Toxicity Testing of Crude Oil and Related Compounds Using Early Life Stages of the Crimson-Spotted Rainbowfish (Melanotaenia fluviatilis)
In: Ecotoxicology and Environmental Safety, Band 52, Heft 3, S. 180-189
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In: Ecotoxicology and Environmental Safety, Band 52, Heft 3, S. 180-189
In: Ecotoxicology and Environmental Safety, Band 43, Heft 3, S. 309-316
In: Ecotoxicology and environmental safety: EES ; official journal of the International Society of Ecotoxicology and Environmental safety, Band 72, Heft 4, S. 1265-1270
ISSN: 1090-2414
Environmental Decision Support Systems (EDSS) are one of a suite of tools that natural resource management (NRM) practitioners may use to support the development of, or help report on the success, of NRM programs. This paper outlines two DSS that are being developed for state government or NRM agencies in Australia to assist them to develop, implement and manage programs aimed at improving resource condition. IBIS is an EDSS that models ecological outcomes of environmental flows. VegBN models the effectiveness of NRM interventions on native vegetation quality on private land in northern Victoria. The underlying model base of each EDSS is comprised of Bayesian Network (BN) models linked with other BN or component models. Bayesian networks have proved to be a flexible and highly valuable approach to modelling such highly complex and uncertain environmental systems. They are an approach that can add rigour and transparency to decision-making processes and have in Australia gained considerable interest from researchers as well as government and other organisations involved in the management of natural resources.
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Globally wetlands are increasingly under threat due to changes in water regimes as a result of river regulation and climate change. We developed the Exploring CLimAte Impacts on Management (EXCLAIM) decision support system (DSS), which simulates flow-driven habitat condition for 16 vegetation species, 13 waterbird species and 4 fish groups in the Macquarie catchment, Australia. The EXCLAIM DSS estimates impacts to habitat condition, considering scenarios of climate change and water management. The model framework underlying the DSS is a probabilistic Bayesian network, and this approach was chosen to explicitly represent uncertainties in climate change scenarios and predicted ecological outcomes. The results suggest that the scenario with no climate change and no water resource development (i.e. flow condition without dams, weirs or water license entitlements, often regarded as a surrogate for 'natural' flow) consistently has the most beneficial outcomes for vegetation, waterbird and native fish. The 2030 dry climate change scenario delivers the poorest ecological outcomes overall, whereas the 2030 wet climate change scenario has beneficial outcomes for waterbird breeding, but delivers poor outcomes for river red gum and black box woodlands, and fish that prefer river channels as habitats. A formal evaluation of the waterbird breeding model showed that higher numbers of observed nest counts are typically associated with higher modelled average breeding habitat conditions. The EXCLAIM DSS provides a generic framework to link hydrology and ecological habitats for a large number of species, based on best available knowledge of their flood requirements. It is a starting point towards developing an integrated tool for assessing climate change impacts on wetland ecosystems. ; Funding for this project was provided by the Australian Government's Caring for our Country Program and the Water for the Future Program, and the NSW Government's Catchment Action NSW Program and the Rivers Environmental Restoration Program, through NSW Central West Catchment Management Authority and NSW Office of Environment and Heritage.
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Environmental Decision Support Systems (EDSS) are one of a suite of tools that natural resource management (NRM) practitioners may use to support the development of, or help report on the success, of NRM programs. This paper outlines two DSS that are being developed for state government or NRM agencies in Australia to assist them to develop, implement and manage programs aimed at improving resource condition. IBIS is an EDSS that models ecological outcomes of environmental flows. VegBN models the effectiveness of NRM interventions on native vegetation quality on private land in northern Victoria. The underlying model base of each EDSS is comprised of Bayesian Network (BN) models linked with other BN or component models. Bayesian networks have proved to be a flexible and highly valuable approach to modelling such highly complex and uncertain environmental systems. They are an approach that can add rigour and transparency to decision-making processes and have in Australia gained considerable interest from researchers as well as government and other organisations involved in the management of natural resources.
BASE
Evaluating different environmental policy options requires extensive modelling of biophysical processes and attributes linked with metrics to measure the magnitude and distribution of societal impacts. An integrated ecosystem services assessment (IESA) has potential to provide salient, credible and legitimate information for environmental policy- and decision-makers. Here we present results of an IESA of the Murray-Darling Basin Plan, an Australian Government initiative to restore aspects of river flow regimes to improve the ecological condition of floodplains, rivers and wetlands in south-eastern Australia. The main outcome from the IESA is that the supply of most ecosystem services (ES) improves under Basin Plan policy and that these improvements have considerable monetary value. An IESA can provide actionable ecological, economic and social information for policy- and decision-makers. In the Basin Plan case the IESA was underpinned by hydrological scenarios that were input into ecological models and interdisciplinary integration across scales, values and variables.
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This study was partially supported by core funds of ICIMOD contributed by the governments of Afghanistan, Australia, Austria, Bangladesh, Bhutan, China, India, Myanmar, Nepal, Norway, Pakistan, Sweden, and Switzerland. AO was supported by funding from the National Environmental Research Council (NERC) National Capability Overseas Development Assistance under the grant 'Polar expertise –Supporting development' (NE/R000107/1). ; River systems originating from the Upper Indus Basin (UIB) are dominated by runoff from snow and glacier melt and summer monsoonal rainfall. These water resources are highly stressed as huge populations of people living in this region depend on them, including for agriculture, domestic use, and energy production. Projections suggest that the UIB region will be affected by considerable (yet poorly quantified) changes to the seasonality and composition of runoff in the future, which are likely to have considerable impacts on these supplies. Given how directly and indirectly communities and ecosystems are dependent on these resources and the growing pressure on them due to ever-increasing demands, the impacts of climate change pose considerable adaptation challenges. The strong linkages between hydroclimate, cryosphere, water resources, and human activities within the UIB suggest that a multi- and inter-disciplinary research approach integrating the social and natural/environmental sciences is critical for successful adaptation to ongoing and future hydrological and climate change. Here we use a horizon scanning technique to identify the Top 100 questions related to the most pressing knowledge gaps and research priorities in social and natural sciences on climate change and water in the UIB. These questions are on the margins of current thinking and investigation and are clustered into 14 themes, covering three overarching topics of 'governance, policy, and sustainable solutions', 'socioeconomic processes and livelihoods', and 'integrated Earth System processes'. Raising awareness of these ...
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