Complex pattern of genetic structuring in the Atlantic salmon (Salmo salar L.) of the River Foyle system in northwest Ireland: disentangling the evolutionary signal from population stochasticity

Little is known about the microevolutionary processes shaping within river population genetic structure of aquatic organisms characterized by high levels of homing and spawning site fidelity. Using a microsatellite panel, we observed complex and highly significant levels of intrariver population genetic substructure and Isolation-by-Distance, in the Atlantic salmon stock of a large river system. Two evolutionary models have been considered explaining mechanisms promoting genetic substructuring in Atlantic salmon, the member-vagrant and metapopulation models. We show that both models can be simultaneously used to explain patterns and levels of population structuring within the Foyle system. We show that anthropogenic factors have had a large influence on contemporary population structure observed. In an analytical development, we found that the frequently used estimator of genetic differentiation, F-ST, routinely underestimated genetic differentiation by a factor three to four compared to the equivalent statistic Jost's D-est (Jost 2008). These statistics also showed a near-perfect correlation. Despite ongoing discussions regarding the usefulness of "adjusted" F-ST statistics, we argue that these could be useful to identify and quantify qualitative differences between populations, which are important from management and conservation perspectives as an indicator of existence of biologically significant variation among tributary populations or a warning of critical environmental damage.

Knowledge, innovation and emulation in the evolutionary thought of Bernard Mandeville

Of the early modern writers on the division of labour, Bernard Mandeville alone extended it to all aspects of human activity and emphasised its role in a cumulative process of evolution in which each generation modified and built on what had been achieved by earlier generations. This required exploration of the mechanisms through which new knowledge was developed as well as the means by which knowledge was transmitted between the generations. The present article examines Mandeville’s treatment of these mechanisms and explores their theoretical origins. It examines Mandeville’s understanding of the role of the division of labour in facilitating discovery and learning and the role of education and imitation in transmitting social knowledge. It shows that, for Mandeville, innovators were people of ordinary capacity who were alert to the opportunities and challenges of their environment. As a result of specialisation, they possessed tacit knowledge which was actualised in what they did rather than in theoretical propositions. Mandeville’s evolutionary thought influenced subsequent writers on political economy and evolutionary social thinkers. It may also have had some influence on Charles Darwin, though it is not, in itself, Darwinian. © The Author 2013. Published by Oxford University Press on behalf of the Cambridge Political Economy Society. All rights reserved.

Restrospective genetic monitoring of the threatened Yellow marsh saxifrage (Saxifraga hirculus) reveals genetic erosion but provides valuable information for conservation strategies

Aim: Retrospective genetic monitoring, comparing genetic diversity of extant populations with historical samples, can provide valuable and often unique insights into evolutionary processes informing conservation strategies. The Yellow marsh saxifrage (Saxifraga hirculus) is listed as ‘critically endangered’ in Ireland with only two extant populations. We quantified genetic changes over time and identified genotypes in extant populations that could be used as founders for reintroductions to sites where the species is extinct.

Location: Ireland.

Methods: Samples were obtained from both locations where the species is currently found, including the most threatened site at the Garron Plateau, Co. Antrim, which held only 13 individuals during 2011. Herbarium samples covering the period from 1886 to 1957 were obtained including plants from the same area as the most threatened population, as well as three extinct populations. In total, 422 individuals (319 present-day and 103 historical) were genotyped at six microsatellite loci. Species distribution modelling was used to identify areas of potentially suitable habitat for reintroductions.

Results: Level of phenotypic diversity within the most threatened population was significantly lower in the present-day compared with historical samples but levels of observed heterozygosity and number of alleles, whilst reduced, did not differ significantly. However, Bayesian clustering analysis suggested gradual lineage replacement over time. All three measures of genetic diversity were generally lower at the most threatened population compared with the more substantial extant populations in Co. Mayo. Species distribution modelling suggested that habitat at one site where the species is extinct may be suitable for reintroduction.

Main conclusions: The dominant genetic lineage in the most threatened population is rare elsewhere; thus, care needs to be taken when formulating any potential reintroduction programme. Our findings highlight both the need for genetic monitoring of threatened populations, but also for its swift implementation before levels of diversity become critically low.

An application of bi-directional evolutionary structural optimisation for optimising energy absorbing structures using a material damage model

The Bi-directional Evolutionary Structural Optimisation (BESO) method is a numerical topology optimisation method developed for use in finite element analysis. This paper presents a particular application of the BESO method to optimise the energy absorbing capability of metallic structures. The optimisation objective is to evolve a structural geometry of minimum mass while ensuring that the kinetic energy of an impacting projectile is reduced to a level which prevents perforation. Individual elements in a finite element mesh are deleted when a prescribed damage criterion is exceeded. An energy absorbing structure subjected to projectile impact will fail once the level of damage results in a critical perforation size. It is therefore necessary to constrain an optimisation algorithm from producing such candidate solutions. An algorithm to detect perforation was implemented within a BESO framework which incorporated a ductile material damage model.