Public choice of species for the ark: Phylogenetic similarity and preferred wildlife species for survival

Humans play a role in deciding the fate of species in the current extinction wave. Because of the previous Similarity Principle, physical attractiveness and likeability, it has been argued that public choice favours the survival of species that satisfy these criteria at the expense of other species. This paper empirically tests this argument by considering a hypothetical ‘Ark’ situation. Surveys of 204 members of the Australian public inquired whether they are in favour of the survival of each of 24 native mammal, bird and reptile species (prior to and after information provision about each species). The species were ranked by percentage of ‘yes’ votes received. Species composition by taxon in various fractions of the ranking was determined. If the previous Similarity Principle holds, mammals should rank highly and dominate the top fractions of animals saved in the hierarchical list. We find that although mammals would be over-represented in the ‘Ark’, birds and reptiles are unlikely to be excluded when social choice is based on numbers ‘voting’ for the survival of each species. Support for the previous Similarity Principle is apparent particularly after information provision. Public policy implications of this are noted and recommendations are given.

Algebraic Bethe ansatz for integrable extended Hubbard models arising from supersymmetric group solutions

Integrable extended Hubbard models arising from symmetric group solutions are examined in the framework of the graded quantum inverse scattering method. The Bethe ansatz equations for all these models are derived by using the algebraic Bethe ansatz method.

Integrable extended hubbard models with boundary Kondo impurities

Three kinds of integrable Kondo impurity additions to one-dimensional q-deformed extended Hubbard models are studied by means of the boundary Z(2)-graded quantum inverse scattering method. The boundary K matrices depending on the local magnetic moments of the impurities are presented as nontrivial realisations of the reflection equation algebras in an impurity Hilbert space. The models are solved by using the algebraic Bethe ansatz method, and the Bethe ansatz equations are obtained.

Robust parameter settings of evolutionary algorithms for the optimisation of agricultural systems models

Numerical optimisation methods are being more commonly applied to agricultural systems models, to identify the most profitable management strategies. The available optimisation algorithms are reviewed and compared, with literature and our studies identifying evolutionary algorithms (including genetic algorithms) as superior in this regard to simulated annealing, tabu search, hill-climbing, and direct-search methods. Results of a complex beef property optimisation, using a real-value genetic algorithm, are presented. The relative contributions of the range of operational options and parameters of this method are discussed, and general recommendations listed to assist practitioners applying evolutionary algorithms to the solution of agricultural systems. (C) 2001 Elsevier Science Ltd. All rights reserved.

Assessing alternative models of individualism and collectivism: A confirmatory factor analysis

Six alternative structural models of individualism-collectivism are reviewed and empirically compared in a confirmatory factor analysis of questionnaire data from an Australian student sample (N=340). Central to the debate about the structure of this broad social attitude are the issues of (I) polarity (are individualism and collectivism bipolar opposites, or orthogonal factors?) and (2) dimensionality (are individualism and collectivism themselves higher-order constructs subsuming several more specific factors and, if so, what are they?). The data from this Australian sample support a model that represents individualism and collectivism as a higher-order bipolar factor hierarchically subsuming several bipolar reference-group-specific individualisms and collectivisms. Copyright (C) 2001 John Wiley & Sons, Ltd.