Human settlements: Australia state of the environment report, 2001

Australia’s transition to the 21st century has been marked by an extended period of economic prosperity unmatched for several decades, but one in which a series of question marks are being raised in three principal areas: in relation to the environment, the social well-being of the population, and the future path of economic development. The first concern, which is of primary interest in this report, relates to the physical environment of cities and their surrounding regions, and the range of pressures exerted by population and human activity. The report begins by noting the increasing divergence of the prime indicator of national economic performance—gross domestic product (GDP)—from the Genuine Progress Indicator (GPI). GPI is a new experimental measure of sustainable development that accommodates factors currently unaccounted for in GDP, such as income distribution, value of household work, cost of unemployment, and various other social and environmental costs. The divergence of these two indicators in recent decades suggests that Australia’s growth has been heavily dependent on the draw-down of the nation’s stocks of capital assets (its infrastructure), its human and social capital, and its natural capital (Hamilton 1997).

The Environment and the Selection of Aquaculture Species and Systems: An Economic Analysis

Environmental conditions play a significant role in the economic success of aquaculture. This article classifies environmental factors in a way that facilitates economic analysis of their implications for the selection of aquaculture species and systems. The implication of on-farm as on-site environmental conditions for this selection are considered first using profit-possibility frontiers and taking into account the biological law of environmental tolerance. However, in selecting, recommending and developing aquaculture species and systems, it is often unrealistic to assume the degree of managerial efficiency implied by the profit-possibility function. It is appropriate to take account of the degree of managerial inefficiency that actually exists, not all of which may be capable of being eliminated. Furthermore, experimental R&D should be geared to on-farm conditions, and the variability of these conditions needs to be taken into account. Particularly in shared water bodies, environmental spillovers between aquaculturalists can be important and as shown theoretically, can influence the socially optimal selection of aquaculture species and systems. Similarly, aquaculture can have environmental consequences for the rest of the community. The social economic implications of this for the selection of aquaculture species and systems are analyzed. Some paradoxical results are obtained. For example, if the quality of social governance of aquaculture is poor, aquaculture species and systems that cause a slow rate of environmental deterioration may be socially less satisfactory than those that cause a rapid rate of such deterioration. Socially optimal choice of aquaculture species and systems depends not only on their biophysical characteristics and market conditions but also on the prevailing state of governance of aquaculture. Failure to consider the last aspect can result in the introduction of new aquaculture species (and systems) doing more social harm than good.

Long-term survivor mixture model with random effects: application to a multi-centre clinical trial of carcinoma

A mixture model incorporating long-term survivors has been adopted in the field of biostatistics where some individuals may never experience the failure event under study. The surviving fractions may be considered as cured. In most applications, the survival times are assumed to be independent. However, when the survival data are obtained from a multi-centre clinical trial, it is conceived that the environ mental conditions and facilities shared within clinic affects the proportion cured as well as the failure risk for the uncured individuals. It necessitates a long-term survivor mixture model with random effects. In this paper, the long-term survivor mixture model is extended for the analysis of multivariate failure time data using the generalized linear mixed model (GLMM) approach. The proposed model is applied to analyse a numerical data set from a multi-centre clinical trial of carcinoma as an illustration. Some simulation experiments are performed to assess the applicability of the model based on the average biases of the estimates formed. Copyright (C) 2001 John Wiley & Sons, Ltd.

Early-Mid Holocene climatic variations in Tasmania, Australia: multi-proxy records in a stalagmite from Lynds Cave

Mass spectrometric uranium-series dating and C-O isotopic analysis of a stalagmite from Lynds Cave, northern Tasmania, Australia provide a high-resolution record of regional climate change between 5100 and 9200 yr before present (BP). Combined delta(18)O, delta(13)C, growth rate, initial U-234/U-238 and physical property (color, transparency and porosity) records allow recognition of seven climatic stages: Stage I ( > 9080 yr BP) - a relatively dry period at the beginning of stalagmite growth evidenced by elevated U-234/U-238; Stage II (9080-8600 yr BP) - a period of unstable climate characterized by high-frequency variability in temperature and bio-productivity; Stage 111 (8600-8000 yr BP) - a period of stable and moderate precipitation and stable and high bio-productivity, with a continuously rising temperature; Stage IV (8000-7400 yr BP) - the warmest period with high evaporation and low effective precipitation (rainfall less evaporation); Stage V (7400-7000 yr BP) - the wettest period with highest stalagmite growth and enhanced but unstable bio-productivity; Stage VI (7000-6600 yr BP) - a period with a significantly reduced precipitation and bio-productivity without noticeable change in temperature; Stage VII (6600-5100 yr BP) - a period of lowest temperature and precipitation marking a significant climatic deterioration. Overall, the records suggest that the warmest climate occurred between 8000 and 7400 yr BP, followed by a wettest period between 7400 and 7000 yr BP. These are broadly correlated with the so-called 'Mid Holocene optimum' previously proposed using pollen and lake level records. However, the timing and resolution of the speleothem. record from Lynds Cave are significantly higher than in both the pollen and lake level records. This allows us to correlate the abrupt change in physical property, delta(18)O, delta(13)C, growth rate, and initial U-234/U-238 of the stalagmite at similar to8000 yr BP with a global climatic event at Early-Mid Holocene transition. (C) 2001 Elsevier Science B.V. All rights reserved.

Integrating high and moderate spatial resolution image data to estimate forest age structure

The collection of spatial information to quantify changes to the state and condition of the environment is a fundamental component of conservation or sustainable utilization of tropical and subtropical forests, Age is an important structural attribute of old-growth forests influencing biological diversity in Australia eucalypt forests. Aerial photograph interpretation has traditionally been used for mapping the age and structure of forest stands. However this method is subjective and is not able to accurately capture fine to landscape scale variation necessary for ecological studies. Identification and mapping of fine to landscape scale vegetative structural attributes will allow the compilation of information associated with Montreal Process indicators lb and ld, which seek to determine linkages between age structure and the diversity and abundance of forest fauna populations. This project integrated measurements of structural attributes derived from a canopy-height elevation model with results from a geometrical-optical/spectral mixture analysis model to map forest age structure at a landscape scale. The availability of multiple-scale data allows the transfer of high-resolution attributes to landscape scale monitoring. Multispectral image data were obtained from a DMSV (Digital Multi-Spectral Video) sensor over St Mary's State Forest in Southeast Queensland, Australia. Local scene variance levels for different forest tapes calculated from the DMSV data were used to optimize the tree density and canopy size output in a geometric-optical model applied to a Landsat Thematic Mapper (TU) data set. Airborne laser scanner data obtained over the project area were used to calibrate a digital filter to extract tree heights from a digital elevation model that was derived from scanned colour stereopairs. The modelled estimates of tree height, crown size, and tree density were used to produce a decision-tree classification of forest successional stage at a landscape scale. The results obtained (72% accuracy), were limited in validation, but demonstrate potential for using the multi-scale methodology to provide spatial information for forestry policy objectives (ie., monitoring forest age structure).