Territory choice during the breeding tenure of male sedge warblers

A territorial male can shift the location of its territory from year to year in order to increase its quality. The male can base its decision on environmental cues or else on its breeding experiences (when territory shift is caused by breeding failure in previous seasons). We tested these possible mechanisms of territory choice in the sedge warbler (Acrocephalus schoenobaenus), a territorial migrating passerine that occupies wetlands. This species bases its territory choices on an environmental cue: tall wetland vegetation cover. We found that the magnitude of territory quality improvement between seasons (measured as the area of tall wetland vegetation) increased throughout the early stages of a male's breeding career as a result of territory shifts dependent on the earliness of arrival. The distance the territory was shifted between seasons depended negatively on the previous year's territory quality and, less clearly, on the previous year's mating success. On the other hand, previous mating or nesting success had no influence on territory quality improvement between seasons as measured in terms of vegetation. The results imply that tall wetland vegetation is a long-term, effective environmental cue and that a preference for territories in which this type of landcover prevails has evolved into a rigid behavioral mechanism, supplemented by short-term individual experiences of breeding failure

Efficient Simulations of Large Scale Convective Heat Transfer Problems

We describe an approach for efficient solution of large scale convective heat transfer problems, formulated as coupled unsteady heat conduction and incompressible fluid flow equations. The original problem is discretized in time using classical implicit methods, while stabilized finite elements are used for space discretization. The algorithm employed for the discretization of the fluid flow problem uses Picard's iterations to solve the arising nonlinear equations. Both problems, heat transfer and Navier-Stokes quations, give rise to large sparse systems of linear equations. The systems are solved using iterative GMRES solver with suitable preconditioning. For the incompressible flow equations we employ a special preconditioner based on algebraic multigrid (AMG) technique. The paper presents algorithmic and implementation details of the solution procedure, which is suitably tuned, especially for ill conditioned systems arising from discretizations of incompressible Navier-Stokes equations. We describe parallel implementation of the solver using MPI and elements of PETSC library. The scalability of the solver is favourably compared with other methods such as direct solvers and standard GMRES method with ILU preconditioning.