An international waste convention: measures for achieving sustainable development.

Waste is a by-product of economic growth. Consequently, economic growth presents challenges for sustainable resource management and development because continued economic growth implies continued growth in waste outputs. Poor management of waste results in the inappropriate depletion of natural resources and potentially adverse effects on the environment, health and the economy. It is unsustainable. This paper begins by outlining the magnitude of and the current response to the growth in the quantity of waste outputs. This is followed by a consideration of why the international response to date, including the Rio Declaration and Agenda 21, fails to address the issue adequately. The paper concludes with a discussion on why and how an international treaty or other measure could advance sustainable development by providing an appropriate framework within which to address the problem.     

Modeling Human Factors That Affect the Loss of Biodiversity

Within conservation biology human factors are treated as driving forces of biodiversity loss, yet there are few empirical studies on how human actions affect biodiversity. We developed and tested an interdisciplinary model of biodiversity loss using socioeconomic and ecological data from 107 countries and structural equation modeling techniques. Some portions of the model fit the data well, other parts were less predictive. Counterintuitive results may be a result of the quality and availability of cross-national data and statistical limitations in testing a model of such complex processes. This model test provides insight into future research needs for examining human impacts on biodiversity. Issues including data quality, temporal and spatial scale, and model refinement are outlined. The results highlight the importance of relations between human social systems and biodiversity and the potential of interdisciplinary research.     

The Importance of Process in Ecosystem Management: Lessons from the Lachlan Catchment,New South Wales,Australia

Effective river management requires integration of biophysical and human dimensions of the ecosystem, which in turn involves the development of new forms of decision-making processes and institutional frameworks. In New South Wales, institutional changes to river management have been formalized in the Water Management Act 2000. This paper presents the findings of a case study that investigated decision-making processes in the establishment of environmental flow regimes for the Lachlan River in western New South Wales. The study was based on document analysis, observation and interviews with members and support staff of a stakeholder-based river management committee. The findings of the study highlight social capital, adaptive management and consensus decision making as key components in establishing environmental flow regimes as part of a participatory approach to river management.     

Patch Isolation, Corridor Effects, and Colonization by a Resident Sparrow in a Managed Pine Woodland

The isolation of habitat patches is often cited as having a major impact on the dynamics of small populations occupying patches in a complex landscape. Few studies, however, have provided field data demonstrating that isolation has an identifiable effect on specific populations independent of other factors such as local habitat quality or that landscape factors such as corridors can alleviate such effects. We conducted field surveys of Bachman's Sparrow ( Aimophila aestivalis ) populations in regions, which we call linear landscapes, where suitable habitat patches were isolated to varying degrees from potential sources of dispersing birds. In these linear landscapes, isolated patches of habitat were less likely to be colonized than were nonisolated patches. We also found that corridor configurations of habitat patches improved the ability of sparrows to find and settle in newly created patches. These results suggest that, for species that do not disperse easily through inhospitable landscapes, habitat occupancy at a regional scale can be enhanced by careful landscape design and planning.     

Selective photoreduction of acetonitrile to acetaldehyde in dilute aqueous solutions

Acetonitrile is a commonly used solvent in both industry and research. The treatment of acetonitrile wastes in dilute aqueous solutions with visible light offers advantages to chemical treatment and ultraviolet (UV) irradiation. This study presents the degradation of acetonitrile via a photoinduced electron transfer reaction in the presence of a photosensitizer (dye) and a sacrificial reductant under visible light. Acetonitrile photodegradation (photoreduction) was investigated utilizing a variety of sacrificial reductants and photosensitizers. Optimal results were observed in the presence of methylene green and tri-isopropanolamine with a decrease of acetonitrile in solution to 86% in 24 hours. The only photoreaction product observed was acetaldehyde and a plausible mechanism for the photochemical degradation of acetonitrile is proposed.     

Estimating parameters of hidden Markov models based on marked individuals: use of robust design data

Development and use of multistate mark-recapture models, which provide estimates of parameters of Markov processes in the face of imperfect detection, have become common over the last 20 years. Recently, estimating parameters of hidden Markov models, where the state of an individual can be uncertain even when it is detected, has received attention. Previous work has shown that ignoring state uncertainty biases estimates of survival and state transition probabilities, thereby reducing the power to detect effects. Efforts to adjust for state uncertainty have included special cases and a general framework for a single sample per period of interest. We provide a flexible framework for adjusting for state uncertainty in multistate models, while utilizing multiple sampling occasions per period of interest to increase precision and remove parameter redundancy. These models also produce direct estimates of state structure for each primary period, even for the case where there is just one sampling occasion. We apply our model to expected-value data, and to data from a study of Florida manatees, to provide examples of the improvement in precision due to secondary capture occasions. We have also implemented these models in program MARK. This general framework could also be used by practitioners to consider constrained models of particular interest, or to model the relationship between within-primary-period parameters (e.g., state structure) and between-primary-period parameters (e.g., state transition probabilities).