Using mathematical programming to address the multiple reserve selection problem: An example from the Eyre Peninsula, South Australia

Cocks, K. D.; Baird, I.A.

doi:10.1016/0006-3207(89)90083-9

Cited by 216 publications

(100 citation statements)

References 5 publications

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“…Applications of these methods to find optimal solutions to the reserve site selection problem include Cocks and Baird (1989), Saetersdal et al (1993), Church et al (1996), Kiester et al (1996), Csuti et al (1997), Pressey et al (1997), Ando et al (1998), Snyder et al (1999), and Polasky et al (2001).…”

Section: Introductionmentioning

confidence: 99%

Dynamic reserve site selection

Costello

Polasky

2004

Resource and Energy Economics

303

212

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Section: Introductionmentioning

confidence: 99%

Dynamic reserve site selection

Costello

Polasky

2004

Resource and Energy Economics

303

212

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“…The application of mathematical algorithms to conservation planning and reserve system design is well known in terrestrial systems (Cocks & Baird 1989, Pressey & Nicholls 1989, Pressey et al 1995, Margules & Pressey 2000, Possingham et al 2000. These methods provide decision support for efficient reserve system design through their capacity to include ecological, spatial and socio-economic information and their flexibility to respond quickly to a variety of treatments and scenarios set by planners, stakeholders and the community (Margules & Nicholls 1988, Pressey & Nicholls 1989, Vane-Wright et al 1991, Nicholls & Margules 1993, Williams et al 1996, Rodrigues et al 1999, Pressey & Cowling 2001, McDonnell et al 2002.…”

Section: Introductionmentioning

confidence: 99%

Opportunity cost of ad hoc marine reserve design decisions: an example from South Australia

Stewart¹,

Noyce²,

Possingham³

2003

Mar. Ecol. Prog. Ser.

136

106

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Like many states and territories, South Australia has a legacy of marine reserves considered to be inadequate to meet current conservation objectives. In this paper we configured exploratory marine reserve systems, using the software MARXAN, to examine how efficiently South Australia's existing marine reserves contribute to quantitative biodiversity conservation targets. Our aim was to compare marine reserve systems that retain South Australia's existing marine reserves with reserve systems that are free to either ignore or incorporate them. We devised a new interpretation of irreplaceability to identify planning units selected more than could be expected from chance alone. This is measured by comparing the observed selection frequency for an individual planning unit with a predicted selection frequency distribution. Knowing which sites make a valuable contribution to efficient marine reserve system design allows us to determine how well South Australia's existing reserves contribute to reservation goals when representation targets are set at 5, 10, 15, 20, 30 and 50% of conservation features. Existing marine reserves that fail to contribute to efficient marine reserve systems constitute 'opportunity costs'. We found that despite spanning less than 4% of South Australian state waters, locking in the existing ad hoc marine reserves presented considerable opportunity costs. Even with representation targets set at 50%, more than half of South Australia's existing marine reserves were selected randomly or less in efficient marine reserve systems. Hence, ad hoc marine reserve systems are likely to be inefficient and may compromise effective conservation of marine biodiversity.

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“…Typically, biological reserve sites are selected to cover the maximum number species given a constraint on the total number of sites that can be included (Church, Stoms, and Davis 1996;Cocks and Baird 1989;Csuti et al 1997;Kiester et al 1996;Saetersdal et al 1993;Willis et al 1996). A species is covered when it occurs in at least one selected reserve site.…”

Section: Introductionmentioning

confidence: 99%