4 resultados para irreplaceability

em University of Queensland eSpace - Australia


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A number of systematic conservation planning tools are available to aid in making land use decisions. Given the increasing worldwide use and application of reserve design tools, including measures of site irreplaceability, it is essential that methodological differences and their potential effect on conservation planning outcomes are understood. We compared the irreplaceability of sites for protecting ecosystems within the Brigalow Belt Bioregion, Queensland, Australia, using two alternative reserve system design tools, Marxan and C-Plan. We set Marxan to generate multiple reserve systems that met targets with minimal area; the first scenario ignored spatial objectives, while the second selected compact groups of areas. Marxan calculates the irreplaceability of each site as the proportion of solutions in which it occurs for each of these set scenarios. In contrast, C-Plan uses a statistical estimate of irreplaceability as the likelihood that each site is needed in all combinations of sites that satisfy the targets. We found that sites containing rare ecosystems are almost always irreplaceable regardless of the method. Importantly, Marxan and C-Plan gave similar outcomes when spatial objectives were ignored. Marxan with a compactness objective defined twice as much area as irreplaceable, including many sites with relatively common ecosystems. However, targets for all ecosystems were met using a similar amount of area in C-Plan and Marxan, even with compactness. The importance of differences in the outcomes of using the two methods will depend on the question being addressed; in general, the use of two or more complementary tools is beneficial.

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Using benthic habitat data from the Florida Keys (USA), we demonstrate how siting algorithms can help identify potential networks of marine reserves that comprehensively represent target habitat types. We applied a flexible optimization tool-simulated annealing-to represent a fixed proportion of different marine habitat types within a geographic area. We investigated the relative influence of spatial information, planning-unit size, detail of habitat classification, and magnitude of the overall conservation goal on the resulting network scenarios. With this method, we were able to identify many adequate reserve systems that met the conservation goals, e.g., representing at least 20% of each conservation target (i.e., habitat type) while fulfilling the overall aim of minimizing the system area and perimeter. One of the most useful types of information provided by this siting algorithm comes from an irreplaceability analysis, which is a count of the number of, times unique planning units were included in reserve system scenarios. This analysis indicated that many different combinations of sites produced networks that met the conservation goals. While individual 1-km(2) areas were fairly interchangeable, the irreplaceability analysis highlighted larger areas within the planning region that were chosen consistently to meet the goals incorporated into the algorithm. Additionally, we found that reserve systems designed with a high degree of spatial clustering tended to have considerably less perimeter and larger overall areas in reserve-a configuration that may be preferable particularly for sociopolitical reasons. This exercise illustrates the value of using the simulated annealing algorithm to help site marine reserves: the approach makes efficient use of;available resources, can be used interactively by conservation decision makers, and offers biologically suitable alternative networks from which an effective system of marine reserves can be crafted.

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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 tail 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 halt 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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With marine biodiversity conservation the primary goal for reserve planning initiatives, a site's conservation potential is typically evaluated on the basis of the biological and physical features it contains. By comparison, socio-economic information is seldom a formal consideration of the reserve system design problem and generally limited to an assessment of threats, vulnerability or compatibility with surrounding uses. This is perhaps surprising given broad recognition that the success of reserve establishment is highly dependent on widespread stakeholder and community support. Using information on the spatial distribution and intensity of commercial rock lobster catch in South Australia, we demonstrate the capacity of mathematical reserve selection procedures to integrate socio-economic and biophysical information for marine reserve system design. Analyses of trade-offs highlight the opportunities to design representative, efficient and practical marine reserve systems that minimise potential loss to commercial users. We found that the objective of minimising the areal extent of the reserve system was barely compromised by incorporating economic design constraints. With a small increase in area (< 3%) and boundary length (< 10%), the economic impact of marine reserves on the commercial rock lobster fishery was reduced by more than a third. We considered also how a reserve planner might prioritise conservation areas using information on a planning units selection frequency. We found that selection frequencies alone were not a reliable guide for the selection of marine reserve systems, but could be used with approaches such as summed irreplaceability to direct conservation effort for efficient marine reserve design.