Enhancing and promoting informed environmental decision making for local government authorities and natural resource management groups. — YRD

Enhancing and promoting informed environmental decision making for local government authorities and natural resource management groups. (3125)

Brooke Hynch 1
  1. Griffith University, Meadowbrook, QLD, Australia

There are currently 561 local government authorities (LGA), 56 natural resource management (NRM)  groups and over 500 NRM related community groups within Australia. Consultations with some of these organisations in Queensland has indicated that they face serious challenges to systematically identifying, discovering and utilising data that has been collected by the LGA’s or by external agencies within the LGA regions.

LGA’s and NRM groups are charged with creating long term strategic plans for ecological corridors and nature refuge planning.  However other activities often include: developing environmental offset mechanisms, developing environmental assessment and planning provisions, undertaking revegetation, conservation and pest management programs, and incorporating outputs from citizen science programs into their decision making processes.

Challenges confronting these organisations include access to, knowledge of, and the skills to utilise:

  • existing data sets, their location and utilisation;
  • data management - access, storage, interoperability, and re-use;
  • climate change information;
  • online modelling tools;
  • integration of climate change adaptation measures into policies and programs.

This presentation will detail a model that streamlines the uptake of cutting edge technology, a lengthy process: from initial concept, implementation and refinement in a university setting, through to the end-user in LGAs who need to apply these ideas. 

The model articulates the development of a technology-orientated social program to provide services to LGAs and to use derived revenue to support continual research into ecological modeling, climate change adaptation and best practice data management.