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.在海洋修复相关的科学文献中，选址与空间规划的相关研究仍较为匮乏，这凸显了亟待深入探究空间规划工具如何有效指导修复行动的必要性。本研究首次在区域尺度上评估了采用不同修复目标与准则对空间修复优先级排序的影响，同时纳入了气候变化的考量因素。我们将广泛应用于系统性保护规划的决策支持工具Marxan，应用于地中海大型海藻林的修复研究中。该栖息地的退化消失已被大量文献记录，且自然恢复的相关证据十分有限。本研究基于六个规划情景，结合三项核心修复目标以呼应《欧盟2030年生物多样性战略》的目标，识别出了空间修复优先级。研究结果显示，在海盆尺度上，可供修复的适宜位点数量极少，仅当规划恢复10%的退化及灭绝型大型海藻林时，方能达成预设修复目标。提升修复目标则会导致Marxan的优化方案中纳入不适宜修复的区域，进而增大修复行动低效的风险。本研究可为大型海藻林修复提供支撑，并为提升各类生境修复行动的有效性提供指导原则与评判准则。研究还探讨了筛选适宜修复位点所面临的限制因素，并给出了指导规划以支撑未来修复行动的相关建议。本研究构建的数据集包含了用于Marxan分析的全部输入信息。数据集的每一行对应一个规划单元（Planning Unit, PU），即用于遴选修复区域的潜在位点集合。每个规划单元均包含以下信息：唯一识别编号（ID）；经纬度坐标（X、Y）；生境适宜性模型（Habitat Suitability Model）分类结果：取值区间为[0,1]，其中取值小于0.61的规划单元被归类为不适宜修复；以百分比表示的海表温度异常（Sea Surface Temperature Anomalies）发生频率，取值大于75的规划单元被归类为不适宜修复；生境丰富度（Habitat Richness）水平，取值区间为[0,1]；至最近探测设施的距离（单位：km）；至最近具备修复活动经验的场地的距离（单位：km）；至最近港口的距离（单位：km）；至最近国际、国家及区域海洋保护区（Marine Protect Areas）的距离（单位：km）；至最近海洋研究所（CIESM）、海洋站（MARS）或特别保护区区域活动中心（SPA/RAC）的距离（单位：km）；至最近相关设施的距离（单位：km）；修复成本（单位：欧元€）；状态标识：0代表纳入分析的规划单元，3代表锁定排除的规划单元；修复特征参数；被排除于分析之外的原因。