The public's knowledge of and support for conservation of Australia's Tree-Kangaroos

After providing some brief background on Dendrolagus species in Australia, two consecutive surveys of Brisbane’s residents are used to assess public knowledge of tree-kangaroos and the stated degree of support for their conservation in Australia. The responses of participants in Survey I are based on their pre-survey knowledge of wildlife. The same additional set of participants completed Survey II after being provided with information on all the wildlife species mentioned in Survey I. Changes in the attitudes of respondents and their degree of support for the protection and conservation of Australia’s tree-kangaroos are measured, including changes in their contingent valuations and stated willingness to provide financial support for such conservation. Reasons for wanting to protect tree-kangaroos are specified and analyzed. Furthermore, changes that occur in the relative importance of these reasons with increased knowledge are also examined. Support for the conservation of tree-kangaroos is found to increase with the additional knowledge supplied. Furthermore, support for the conservation of Australia’s less well-known tropical mammals is shown to increase relative to better known mammals (icons) present in temperate areas, such as koalas and red kangaroos with this increased knowledge. Possible implications of the results for government conservation policies in Australia are examined.

Lanczos subspace filter diagonalization: Homogeneous recursive filtering and a low-storage method for the calculation of matrix elements

We develop a new iterative filter diagonalization (FD) scheme based on Lanczos subspaces and demonstrate its application to the calculation of bound-state and resonance eigenvalues. The new scheme combines the Lanczos three-term vector recursion for the generation of a tridiagonal representation of the Hamiltonian with a three-term scalar recursion to generate filtered states within the Lanczos representation. Eigenstates in the energy windows of interest can then be obtained by solving a small generalized eigenvalue problem in the subspace spanned by the filtered states. The scalar filtering recursion is based on the homogeneous eigenvalue equation of the tridiagonal representation of the Hamiltonian, and is simpler and more efficient than our previous quasi-minimum-residual filter diagonalization (QMRFD) scheme (H. G. Yu and S. C. Smith, Chem. Phys. Lett., 1998, 283, 69), which was based on solving for the action of the Green operator via an inhomogeneous equation. A low-storage method for the construction of Hamiltonian and overlap matrix elements in the filtered-basis representation is devised, in which contributions to the matrix elements are computed simultaneously as the recursion proceeds, allowing coefficients of the filtered states to be discarded once their contribution has been evaluated. Application to the HO2 system shows that the new scheme is highly efficient and can generate eigenvalues with the same numerical accuracy as the basic Lanczos algorithm.