Climate risk continues to exacerbate the challenges facing resource constrained farmers in the global South. Smallholder farmers in the global south face the greatest risk from climate variability and change given their socio-economic status. Food security and livelihoods are therefore threatened as most staple food crops are susceptible to climate risks. Notable work has been undertaken on climate variability and change management in the global South. There is however need to prioritize research on low-cost climate variability and change management strategies for effective and sustainable climate risk management and mitigation. These are potentially suitable for resource constrained farming systems. Realization of climate change management strategies with additional mitigation benefits would also contribute to reduction of greenhouse gases. Evaluation of climate variability and change strategies is complex and risky to undertake using only field trials. Modeling approaches such as crop, machine learning and statistical models provide relatively quicker and feasible methods for ex-ante analysis of climate change and variability management strategies. Use of such tools has been made feasible through the availability of the ever-increasing body of literature and data from on-station, on-farm and survey research. This also allows for ex-ante assessment of the climate variability and change strategies.
The research topic will bring together learnings from the global south on the various low-cost strategies that are available to increase climate risk adaptation and mitigation. Aggregated learnings from the same region on the same challenge will lead to streamlining of the climate risk management strategies in the region and peer-to-peer learning on best practices. The major problem sought to be addressed is the inability of farmers to cope and adapt to the climate change variability and change impacts currently being experienced in the global south. Such inability has led to recurrent low crop yields which has led to food insecurity and loss of livelihood. Farmers in the global south are characterized by resource constraints. The research therefore seeks to identify the most feasible low-cost strategies to manage climate variability. Research has been under undertaken in the global south on a range of climate variability and change management and mitigation practices. There is however need to streamline such research to improve targeting of resource constrained farmers who are the major beneficiaries of such research.
The topic targets research dwelling on crop modelling, socio-economic modelling, machine learning modelling and big data analysis components. The topic covers themes related to climate risk, climate variability, climate change, greenhouse gas mitigation, climate variability and change adaptation. Geographically the research topic covers countries in the global South but from researchers anywhere on the globe. The research topic also covers food crops.
For this research topic we invite research and review-based manuscripts.
Research topic themes:
- Use crop models to determine the most appropriate crop management practices under certain weather and climate conditions
- Integration of crop models and weather and climate data to enhance decision making
- Use of machine learning algorithms for yield prediction
- Climate impacts on growth and development of staple food crops
- Modelling approaches to enhance greenhouse gas mitigation
- Reducing climate risk in smallholder farming systems
- Big data analysis of large-scale legacy data sets to enhance decision making in climate change adaptation and mitigation
Climate risk continues to exacerbate the challenges facing resource constrained farmers in the global South. Smallholder farmers in the global south face the greatest risk from climate variability and change given their socio-economic status. Food security and livelihoods are therefore threatened as most staple food crops are susceptible to climate risks. Notable work has been undertaken on climate variability and change management in the global South. There is however need to prioritize research on low-cost climate variability and change management strategies for effective and sustainable climate risk management and mitigation. These are potentially suitable for resource constrained farming systems. Realization of climate change management strategies with additional mitigation benefits would also contribute to reduction of greenhouse gases. Evaluation of climate variability and change strategies is complex and risky to undertake using only field trials. Modeling approaches such as crop, machine learning and statistical models provide relatively quicker and feasible methods for ex-ante analysis of climate change and variability management strategies. Use of such tools has been made feasible through the availability of the ever-increasing body of literature and data from on-station, on-farm and survey research. This also allows for ex-ante assessment of the climate variability and change strategies.
The research topic will bring together learnings from the global south on the various low-cost strategies that are available to increase climate risk adaptation and mitigation. Aggregated learnings from the same region on the same challenge will lead to streamlining of the climate risk management strategies in the region and peer-to-peer learning on best practices. The major problem sought to be addressed is the inability of farmers to cope and adapt to the climate change variability and change impacts currently being experienced in the global south. Such inability has led to recurrent low crop yields which has led to food insecurity and loss of livelihood. Farmers in the global south are characterized by resource constraints. The research therefore seeks to identify the most feasible low-cost strategies to manage climate variability. Research has been under undertaken in the global south on a range of climate variability and change management and mitigation practices. There is however need to streamline such research to improve targeting of resource constrained farmers who are the major beneficiaries of such research.
The topic targets research dwelling on crop modelling, socio-economic modelling, machine learning modelling and big data analysis components. The topic covers themes related to climate risk, climate variability, climate change, greenhouse gas mitigation, climate variability and change adaptation. Geographically the research topic covers countries in the global South but from researchers anywhere on the globe. The research topic also covers food crops.
For this research topic we invite research and review-based manuscripts.
Research topic themes:
- Use crop models to determine the most appropriate crop management practices under certain weather and climate conditions
- Integration of crop models and weather and climate data to enhance decision making
- Use of machine learning algorithms for yield prediction
- Climate impacts on growth and development of staple food crops
- Modelling approaches to enhance greenhouse gas mitigation
- Reducing climate risk in smallholder farming systems
- Big data analysis of large-scale legacy data sets to enhance decision making in climate change adaptation and mitigation
