Assessment of the response of pollinator abundance to environmental pressures using structured expert elicitation
Assessment of the response of pollinator abundance to environmental pressures using structured expert elicitation
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DOI：
10.1080/00218839.2018.1494891
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发表时间：
2018-10-20
影响因子：
1.9
通讯作者：
Carreck, Norman L.
中科院分区：
文献类型：
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作者：
Barons, Martine J.;Hanea, Anca M.;Carreck, Norman L.
政策制定者在复杂、多方面、动态的环境（如处理生态系统服务的环境）中做出政策选择时，往往需要依赖具有不同专业领域的专家。对于希望做出最有利于传粉媒介丰富度和授粉服务的循证决策的决策者来说，面临的问题之一是如何获取所需的信息和证据，以及如何将其结合起来制定和评估候选政策。当多种因素共同产生影响时，情况就更加复杂了。影响蜜蜂（Apis mellifera）、野生蜜蜂和其他传粉媒介的生存和授粉能力的压力有很好的记录，但不完整。为了评估各种候选政策选择的潜在有效性，迫切需要量化各种因子组合对授粉生态系统服务的影响。使用高质量的实验证据是最可靠的方法，但该系统的关键方面可能不适合实验，或者可能基于成本、时间和精力而令人望而却步。在这种情况下，有可能通过使用结构化专家启发获得所需的证据，这是一种定量描述不确定数量的知识状态的方法。在这里，我们报告并讨论了结构化专家启发的新用途的输出，旨在量化在各种天气，疾病和栖息地情景下良好传粉者丰度的概率。
Policy-makers often need to rely on experts with disparate fields of expertise when making policy choices in complex, multi-faceted, dynamic environments such as those dealing with ecosystem services. For policy-makers wishing to make evidence-based decisions which will best support pollinator abundance and pollination services, one of the problems faced is how to access the information and evidence they need, and how to combine it to formulate and evaluate candidate policies. This is even more complex when multiple factors provide influence in combination. The pressures affecting the survival and pollination capabilities of honey bees (Apis mellifera), wild bees, and other pollinators are well documented, but incomplete. In order to estimate the potential effectiveness of various candidate policy choices, there is an urgent need to quantify the effect of various combinations of factors on the pollination ecosystem service. Using high-quality experimental evidence is the most robust approach, but key aspects of the system may not be amenable to experimentation or may be prohibitive based on cost, time and effort. In such cases, it is possible to obtain the required evidence by using structured expert elicitation, a method for quantitatively characterizing the state of knowledge about an uncertain quantity. Here we report and discuss the outputs of the novel use of a structured expert elicitation, designed to quantify the probability of good pollinator abundance given a variety of weather, disease, and habitat scenarios.