Genetic diversity within and between two wild and one farmed population of Atlantic salmon was estimated by 12 variable enzyme loci, three single locus‐ and one multilocus DNA minisatellite probe. The farmed salmon were fifth‐generation fish from one of the principal commercial strains in Norway and the wild salmon were from the rivers Numedalslågen and Tana, Norway. All three classes of markers detected significant differentiation between the populations, with the farmed population being genetically most divergent. The farmed fish showed less genetic variability than the wild populations, as all techniques revealed a lower (14%−45%) number of variable bands/alleles in this group. However, only multilocus DNA fingerprinting detected a significantly lower level of heterozygosity within the farmed population. Estimates of average heterozygosity within populations were almost identical for single locus and multilocus minisatellites (0.558 and 0.548, respectively), which were more than three times higher than for polymorphic allozymes (0.162). Estimates of interpopulation genetic differentiation, however, gave highly concordant results between the allozymes and minisatellites (Fstrange: 0.106‐0.135). Our results show that fifth generation farmed Atlantic salmon differ significantly from wild salmon in loci others than those chosen for selection in the breeding program. The study also suggests that the choice of genetic markers for studies of Atlantic salmon depends on the aim of the study (within‐versus between‐population variability).
Volterra processes appear in several applications ranging from turbulence to energy finance where they are used in the modelling of e.g. temperatures and wind and the related financial derivatives. Volterra processes are in general non-semimartingales and a theory of integration with respect to such processes is in fact not standard. In this work we suggest to construct an approximating sequence of Lévy driven Volterra processes, by perturbation of the kernel function. In this way, one can obtain an approximating sequence of semimartingales.Then we consider fractional integration with respect to Volterra processes as integrators and we study the corresponding approximations of the fractional integrals. We illustrate the approach presenting the specific study of the Gamma-Volterra processes. Examples and illustrations via simulation are given.
The transboundary Georgia Basin Puget Sound ecosystem is situated in the southwest corner of British Columbia and northwest comer of Washington State. While bountiful and beautiful, this international region is facing significant threats to its marine and freshwater resources, air quality, habitats and species. These environmental challenges are compounded by rapid population growth and attendant uiban sprawl. As ecosystem stresses amplified and partnerships formed around possible solutions, it became increasingly clear that the shared sustainability challenges in the Georgia Basin and Puget Sound required shared solutions. Federal, state and provincial institutional arrangements were made between jurisdictions, which formalized small scale interest in transboundary management of this ecosystem. Formal agreements, however, can only do so much to further management of an ecosystem that spans international boarders. A transboundary regional research meeting, the 2003 GB/PS Research Conference, opened the doors for large-scale informal cross-boarder cooperation and management. In addition to cooperation, continued efforts to stem toxic pollution, contain urban growth, and protect and restore ecosystems, require a commitment from scientists, educators and policy makers to better integrate research and science with decision-making.
In an incomplete market driven by time-changed Lévy noises we consider the problem of hedging a financial position coupled with the underlying risk of model uncertainty. Then we study hedging under worst-case-scenario. The proposed strategies are not necessarily self-financing and include the interplay of a cost process to achieve the perfect hedge at the end of the time horizon. The hedging problem is tackled in the framework of stochastic differential games and it is treated via backward stochastic differential equations. Two different information flows are considered and the solutions compared.
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