Conservation planning involves identifying and selecting actions to best achieve objectives for managing natural, social and cultural resources. Conservation problems are often high dimensional when specified as combinatorial or portfolio problems and when multiple competing objectives are considered at varying spatial and temporal scales. Although analytical techniques such as modern portfolio theory (MPT) have been developed to address these complex problems, open source computational platforms for executing these approaches are not readily available. We present a user-friendly R-package called SiteOpt for optimization of binary decisions while explicitly considering environmental or economic uncertainty and the risk tolerance of decision makers. We illustrate the package with spatially-explicit site selection problems (i.e. spatial conservation planning), including an option for divestment (i.e. selling assets), when accounting for future uncertainties in designing conservation areas. The tool is applicable to both spatial and non-spatial problems, such as budget allocation or species selection. Constraints for spatial design and spatial dependencies (e.g. connectivity among sites) can also be specified in SiteOpt. Users can optimize site selection based on two competing objectives by solving for the Nash bargaining solution. Importantly, by quantifying uncertainty and asset spatial correlation, a measure of risk can be included as one such objective to be traded off against portfolio benefits. Thus, SiteOpt can be used to explicitly manage risk in portfolio-based spatial optimization. This tool facilitates decisions in a variety of problem settings, including reserve selection, invasive species management, allocation of law enforcement activities for conservation, budget allocation and asset selection under uncertainty and risk.

中文翻译：

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SiteOpt：用于站点选择和投资组合优化的开源 R 包

保护规划涉及确定和选择行动以最好地实现管理自然、社会和文化资源的目标。当保护问题被指定为组合或投资组合问题时，以及在不同的空间和时间尺度上考虑多个相互竞争的目标时，保护问题通常是高维的。尽管已经开发了诸如现代投资组合理论 (MPT) 之类的分析技术来解决这些复杂的问题，但用于执行这些方法的开源计算平台并不容易获得。我们提出了一个名为 SiteOpt 的用户友好 R 包，用于优化二元决策，同时明确考虑环境或经济不确定性以及决策者的风险承受能力。我们用空间明确的站点选择问题来说明包（即 空间保护规划），包括撤资（即出售资产）的选项，以考虑未来设计保护区的不确定性。该工具适用于空间和非空间问题，例如预算分配或物种选择。空间设计的约束和空间依赖性（例如站点之间的连通性）也可以在 SiteOpt 中指定。用户可以通过求解 Nash 讨价还价解决方案，基于两个相互竞争的目标来优化站点选择。重要的是，通过量化不确定性和资产空间相关性，可以将风险度量作为一个这样的目标，以与投资组合收益进行权衡。因此，SiteOpt 可用于在基于投资组合的空间优化中明确管理风险。该工具有助于在各种问题设置中做出决策，