ADAPTIVE MANAGEMENT OF NATIVE VEGETATION CONDITION
Grant number: LP110100321 | Funding period: 2011 - 2014
Environmental managers face severe uncertainty about how to best restore native habitats. This project will develop an adaptive strategy to improve vegetation management decisions by integrating expert knowledge with monitoring. This will improve the efficiency of management and provide an example of 'learning by doing' in two case study regions.
Related publications (9)
Classifying animals into ecologically meaningful groups: A case study on woodland birds
Hannah Fraser, Cindy E Hauser, Libby Rumpff, Georgia E Garrard, Michael A McCarthy
Ecologists often classify species into binary groupings such as woodland or non-woodland birds. However, each ecologist may apply ..
Modelling spatial and temporal changes with GIS and Spatial and Dynamic Bayesian Networks
Yung En Chee, Lauchlin Wilkinson, Ann E Nicholson, Pedro F Quintana-Ascencio, John E Fauth, Dianne Hall, Kimberli J Ponzio, Libby Rumpff
State-and-transition models (STMs) have been successfully combined with Dynamic Bayesian Networks (DBNs) to model temporal changes..
Empirically validating a dense woody regrowth 'problem' and thinning 'solution' for understory vegetation
Christopher S Jones, David H Duncan, Libby Rumpff, Freya M Thomas, William K Morris, Peter A Vesk
In landscapes with a short history of intensive land use, woody plant regrowth on cleared land is often favorably received as a sh..
Practical solutions for making models indispensable in conservation decision-making
Prue FE Addison, Libby Rumpff, S Sana Bau, Janet M Carey, Yung En Chee, Frith C Jarrad, Marissa F McBride, Mark A Burgman
Aim: Decision-making for conservation management often involves evaluating risks in the face of environmental uncertainty. Models ..