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在机会成本较高时实现保护:优化艾伯塔省油砂区的保护区设计。

Achieving conservation when opportunity costs are high: optimizing reserve design in Alberta's oil sands region.

机构信息

Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.

出版信息

PLoS One. 2011;6(8):e23254. doi: 10.1371/journal.pone.0023254. Epub 2011 Aug 17.

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.

摘要

最近的研究表明,在保护规划过程中纳入生物效益和经济成本的空间分布,可以实现保护增益。以加拿大艾伯塔省为例,我们在粗滤储备设计的背景下应用这些技术。由于生态系统代表性目标和其他粗滤设计要素很难客观地定义,我们使用权衡分析来系统地探索保护目标与经济机会成本之间的关系。我们使用 Marxan 保护规划软件,在每个保护目标水平上生成储备设计,以确保我们对保护和经济结果的量化代表了在每种情况下资源的最佳分配。机会成本受生态代表性目标的影响最大,这种关系是非线性的。尽管艾伯塔省大部分地区都有石油资源,包括极具价值的油砂矿床,但我们的分析表明,在保持对该地区 97%以上资源价值的同时,超过 30%的公共土地可以得到保护。我们的案例研究表明,即使保护目标定义不明确,最优资源分配也可以有效地用于支持土地利用规划中的战略决策。

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