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Elevating local knowledge through participatory modeling: active community engagement in restoration planning in coastal Louisiana

机译:通过参与式建模提升当地知识:在沿海路易斯安那州的恢复规划中的积极社区参与

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Numerical modeling efforts in support of restoration and protection activities in coastal Louisiana have traditionally been conducted externally to any stakeholder engagement processes. This separation has resulted in planning- and project-level models built solely on technical observation and analysis of natural processes. Despite its scientific rigor, this process often fails to account for the knowledge, values, and experiences of local stakeholders that often contextualizes a modeled system. To bridge this gap, a team of natural and social scientists worked directly with local residents and resource users to develop a participatory modeling approach to collect and utilize local knowledge about the Breton Sound Estuary in southeast Louisiana, USA. Knowledge capture was facilitated through application of a local knowledge mapping methodology designed to catalog local understanding of current and historical conditions within the estuary and identify desired ecological and hydrologic end states. The results of the mapping endeavor informed modeling activities designed to assess the applicability of the identified restoration solutions. This effort was aimed at increasing stakeholder buy-in surrounding the utility of numerical models for planning and designing coastal protection and restoration projects and included an ancillary outcome aimed at elevating stakeholder empowerment regarding the design of nature-based restoration solutions and modeling scenarios. This intersection of traditional science and modeling activities with the collection and analysis of traditional ecological knowledge proved useful in elevating the confidence that community members had in modeled restoration outcomes.
机译:在沿海路易斯安那州沿海路易斯安那州的恢复和保护活动支持的数值建模努力传统上是对任何利益相关者参与进程进行的。这种分离导致规划和项目级模型仅基于技术观察和自然过程分析。尽管它科学严谨,但该过程往往无法解释当地利益相关者的知识,价值观和经验,这些利益相关者通常会扩大建模系统。为了弥补这一差距,一支自然和社会科学家团队直接与当地居民和资源用户一起使用,以开发参与式建模方法,以收集和利用美国东南部的Breton Sound Estuary的当地知识。通过应用旨在目录到河口内的当前和历史条件的本地知识映射方法,旨在促进知识捕获,并识别所需的生态和水文结束状态。映射的结果努力提供了明智的建模活动,旨在评估所识别的恢复解决方案的适用性。这项努力旨在增加利益攸关方买入规划和设计沿海保护和恢复项目的数值模型的效用,并包括提升利益攸关方赋权的辅助结果,了解基于自然的恢复解决方案和建模情景。这种与传统生态知识的收集和分析的传统科学与建模活动证明,在提升社区成员在建模恢复成果中的信心有用。

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