Prioritising catchment rehabilitation for multi objective management: An application from SE-Queensland, Australia

被引:19
作者
Hermoso, Virgilio [1 ,2 ,3 ]
Pantus, Francis [1 ,2 ]
Olley, Jon [1 ,2 ]
Linke, Simon [1 ,2 ]
Mugodo, James [2 ]
Lea, Patrick [2 ]
机构
[1] Griffith Univ, Australian Rivers Inst, Nathan, Qld 4111, Australia
[2] Univ Melbourne, eWater Cooperat Res Ctr, Parkville, Vic 3010, Australia
[3] Ctr Tecnol Forestal Catalunya, Solsona 25280, Lleida, Spain
关键词
Decision making; MOSA; NRM tradeoffs; Opportunity cost; Pareto-optimal; Stakeholder; RIVER; RESTORATION; THREATS; OPTIMIZATION; EROSION;
D O I
10.1016/j.ecolmodel.2015.08.017
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Freshwater ecosystems are among the most diverse environments on Earth but also one of the most degraded and threatened due mainly to the intense human modification and exploitation. Despite the increase in funds devoted to rehabilitation of these systems little success has been reported so far. When planning for rehabilitation of catchments, stakeholders have to decide what combination of actions to implement and at which locations from a vast number of possible options. Often these activities are constrained by limited budgets. Here we apply the principles of systematic planning to rehabilitation, integrating erosion, sediment transport, ecological and economic objectives into the planning process to enhance the effectiveness of the rehabilitation plans and to support stakeholders in better understanding the effects of various objectives. We develop and apply a multi-objective approach to find a set of near-optimal trade-off solutions among a large number of candidate combinations of rehabilitation actions under sometimes competing objectives. We use a Pareto-optimal approach to store potentially useful combinations of rehabilitation actions (trade-offs) along the management objective gradients. Presenting those trade-offs as a function of the management objectives allow users to understand the commonalities and differences of various rehabilitation options when selecting different objectives. It is the learning from these relationships that classic optimisation approaches often lack. As proof of concept, we used an example rehabilitation project in South East Queensland (Australia) that aims to reduce sediment loads and improve the ecological health (measured as the EHMP index) of rivers while minimizing opportunity cost of rehabilitation plans. Opportunity cost is defined as the forgone economic value that would be compromised by the implementation of a rehabilitation plan. We found that our approach was efficient and effective in finding and systematically presenting promising trade-offs along different objective gradients (sediment reduction, ecosystem health and opportunity cost economics). (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:168 / 175
页数:8
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