CARES, University of Missouri, Columbia, Agricultural Economics, 212 Mumford Hall University of Missouri, Columbia, MO 65211, USA.
Environ Manage. 2011 Jul;48(1):142-9. doi: 10.1007/s00267-011-9648-x. Epub 2011 Mar 4.
Wildlife managers have little or no control over climate change. However, they may be able to alleviate potential adverse impacts of future climate change by adaptively managing wildlife for climate change. In particular, wildlife managers can evaluate the efficacy of compensatory management actions (CMAs) in alleviating potential adverse impacts of future climate change on wildlife species using probability-based or fuzzy decision rules. Application of probability-based decision rules requires managers to specify certain probabilities, which is not possible when they are uncertain about the relationships between observed and true ecological conditions for a species. Under such uncertainty, the efficacy of CMAs can be evaluated and the best CMA selected using fuzzy decision rules. The latter are described and demonstrated using three constructed cases that assume: (1) a single ecological indicator (e.g., population size for a species) in a single time period; (2) multiple ecological indicators for a species in a single time period; and (3) multiple ecological conditions for a species in multiple time periods.
野生动物管理者对气候变化几乎没有或完全没有控制能力。然而，他们可以通过适应管理野生动物来减轻未来气候变化的潜在不利影响。具体来说，野生动物管理者可以使用基于概率或模糊决策规则来评估补偿管理措施（CMA）在减轻未来气候变化对野生动物物种的潜在不利影响方面的效果。应用基于概率的决策规则要求管理者指定某些概率，而当他们对物种的观测和真实生态条件之间的关系不确定时，这是不可能的。在这种不确定性下，可以使用模糊决策规则来评估 CMA 的效果，并选择最佳的 CMA。本文使用三个构造案例来描述和演示后者，假设：（1）单一时期的单一生态指标（例如，物种的种群规模）；（2）单一时期的多个生态指标；以及（3）多个时期的多个生态条件。
