanctions for victims of forced sex were associated with a decline in self-esteem at endline (ß = -0.103; p  =  0.014). Significant findings for collective descriptive norms and injunctive norms remained when controlling for all three constructs simultaneously. CONCLUSIONS: Findings suggest shifting collective norms around gender inequity, particularly at the community and peer levels, may sustainably support the safety and well-being of adolescent girls in refugee settings

Properties of an alkali-thermo stable xylanase from Geobacillus thermodenitrificans A333 and applicability in xylooligosaccharides generation

An extracellular thermo-alkali-stable and cellulase-free xylanase from Geobacillus thermodenitrificans A333 was purified to homogeneity by ion exchange and size exclusion chromatography. Its molecular mass was 44 kDa as estimated in native and denaturing conditions by gel filtration and SDS-PAGE analysis, respectively. The xylanase (GtXyn) exhibited maximum activity at 70 °C and pH 7.5. It was stable over broad ranges of temperature and pH retaining 88 % of activity at 60 °C and up to 97 % in the pH range 7.5–10.0 after 24 h. Moreover, the enzyme was active up to 3.0 M sodium chloride concentration, exhibiting at that value 70 % residual activity after 1 h. The presence of other metal ions did not affect the activity with the sole exceptions of K+ that showed a stimulating effect, and Fe2+, Co2+ and Hg2+, which inhibited the enzyme. The xylanase was activated by non-ionic surfactants and was stable in organic solvents remaining fully active over 24 h of incubation in 40 % ethanol at 25 °C. Furthermore, the enzyme was resistant to most of the neutral and alkaline proteases tested. The enzyme was active only on xylan, showing no marked preference towards xylans from different origins. The hydrolysis of beechwood xylan and agriculture-based biomass materials yielded xylooligosaccharides with a polymerization degree ranging from 2 to 6 units and xylobiose and xylotriose as main products. These properties indicate G. thermodenitrificans A333 xylanase as a promising candidate for several biotechnological applications, such as xylooligosaccharides preparation

Soil erosion modelling: A bibliometric analysis

Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication\u27s CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper

Soil erosion modelling: A global review and statistical analysis

To gain a better understanding of the global application of soil erosion prediction models, we comprehensivelyreviewed relevant peer-reviewed research literature on soil-erosion modelling published between 1994 and2017. We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the re-gions within which models are primarily applied, (iii) the regions which remain unaddressed and why, and (iv)how frequently studies are conducted to validate/evaluate model outcomes relative to measured data. To per-form this task, we combined the collective knowledge of 67 soil-erosion scientists from 25 countries. Theresulting database, named‘Global Applications of Soil Erosion Modelling Tracker (GASEMT)’, includes 3030 indi-vidual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluatedand transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insightsinto the state-of-the-art of soil- erosion models and model applications worldwide. This database intends to sup-port the upcoming country-based United Nations global soil-erosion assessment in addition to helping to informsoil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is anopen-source database available to the entire user-community to develop research, rectify errors, andmakefutureexpansion