Knowledge centre

Research and publications

Working with OEH for mutual benefit

Major OEH programs and existing resources can meet some of the priority knowledge needs. Other priorities are aspirational and best achieved through collaboration. Opportunities for research partners and other organisations to work with OEH are outlined below. More information about each of the knowledge themes is available in information sheets.

Biodiversity

  • Abundance and distribution of biodiversity: Inform management actions and priorities by, for example, mapping threatened ecological communities at a fine-scale in priority areas
  • Ecosystem services to better manage species: Identify species that provide critical ecosystem services or hold major cultural or economic significance to inform management
  • Appropriate management actions and how to prioritise them: Develop techniques to restore ecosystems and build their resilience. Identify ways to improve the recovery of threatened species. Integrate spatial information from multiple sources to prioritise conservation actions
  • Effectiveness of existing processes and tools to conserve biodiversity: Improve the capacity of protected areas to conserve biodiversity over the long- term. Gather ecological data to inform impact assessments. Better understand conservation values at different scales to inform decision-making processes

Climate Change Impacts & Adaptation

NSW Adaptation Research Hub: OEH has established the NSW Adaptation Research Hub which has three nodes. Research institutions host each node and collaborate with OEH to study the impacts of climate change in NSW and develop potential adaptation responses. The three nodes are:

  • Adaptive Communities – hosted by the Institute for Sustainable Futures (University of Technology Sydney) and CSIRO
  • Biodiversity – hosted by Macquarie University and CSIRO
  • Coastal Processes and Responses – hosted by the Sydney Institute of Marine Science and the Australian Climate Change Adaptation Research Network for Settlements  and Infrastructure.

Future collaborations and priority knowledge needs will be identified by the NSW Adaptation Research Hub.

Coastal, Estuarine & Marine Environments

  • Coastal values to balance multiple uses: Better understand coastal values (social, economic and environmental) held by coastal communities
  • Coastal erosion to develop management responses: Refine and promote tools to help coastal planners predict the risk of erosion under current and possible future conditions
  • Estuarine foreshore inundation and sea level rise: Understand how the risk of flooding varies within and between estuaries, to tailor planning responses. Build this knowledge through monitoring, mapping and modelling, and by analysing historic trends and extreme events
  • How to predict estuarine responses to management actions: Develop regional models that link catchments with estuary responses, to support regional planning
  • Conservation needs for better regulation: Assess the extent and condition of marine habitats, natural resource assets and heritage objects, to improve management, regulation and conservation outcomes

Landscape Management 

  • Landscape processes and ecosystem services: Understand spatial landscape processes, connectivity, function and threats to human and environmental health, to promote productive and sustainable landscapes
  • Social drivers of landscape change: Improve methods to communicate with landholders, institutions and Aboriginal communities, about landscape management. Build knowledge of the impacts of socio-cultural values and behaviours on landscapes
  • Biophysical drivers of landscape change: Study the impacts of pressures and threats on landscape function, to inform regional planning
  • Landscape monitoring and data collection: Build knowledge of how landscape function and ecosystems services change over time and space. Enable better management decisions by determining the essential attributes of healthy, productive and resilient landscapes
  • How to assess and manage landscapes by using decision-support systems: Develop and promote decision-support systems that assess pressures and threats to landscapes. Support capacity-building for local and regional planning authorities to help communities adapt to change

Pollution 

  • Activities that cause pollution and types of pollutants from activities: Deliver new or improved tools to measure and identify pollutant sources and concentrations. Study potential sources and impacts of non-traditional or emerging pollutants. Investigate cost-effective technologies for pollution control and mitigation
  • How to determine the risk of unacceptable impacts to human and environmental health: Understand how to predict the future impacts of pollutants and polluting processes. Use this knowledge to develop resources to prioritise management options
  • What drives and influences behaviour: Study the factors that influence the behaviour and expectations of the regulated community, to reduce red tape, manage expectations and increase uptake of policies

Water & Wetlands

  • Extent and condition of wetlands and groundwater-dependent ecosystems: Complete a comprehensive inventory of significant NSW wetlands. Identify the groundwater-dependent ecosystems of most socio-economic value, to inform management decisions
  • The best management tools for aquatic resources: Assess the potential risks to aquatic ecosystems from existing and proposed developments, including mining
  • Acceptable target conditions for aquatic ecosystems: Build knowledge of the natural and cultural values of wetlands, rivers and groundwater-dependent ecosystems, to support communities and agencies to manage these systems, determine targets for sustainable use, and protect cultural heritage
  • How wetlands and floodplains function: Monitor and model aquatic ecosystems and deliver decision-support systems to support water planners and communities, and inform the allocation of environmental water
  • How to measure progress: Undertake monitoring, evaluation and reporting, and survey wetland condition, to ground-truth remote-sensing and predictive models
Page last updated: 14 August 2013