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The increasing use of multi-member climate model ensembles for making future climate impact assessments presents both opportunities for understanding uncertainties, and challenges for interpreting the results. We outline current approaches to assessing uncertainties in climate impacts, statistical methods for assessing uncertainties, issues regarding model integration and complexity, and ways in which uncertainty frameworks can be used to inform adaptation decisions, with case studies focused on agriculture. Finally, we highlight future research needs and provide recommendations for making further progress.

We developed a system for amperometric detection of Escherichia coli (E. coli) based on the integration of microelectromechanical systems (MEMS), self-assembled monolayers (SAMS), DNA hybridization, and enzyme amplification. Using MEMS technology, a detector array was fabricated which has multiple electrodes deposited on a Si wafer and was fully reusable. Using SAMs, a monolayer of the protein streptavidin was immobilized on the working electrode (Au) surface to capture rRNA from E. coli. Three different approaches can be used to immobilize streptavidin onto Au, direct adsorption of the protein on bare Au, binding the protein to a biotinylated thiol SAM on Au, and binding the protein to a biotinylated disulfide monolayer on Au. The biotinylated thiol approach yielded the best results. High specificity for E. coli was achieved using ssDNA-rRNA hybridization and high sensitivity was achieved using enzymatic amplification with peroxidase as the enzyme. The analysis protocol can be conducted with solution volumes on the order of a few microliters and completed in 40 min. The detection system was capable of detecting 1000 E. coli cells without polymerase chain reaction with high specificity for E. coli vs. the bacteria Bordetella bronchiseptica.