scholarly journals Small grain production as an adaptive strategy to climate change in Mangwe District, Matabeleland South in Zimbabwe

Author(s):  
Tapiwa Muzerengi ◽  
Happy M. Tirivangasi

This article assesses the feasibility of small grains as an adaptive strategy to climate change in the Mangwe District in Zimbabwe. The change in climate has drastically affected rainfall patterns across the globe and in Zimbabwe in particular. Continuous prevalence of droughts in Zimbabwe, coupled with other economic calamities facing the Southern African country, has contributed to a larger extent to the reduction in grain production among communal farmers, most of whom are in semi-arid areas. This has caused a sudden increase in food shortages, particularly in the Mangwe District, as a result of erratic rainfall, which has negatively affected subsistence farming. This article was deeply rooted in qualitative research methodologies. Purposive sampling was used to sample the population. The researchers used key informant interviews, focus group discussions and secondary data to collect data. Data were analysed using INVIVO software, a data analysis tool that brings out themes. The results of the study are presented in the form of themes. The study established that small grains contributed significantly to addressing food shortages in the Mangwe District. The study results revealed that small grains were a reliable adaptive strategy to climate change as they increased food availability, accessibility, utilisation and stability. Despite the significant contribution of small grains to addressing food shortages, there is a need for the government to come up with a vibrant small grains policy, and government support that is visible as well as market creation for small grains. The study further recommends that small grains in semi-arid areas can be a panacea to food insecurity in Zimbabwe.

Author(s):  
Daniel Pabón-Caicedo José ◽  
Carlos Alarcón-Hincapié Juan
Keyword(s):  

2020 ◽  
Author(s):  
YaoJie Yue ◽  
Min Li

<p>Desertification, as one of the gravest ecological and environmental problems in the world, is affected both by climate change and human activities. As the consequences of global warming, the temperature in global arid and semi-arid areas is expected to increase by 1-3℃ by the end of this century. This change will significantly influence the spatial and temporal pattern of temperature, precipitation and wind speed in global arid and semi-arid areas, and in turn, ultimately impact the processing of desertification. Although current studies point out that future climate change tends to increase the risk of desertification. However, the future global or regional desertification risk under different climate change scenarios hasn’t been quantitively assessed. In this paper, we focused on this question by building a new model to evaluate this risk of desertification under an extreme climate change scenario, i.e. RCP8.5 (Representative Concentration Pathways, RCPs). We selected the northern agro-pastoral ecotone in China as the study area, where is highly sensitive to desertification. Firstly, the risk indicators of desertification were chosen in both natural and anthropic aspects, such as temperature, precipitation, wind speed, evaporation, and population. Secondly, the decision tree C5.0 algorithm of the machine learning technique was used to construct the quantitative evaluation model of land desertification risk based on the database of the 1:100,000 desertification map in China. Thirdly, with the support of the simulated meteorological data by General Circulation Models of HadGEM2-ES, the risk of desertification in the agro-pastoral ecotone in the north China under the RCP 8.5 scenario and SSP3 scenario (Shared Socioeconomic Pathways, SSPs) were predicted. The results show that the overall accuracy of the C5.0-based quantitative evaluation model for desertification risk is up to 83.32%, indicating that the C5.0 can better distinguish the risk of desertification according to the status of desertification impacting factors. Under the influence of future climate change, the agro-pastoral ecotone in northern China was estimated to be dominated by mild desertification risk, covering an area of more than 70%. Severe and moderate desertification risk is mainly distributed in the vicinity of Hulunbuir sandy land in the northeast of Inner Mongolia and the Horqin sandy land in the junction between Inner Mongolia, Jilin and Liaoning provinces. Compared with the datum period, the risk of desertification will decrease under the RCP8.5-SSP3 scenario. However, the desertification risk in Hulunbuir sandy land and that in the northwest of Jilin province will increase. The results of this study provide a scientific basis for developing more effective desertification control strategies to adapt to climate change in the agro-pastoral ecotone in north China. More importantly, it shows that the desertification risk can be predicted under the different climate change scenarios, which will help us to make a better understanding of the potential trend of desertification in the future, especially when the earth is getting warmer.</p>


2020 ◽  
Author(s):  
Debrah Onyango ◽  
Hezron Mogaka ◽  
Samuel Njiri Ndirangu ◽  
Kwena Kizito

This work covers the dissemination of climate change adaptation information in arid and semi-arid regions of Kenya with the aim of improving the adaptive capacity of smallholder farmers through dissemination of well package technologies referred to as agro-advisories.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fatemeh Hateffard ◽  
Safwan Mohammed ◽  
Karam Alsafadi ◽  
Glory O. Enaruvbe ◽  
Ahmad Heidari ◽  
...  

AbstractSoil erosion (SE) and climate change are closely related to environmental challenges that influence human wellbeing. However, the potential impacts of both processes in semi-arid areas are difficult to be predicted because of atmospheric variations and non-sustainable land use management. Thus, models can be employed to estimate the potential effects of different climatic scenarios on environmental and human interactions. In this research, we present a novel study where changes in soil erosion by water in the central part of Iran under current and future climate scenarios are analyzed using the Climate Model Intercomparison Project-5 (CMIP5) under three Representative Concentration Pathway-RCP 2.6, 4.5 and 8.5 scenarios. Results showed that the estimated annual rate of SE in the study area in 2005, 2010, 2015 and 2019 averaged approximately 12.8 t ha−1 y−1. The rangeland areas registered the highest soil erosion values, especially in RCP2.6 and RCP8.5 for 2070 with overall values of 4.25 t ha−1 y−1 and 4.1 t ha−1 y−1, respectively. They were followed by agriculture fields with 1.31 t ha−1 y−1 and 1.33 t ha−1 y−1. The lowest results were located in the residential areas with 0.61 t ha−1 y−1 and 0.63 t ha−1 y−1 in RCP2.6 and RCP8.5 for 2070, respectively. In contrast, RCP4.5 showed that the total soil erosion could experience a decrease in rangelands by − 0.24 t ha−1 y−1 (2050), and − 0.18 t ha−1 y−1 (2070) or a slight increase in the other land uses. We conclude that this study provides new insights for policymakers and stakeholders to develop appropriate strategies to achieve sustainable land resources planning in semi-arid areas that could be affected by future and unforeseen climate change scenarios.


2020 ◽  
Author(s):  
Debrah Onyango ◽  
Hezron Mogaka ◽  
Samuel Njiri Ndirangu ◽  
Kwena Kizito

This work covers the dissemination of climate change adaptation information in arid and semi-arid regions of Kenya with the aim of improving the adaptive capacity of smallholder farmers through dissemination of well package technologies referred to as agro-advisories.


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