Review of The Science, Impacts and Monitoring of Drought in Western Canada: Proceedings of the 2004 Prairie Drought Workshop Edited by Dave Sauchyn, Madhav Khandekar, and E. Ray Garnett

Drought is not an unusual phenomenon on the Canadian prairies or the U.S. Great Plains. There were many short-term droughts in the prairies during the 20th century that generally lasted one to two years (e.g., 1961, 1988). The Canadian prairies multi-year drought event (1999-2003+) has been considered similar in severity to the 1930s drought years. The 2004 Prairie Drought Workshop resulted in 76 scientists and resource managers gathering in Calgary, Alberta, to share information on drought science, impacts, and monitoring. Presenters examined the impacts on agriculture, stream flow, forests, and ground water, including potential impacts under a changed climate. Though focused on the Canadian prairies, the information presented could be applied to many parts of the U.S. Great Plains.

Linkage & Selective Mapping and QTL Analysis in a Harosoy x Clark population of 300 RILs

Four of the 12 major Glycine max ancestors of all modern elite U.S.A. soybean cultivars were the grandparents of Harosoy and Clark, so a Harosoy x Clark population would include some of that genetic diversity. A mating of eight Harosoy and eight Clark plants generated eight F1 plants. The eight F1:2 families were advanced via a plant-to-row selfing method to produce 300 F6-derived RILs that were genotyped with 266 SSR, 481 SNP, and 4 classical markers. SNPs were genotyped with the Illumina 1536-SNP assay. Three linkage maps, SSR, SNP, and SSR-SNP, were constructed with a genotyping error of < 1 %. Each map was compared with the published soybean consensus map. The best subset of 94 RILs for a high-resolution framework (joint) map was selected based on the expected bin length statistic computed with MapPop. The QTLs of seven traits measured in a 2-year replicated performance trial of the 300 RILs were identified using composite interval mapping (CIM) and multiple-interval mapping (MIM). QTL x Year effects in multiple trait analysis were compared with results of multiple-interval mapping. QTL x QTL effects were identified in MIM.