Climate analogues: Finding tomorrow’s agriculture today

The analogues approach, developed by CCAFS in R programming, is a novel way of supporting climate and crop models with on-the-ground empirical testing. In essence, the analogues tool connects sites with statistically similar (‘analogous’) climates, across space (i.e. between locations) and/or time (i.e. with past or future climates). A CCAFS dissimilarity index or Hallegatte index can be used to systematically identify climate analogues across the world, for certain regions, or among specific locations. Users may use default criteria or choose from a variety of global climate models (GCMs), scenarios, and input data. Once analogue sites are identified, information gathered from local field studies or databases can be used and compared to provide data for further studies, propose high-potential adaptation pathways, facilitate farmer-to-farmer exchange of knowledge, validate computational models, test new technologies and/or techniques, or enable us to learn from history. Users may manipulate the tool in the free, open-source R software, or access a simplified user-friendly version online

Regional differences in awareness and attitudes regarding genetic testing for disease risk and ancestry

Little is known about the lay public’s awareness and attitudes concerning genetic testing and what factors influence their perspectives. The existing literature focuses mainly on ethnic and socioeconomic differences; however, here we focus on how awareness and attitudes regarding genetic testing differ by geographical regions in the US. We compared awareness and attitudes concerning genetic testing for disease risk and ancestry among 452 adults (41% Black and 67% female) in four major US cities, Norman, OK; Cincinnati, OH; Harlem, NY; and Washington, DC; prior to their participation in genetic ancestry testing. The OK participants reported more detail about their personal ancestries (p = 0.02) and valued ancestry testing over disease testing more than all other sites (p < 0.01). The NY participants were more likely than other sites to seek genetic testing for disease (p = 0.01) and to see benefit in finding out more about one’s ancestry (p = 0.02), while the DC participants reported reading and hearing more about genetic testing for African ancestry than all other sites (p < 0.01). These site differences were not better accounted for by sex, age, education, self-reported ethnicity, religion, or previous experience with genetic testing/counseling. Regional differences in awareness and attitudes transcend traditional demographic predictors, such as ethnicity, age and education. Local sociocultural factors, more than ethnicity and socioeconomic status, may influence the public’s awareness and belief systems, particularly with respect to genetics