Convertino Matteo, Valverde L James
Department of Agricultural and Biological Engineering-Institute of Food and Agricultural Sciences, University of Florida, Gainesville, Florida, United States of America ; Florida Climate Institute, University of Florida, Gainesville, Florida, United States of America.
PLoS One. 2013 Jun 18;8(6):e65056. doi: 10.1371/journal.pone.0065056. Print 2013.
Management of natural resources in coastal ecosystems is a complex process that is made more challenging by the need for stakeholders to confront the prospect of sea level rise and a host of other environmental stressors. This situation is especially true for coastal military installations, where resource managers need to balance conflicting objectives of environmental conservation against military mission. The development of restoration plans will necessitate incorporating stakeholder preferences, and will, moreover, require compliance with applicable federal/state laws and regulations. To promote the efficient allocation of scarce resources in space and time, we develop a portfolio decision analytic (PDA) framework that integrates models yielding policy-dependent predictions for changes in land cover and species metapopulations in response to restoration plans, under different climate change scenarios. In a manner that is somewhat analogous to financial portfolios, infrastructure and natural resources are classified as human and natural assets requiring management. The predictions serve as inputs to a Multi Criteria Decision Analysis model (MCDA) that is used to measure the benefits of restoration plans, as well as to construct Pareto frontiers that represent optimal portfolio allocations of restoration actions and resources. Optimal plans allow managers to maintain or increase asset values by contrasting the overall degradation of the habitat and possible increased risk of species decline against the benefits of mission success. The optimal combination of restoration actions that emerge from the PDA framework allows decision-makers to achieve higher environmental benefits, with equal or lower costs, than those achievable by adopting the myopic prescriptions of the MCDA model. The analytic framework presented here is generalizable for the selection of optimal management plans in any ecosystem where human use of the environment conflicts with the needs of threatened and endangered species. The PDA approach demonstrates the advantages of integrated, top-down management, versus bottom-up management approaches.
沿海生态系统中自然资源的管理是一个复杂的过程，利益相关者需要面对海平面上升以及一系列其他环境压力因素，这使得该过程更具挑战性。对于沿海军事设施而言，情况尤其如此，在这些设施中，资源管理者需要在环境保护的相互冲突目标与军事任务之间取得平衡。恢复计划的制定将需要纳入利益相关者的偏好，此外，还需要遵守适用的联邦/州法律法规。为了促进稀缺资源在空间和时间上的有效分配，我们开发了一个投资组合决策分析（PDA）框架，该框架整合了一些模型，这些模型能够针对不同气候变化情景下恢复计划所导致的土地覆盖和物种集合种群变化生成与政策相关的预测。在某种程度上类似于金融投资组合，基础设施和自然资源被归类为需要管理的人力和自然资产。这些预测作为多标准决策分析模型（MCDA）的输入，该模型用于衡量恢复计划的效益，并构建代表恢复行动和资源的最优投资组合分配的帕累托前沿。最优计划使管理者能够通过对比栖息地的整体退化以及物种减少可能增加的风险与任务成功的效益，来维持或增加资产价值。PDA框架得出的恢复行动的最优组合使决策者能够以等于或低于采用MCDA模型短视方案所能实现的成本，实现更高的环境效益。这里提出的分析框架可推广用于在任何人类对环境的利用与受威胁和濒危物种的需求相冲突的生态系统中选择最优管理计划。PDA方法展示了综合的自上而下管理相对于自下而上管理方法的优势。
