Identifying hotspots for gender-focused climate-smart interventions
In a recently published paper, "Woman in agriculture, and climate risks: hotspots for development," by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), "hotspots" for climate risks and women in agriculture have been identified. The intention of the study is to inform policy makers and development practitioners on which geographic regions should be prioritized, based on necessity, for implementing climate change adaptation measures for female farmers.
Definitions: what are hotspots?
Hotspots are defined in the study as regions with high concentrations of women farmers impacted by a high degree of climatic risk. Central to the study was the creation of a methodology for identification of hotspots. The study illustrates the results for India, outlining the major socio-economic constraints faced by women farmers in identified hotspots. A systematic literature review was also carried out in order to highlight the results of studies conducted outside of these hotspots.
Methodology: how to find a hotspot
"Women in agriculture" is defined in the study as the "absolute number of females whose major economic activity is working in agriculture as either a cultivator or a labourer." Using the district (an administrative division of an Indian state or territory) as the unit, the number of women in agriculture was obtained by compiling rural-level data on female cultivators and labourers in agriculture.
Drought, extreme rainfall and heat waves, all of which have a substantial negative impact on major crops, are the three types of climatic risks that were mapped using gridded data from the Indian Meteorological Department. Using a geographic information system (GIS), hotspots were identified by overlaying female participation with climate risks. Jenk’s natural break classification was used to classify the data for these two parameters into five different categories (very low, low, medium, high, and very high). The intersections of "high" and "very high" classes for the parameters in the overlay analysis indicated districts where the largest populations of women in agriculture are impacted by higher degrees of climate risks, i.e. the hotspots.
By IAMNOTUNIQUE