Local adaptation and species segregation in two mussel (Mytilus edulis X M. trossulus) hybrid zones

Few marine hybrid zones have been studied extensively, the major exception being the hybrid zone between the mussels Mytilus edulis and M. galloprovincialis in southwestern Europe. Here, we focus on two less studied hybrid zones that also involve Mytilus spp.; M. edulis and M. trossulus are sympatric and hybridize on both western and eastern coasts of the Atlantic Ocean. We review the dynamics of hybridization in these two hybrid zones and evaluate the role of local adaptation for maintaining species boundaries. In Scandinavia, hybridization and gene introgression is so extensive that no individuals with pure M. trossulus genotypes have been found. However, M. trossulus alleles are maintained at high frequencies in the extremely low salinity Baltic Sea for some allozyme genes. A synthesis of reciprocal transplantation experiments between different salinity regimes shows that unlinked Gpi and Pgm alleles change frequency following transplantation, such that post-transplantation allelic composition resembles native populations found in the same salinity. These experiments provide strong evidence for salinity adaptation at Gpi and Pgm (or genes linked to them). In the Canadian Maritimes, pure M. edulis and M. trossulus individuals are abundant, and limited data suggest that M. edulis predominates in low salinity and sheltered conditions, whereas M. trossulus are more abundant on the wave-exposed open coasts. We suggest that these conflicting patterns of species segregation are, in part, caused by local adaptation of Scandinavian M. trossulus to the extremely low salinity Baltic Sea environment.

A hybrid probabilistic criterion for market-based transmission expansion planning

Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.