About this Research Topic
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
Keywords: Climate variability and change adaptation, crop modelling, machine learning, cropping systems, resource constrained farmers
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.