The challenge of setting restoration targets for macroalgal forests under climate changes

The process of site selection and spatial planning has received scarce attention in the scientific literature dealing
with marine restoration, suggesting the need to better address how spatial planning tools could guide restoration
interventions.
In this study, for the first time, the consequences of adopting different restoration targets and criteria on
spatial restoration prioritization have been assessed at a regional scale, including the consideration of climate
changes. We applied the decision-support tool Marxan, widely used in systematic conservation planning on
Mediterranean macroalgal forests. The loss of this habitat has been largely documented, with limited evidences
of natural recovery. Spatial priorities were identified under six planning scenarios, considering three main
restoration targets to reflect the objectives of the EU Biodiversity Strategy for 2030.
Results show that the number of suitable sites for restoration is very limited at basin scale, and targets are only
achieved when the recovery of 10% of regressing and extinct macroalgal forests is planned. Increasing targets
translates into including unsuitable areas for restoration in Marxan solutions, amplifying the risk of ineffective
interventions.
Our analysis supports macroalgal forests restoration and provides guiding principles and criteria to strengthen
the effectiveness of restoration actions across habitats. The constraints in finding suitable areas for restoration
are discussed, and recommendations to guide planning to support future restoration interventions are also
included.
The dataset produced for this study shows the information used as input for Marxan analysis. Rows of the dataset correspond to Planning Units (PU), i.e., the set of potential sites from which to select restoration areas. For each PU the following elements are provided: identification number (ID); longitude and latitude (X and Y); Habitat Suitability Model classification: values ranging in the [0,1] interval. PUs with values < 0.61 are classified as unsuitable for restoration; the frequency of Sea Surface Temperature Anomalies expressed as a percentage. PUs with values > 75 are classified as unsuitable for restoration; the level of Habitat Richness. Values ranging in the [0,1] interval; the distance to the closest divining facilities (in km); the distance to the closest location with previous experience on restoration activities (in km); the distance to the closest port (in km); distance to the closest International, National and Regional Marine Protect Areas (in km); the distance to the closest Marine Institute (CIESM), Marine Station (MARS) or Specially Protected Areas Regional Activity Centres (SPA/RAC) (in km); the distance to the closest facility (in km); the cost of restoration (in €); the status: 0 for included PUs, 3 for locked-out PUs; the restoration features; the reason for exclusion from the analysis.

在海洋恢复领域的科学文献中，对于场址选择和空间规划的研究寥寥无几，这暗示了有必要更深入地探讨空间规划工具如何指导恢复干预措施。在本研究中，首次对采用不同恢复目标和标准对区域尺度上空间恢复优先级的后果进行了评估，其中包括对气候变化的考虑。我们应用了广泛用于地中海大型海藻森林系统保护规划决策支持工具Marxan。该栖息地的丧失已得到大量记录，而自然恢复的证据有限。在考虑了三个主要恢复目标以反映欧盟2030年生物多样性战略目标的情况下，确定了六种规划情景下的空间优先级。结果显示，在流域尺度上，适宜恢复的场址数量极为有限，只有在计划恢复10%的衰退和灭绝的大型海藻森林时，目标才能得以实现。提高目标意味着在Marxan解决方案中纳入不适宜的恢复区域，从而放大了干预措施无效的风险。我们的分析支持了大型海藻森林的恢复，并提供了指导原则和标准，以加强跨栖息地恢复行动的有效性。讨论了寻找适宜恢复区域的限制，并包含了指导规划以支持未来恢复干预的建议。本研究产生的数据集展示了作为Marxan分析输入使用的信息。数据集的行对应于规划单元（PU），即从中选择恢复区域的可能性场址集合。对于每个PU，提供以下元素：识别编号（ID）；经纬度（X和Y）；栖息地适宜性模型分类：[0,1]区间内的值。值小于0.61的PU被归类为不适宜恢复；海表温度异常的频率，以百分比表示。值大于75的PU被归类为不适宜恢复；栖息地丰富度水平。[0,1]区间内的值；距离最近的取水设施的距离（公里）；距离具有先前恢复活动经验的最近地点的距离（公里）；距离最近的港口的距离（公里）；距离最近的国际、国家和区域海洋保护区（公里）；距离最近的海洋研究所（CIESM）、海洋站（MARS）或特别保护区区域活动中心（SPA/RAC）的距离（公里）；距离最近的设施的距离（公里）；恢复成本（欧元）；状态：0表示包含的PU，3表示被锁定的PU；恢复特征；排除分析的原因。