Abstract
Recent studies have shown that conservation gains can be achieved when the spatial distributions of biological benefits and economic costs are incorporated in the conservation planning process. Using Alberta, Canada, as a case study we apply these techniques in the context of coarse-filter reserve design. Because targets for ecosystem representation and other coarse-filter design elements are difficult to define objectively we use a trade-off analysis to systematically explore the relationship between conservation targets and economic opportunity costs. We use the Marxan conservation planning software to generate reserve designs at each level of conservation target to ensure that our quantification of conservation and economic outcomes represents the optimal allocation of resources in each case. Opportunity cost is most affected by the ecological representation target and this relationship is nonlinear. Although petroleum resources are present throughout most of Alberta, and include highly valuable oil sands deposits, our analysis indicates that over 30% of public lands could be protected while maintaining access to more than 97% of the value of the region's resources. Our case study demonstrates that optimal resource allocation can be usefully employed to support strategic decision making in the context of land-use planning, even when conservation targets are not well defined.
Highlights
It is becoming widely recognized that trade-offs between conservation objectives and economic objectives need to be addressed as an integral component of the conservation planning process [1,2,3]
In the trade-off analysis we systematically explore the relationship between conservation targets and economic opportunity costs
In the scenarios where the model included only the representation target and minimization of cost, the net present value (NPV) of the reserve system remained less than 1% of the total NPV of the study area until the representation target exceeded 30%
Summary
It is becoming widely recognized that trade-offs between conservation objectives and economic objectives need to be addressed as an integral component of the conservation planning process [1,2,3]. Various approaches involving optimal resource allocation techniques have been developed for this purpose [4,5,6,7] These approaches can help ensure that conservation gains are as great as possible given other land use constraints and that conservation plans do not fail at the point of implementation [2,8]. Other applications involve maximizing the number of species protected per dollar invested using a return on investment approach [1,7]. In both cases the conservation objective can be clearly defined, either in terms of the number of species protected or, in the case of individual species, measures of population viability. This provides a robust basis for constructing an objective function and applying optimization algorithms
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