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At any time, the condition of ecological infrastructure is related to the availability of funds to support operational management programmes. Environmental management outcomes are therefore often coupled to general economic conditions. When general economic conditions are favourable, investment in environmental management is often greater. This implies that environmental management frameworks need to be able to cope with the waxing and waning of economic conditions while still delivering acceptable environmental management and service delivery outcomes. At the onset of budget cuts, environmental managers therefore need effective ways of assessing the near and far future trade-offs of curtailing particular programmes in a defensible and internally consistent manner. Operators of large civil infrastructure assets face the same problem. In response, the asset management community has developed the State of Good Repair approach. The objective of the preliminary consideration presented here was to determine whether this engineering management approach has any merit in environmental management. [ABSTRACT FROM PUBLISHER]

Active restoration is increasingly being seen as a viable method for reversing global coral reef decline in many locations. We assess coral aquaculture production as a restoration strategy to grow and deploy cultivated corals to specified reef locations in the wild. We formulate and solve a novel mathematical programming model of the facility location and sizing problem for coral aquaculture. This is used to address crucial strategic decisions regarding the number, location and sizing of facilities, as well as operational decisions on growth time to minimise total costs. The characteristic function for coral survival based on facility growth time is shown to be c ritical in determining the optimal growth time. Computational experiments demonstrate that the optimal number and location of facilities are sensitive to changes in the reefs serviced and the relative weighting of capital and operational cost parameters. This demonstrates the value of data clarity to minimise total costs. [ABSTRACT FROM AUTHOR]