Ecological restoration is increasingly being upscaled to larger spatial scales of tens to hundreds of kilometers. Yet the complex logistics and high costs of ecological restoration mean that actions must be placed strategically at local scales of tens of meters to maximize ecological benefits and reduce socioeconomic costs. Despite the purported use of systematic planning tools for allocating restoration effort, the uptake and implementation of data-driven restoration planning and ecological goal setting remains poor in many restoration programs. Here we demonstrate how the sequential workflows of systematic conservation planning can be translated to restoration at two spatial scales to enhance estuarine fisheries in eastern Australia. We select estuaries where restoration is feasible and recommended based on quantitative regional ecological goals (i.e. regional-scale prioritization), and then identify potential restoration sites at smaller spatial scales within estuaries based on the principles of spatial ecology to ensure that the success and benefits of restoration are maximized (i.e. local-scale prioritization). At the regional scale, we identified four levels of restoration priorities (very high, high, intermediate, and low) using quantitative ecological goals and the current ecological understanding of each system. At the local scale, we used spatially explicit Bayesian belief networks to identify sites that maximize restoration outcomes based on the environmental niche of habitat-forming species and the spatial configuration of habitats that maximizes their use by fish. We show that using systematic frameworks can become an essential tool to optimize restoration investments at multiple scales as efforts upscale globally.

中文翻译：

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应用系统的保护规划来改善多个空间尺度的恢复行动的分配

生态恢复正日益扩大到数十至数百公里的更大空间尺度。然而，生态恢复的复杂物流和高成本意味着必须在数十米的局部范围内战略性地采取行动，以最大限度地提高生态效益并降低社会经济成本。尽管据称使用系统规划工具来分配恢复工作，但在许多恢复计划中，数据驱动的恢复规划和生态目标设定的采用和实施仍然很差。在这里，我们展示了如何将系统保护规划的连续工作流程转化为两个空间尺度的恢复，以加强澳大利亚东部的河口渔业。我们根据定量的区域生态目标（即区域尺度优先排序）选择和推荐恢复可行的河口，然后根据空间生态学原理在河口内较小的空间尺度上识别潜在的恢复点，以确保成功和效益。恢复最大化（即本地规模的优先级）。在区域范围内，我们使用定量生态目标和每个系统的当前生态理解确定了四个级别的恢复优先级（非常高、高、中和低）。在局部范围内，我们使用空间明确的贝叶斯信念网络，根据形成栖息地的物种的环境生态位和最大限度地利用鱼类的栖息地空间配置来确定最大限度地恢复结果的地点。