Genomic consequences of mating system evolution in the Pacific coastal dune endemic, Abronia umbellata (Nyctaginaceae)

The advent of next-generation sequencing has significantly reduced the cost of obtaining large-scale genetic resources, opening the door for genomic studies of non-model but ecologically interesting species. The shift in mating system, from outcrossing to selfing, has occurred thousands of times in angiosperms and is accompanied by profound changes in the population genetics and ecology of a species. A large body of work has been devoted to understanding why the shift occurs and the impact of the shift on the genetics of the resulting selfing populations, however, the causes and consequences of the transition to selfing involve a complicated interaction of genetic and demographic factors which are difficult to untangle. Abronia umbellata is a Pacific coastal dune endemic which displays a striking shift in mating system across its geographic range, with large-flowered outcrossing populations south of San Francisco and small-flowered selfing populations to the north. Abronia umbellata is an attractive model system for the study of mating system transitions because the shift appears to be recent and therefore less obscured by post-shift processes, it has a near one-dimensional geographic range which simplifies analysis and interpretation, and demographic data has been collected for many of the populations. In this study, we generated transcriptome-level data for 12 plants including individuals from both subspecies, along with a resequencing study of 48 individuals from populations across the range. The genetic analysis revealed a recent transition to selfing involving a drastic reduction in genetic diversity in the selfing lineage, potentially indicative of a recent population bottleneck and a transition to selfing due to reproductive assurance. Interestingly, the genetic structure of the populations was not coincident with the current subspecies demarcation, and two large-flowered populations were classified with the selfing subspecies, suggesting a potential need for re-evaluation of the current subspecies classification. Our finding of low diversity in selfing populations may also have implications for the conservation value of the threatened selfing subspecies.

Numerical Modelling of Eddy Current Probes for CANDU® Fuel Channel Inspection

Multi-frequency Eddy Current (EC) inspection with a transmit-receive probe (two horizontally offset coils) is used to monitor the Pressure Tube (PT) to Calandria Tube (CT) gap of CANDU® fuel channels. Accurate gap measurements are crucial to ensure fitness of service; however, variations in probe liftoff, PT electrical resistivity, and PT wall thickness can generate systematic measurement errors. Validated mathematical models of the EC probe are very useful for data interpretation, and may improve the gap measurement under inspection conditions where these parameters vary. As a first step, exact solutions for the electromagnetic response of a transmit-receive coil pair situated above two parallel plates separated by an air gap were developed. This model was validated against experimental data with flat-plate samples. Finite element method models revealed that this geometrical approximation could not accurately match experimental data with real tubes, so analytical solutions for the probe in a double-walled pipe (the CANDU® fuel channel geometry) were generated using the Second-Order Vector Potential (SOVP) formalism. All electromagnetic coupling coefficients arising from the probe, and the layered conductors were determined and substituted into Kirchhoff’s circuit equations for the calculation of the pickup coil signal. The flat-plate model was used as a basis for an Inverse Algorithm (IA) to simultaneously extract the relevant experimental parameters from EC data. The IA was validated over a large range of second layer plate resistivities (1.7 to 174 µΩ∙cm), plate wall thickness (~1 to 4.9 mm), probe liftoff (~2 mm to 8 mm), and plate-to plate gap (~0 mm to 13 mm). The IA achieved a relative error of less than 6% for the extracted FP resistivity and an accuracy of ±0.1 mm for the LO measurement. The IA was able to achieve a plate gap measurement with an accuracy of less than ±0.7 mm error over a ~2.4 mm to 7.5 mm probe liftoff and ±0.3 mm at nominal liftoff (2.42±0.05 mm), providing confidence in the general validity of the algorithm. This demonstrates the potential of using an analytical model to extract variable parameters that may affect the gap measurement accuracy.