Journal article
Optimisation as a process for understanding and managing river ecosystems
- Abstract:
- Optimisation can assist in the management of riverine ecosystems through the exploration of multiple alternative management strategies, and the evaluation of trade-offs between conflicting objectives. In addition, it can facilitate communication and learning about the system. However, the effectiveness of optimisation in aiding decision making for ecological management is currently limited by four major challenges: identification and quantification of ecosystem objectives; representation of ecosystems in predictive simulation models; specification of objectives and management alternatives in an optimisation framework; and evaluation of model results against actual ecological outcomes. This study evaluates previous literature in ecology, optimisation and decision science, and provides a strategy for addressing the challenges identified. It highlights the need for better recognition and analysis of assumptions in optimisation modelling as part of a process that generates and shares knowledge.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 376.4KB, Terms of use)
-
- Publisher copy:
- 10.1016/j.envsoft.2016.04.029
Authors
+ National Centre for Groundwater Research and Training, Australia
More from this funder
- Funding agency for:
- Barbour, E
- Publisher:
- Elsevier
- Journal:
- Environmental Modelling and Software More from this journal
- Volume:
- 83
- Pages:
- 167-178
- Publication date:
- 2016-05-31
- Acceptance date:
- 2016-04-29
- DOI:
- EISSN:
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1873-6726
- ISSN:
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1364-8152
- Keywords:
- Pubs id:
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pubs:626780
- UUID:
-
uuid:ece7b5ca-0101-41c3-bee3-e5a3567c146c
- Local pid:
-
pubs:626780
- Source identifiers:
-
626780
- Deposit date:
-
2016-06-08
Terms of use
- Copyright holder:
- Elsevier
- Copyright date:
- 2016
- Notes:
- © 2016 Elsevier Ltd. All rights reserved. This is the accepted manuscript version of the article. The final version is available online from Elsevier at: [10.1016/j.envsoft.2016.04.029]
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