An enhanced microsatellite map of diploid Fragaria

A total of 45 microsatellites (SSRs) were developed for mapping in Fragaria. They included 31 newly isolated codominant genomic SSRs from F. nubicola and a further 14 SSRs, derived from an expressed sequence tagged library (EST-SSRs) of the cultivated strawberry, F. × ananassa. These, and an additional 64 previously characterised but unmapped SSRs and EST-SSRs, were scored in the diploid Fragaria interspecific F2 mapping population (FV×FN) derived from a cross between F. vesca 815 and F. nubicola 601. The cosegregation data of these 109 SSRs, and of 73 previously mapped molecular markers, were used to elaborate an enhanced linkage map. The map is composed of 182 molecular markers (175 microsatellites, six gene specific markers and one sequence-characterised amplified region) and spans 424 cM over seven linkage groups. The average marker spacing is 2.3 cM/marker and the map now contains just eight gaps longer than 10 cM. The transferability of the new SSR markers to the cultivated strawberry was demonstrated using eight cultivars. Because of the transferable nature of these markers, the map produced will provide a useful reference framework for the development of linkage maps of the cultivated strawberry and for the development of other key resources for Fragaria such as a physical map. In addition, the map now provides a framework upon which to place transferable markers, such as genes of known function, for comparative mapping purposes within Rosaceae.

Exploring the spatial relations between soil physical properties and apparent electrical conductivity

Relations between the apparent electrical conductivity of the soil (ECa) and top- and sub-soil physical properties were examined for two arable fields in southern England (Crowmarsh Battle Farms and the Yattendon Estate). The spatial variation of ECa and the soil properties was explored geostatistically. The variogram ranges showed that ECa varied on a similar spatial scale to many of the soil physical properties in both fields. Several features in the map of kriged predictions of ECa were also evident in maps of the soil properties. In addition, the correlation coefficients showed a strong relation between ECa and several soil properties. A moving correlation analysis enabled differences in the relations between ECa and the soil properties to be examined within the fields. The results indicated that relations were inconsistent; they were stronger in some areas than others. A regression of ECa on the principal component scores of the leading components for both fields showed that the first two components accounted for a large proportion of the variance in ECa, whereas the others accounted for little or none. For Crowmarsh topsoil sand and clay, loss on ignition and volumetric water measured in the autumn had large correlations on the first component, and for Yattendon they were large for topsoil sand and clay, and autumn and spring volumetric water. The cross-variograms suggested strong coregionalization between ECa and several soil physical properties; in particular subsoil sand and silt at Crowmarsh, and subsoil sand and clay at Yattendon. The structural correlations from the linear model of coregionalization confirmed the strength of the relations between ECa and the subsoil properties. Nevertheless, no one property was consistently important for both fields. Although a map of ECa can indicate the general patterns of spatial variation in the soil, it is not a substitute for information on soil properties obtained by sampling and analysing the soil. Nevertheless, it could be used to guide further sampling. (c) 2005 Elsevier B.V. All rights reserved.

Deriving global flood hazard maps of fluvial floods through a physical model cascade

Global flood hazard maps can be used in the assessment of flood risk in a number of different applications, including (re)insurance and large scale flood preparedness. Such global hazard maps can be generated using large scale physically based models of rainfall-runoff and river routing, when used in conjunction with a number of post-processing methods. In this study, the European Centre for Medium Range Weather Forecasts (ECMWF) land surface model is coupled to ERA-Interim reanalysis meteorological forcing data, and resultant runoff is passed to a river routing algorithm which simulates floodplains and flood flow across the global land area. The global hazard map is based on a 30 yr (1979–2010) simulation period. A Gumbel distribution is fitted to the annual maxima flows to derive a number of flood return periods. The return periods are calculated initially for a 25×25 km grid, which is then reprojected onto a 1×1 km grid to derive maps of higher resolution and estimate flooded fractional area for the individual 25×25 km cells. Several global and regional maps of flood return periods ranging from 2 to 500 yr are presented. The results compare reasonably to a benchmark data set of global flood hazard. The developed methodology can be applied to other datasets on a global or regional scale.