Department of Environmental Sciences, Informatics and Statistics, University Ca' Foscari Venice, I-30170 Venice, Italy; CMCC Foundation - Euro-Mediterranean Center on Climate Change, Italy.
Department of Environmental Sciences, Informatics and Statistics, University Ca' Foscari Venice, I-30170 Venice, Italy; CMCC Foundation - Euro-Mediterranean Center on Climate Change, Italy; University School for Advanced Studies Pavia, Piazza della Vittoria 15, Pavia 27100, Italy.
Sci Total Environ. 2024 Dec 10;955:176803. doi: 10.1016/j.scitotenv.2024.176803. Epub 2024 Oct 9.
The growing environmental risks induced by interacting climate and human-induced pressures threaten the survival and growth of marine coastal ecosystems (MCEs) and the ecosystem services they provide. Nature-based solutions (NBS), consisting of ecosystem-based approaches, have emerged as vital tools for climate adaptation and mitigation facing biodiversity loss and societal challenges. Identifying suitable environmental conditions for implementing Blue-NBS in marine coastal areas is a key priority to drive robust and cost-effective nature-based adaptation pathways. This study developed a suitability model for Blue-NBS, with a specific focus on Posidonia oceanica meadows in the Mediterranean Sea under a baseline scenario. GIS-based Multiple Criteria Decision Analysis (MCDA) was applied for data integration and prioritization of different environmental variables in geomorphological (e.g., depth), water quality (WQ) (e.g., salinity), and climatic (e.g., thermal stress) sub-groups. Suitability classes and scores for each variable were determined using statistical distributions, ensuring a data-driven approach to defining environmental suitability. Variables' weights were derived from the Analytic Hierarchy Process (AHP) based on expert judgment and then combined with scores to generate suitability maps for managing Blue-NBS on seagrasses. Depth was found to be the most dominant environmental variable, with shallow areas (e.g., Northern Adriatic, Gulf of Gabés) showing higher suitability. The southern part of the Mediterranean (e.g., Egypt) reported relatively low scores for both climate and WQ, while the Northern Adriatic had the lowest WQ scores. This study represents the first attempt to evaluate Blue-NBS suitability for seagrass meadows at the eco-regional scale with geomorphologic, WQ, and climatic variables, providing decision support for the selection and allocation of Blue-NBS in different environmental settings. The resulting environmental suitability maps represent a basis for the integration of socio-economic and governance-related indicators into a more complex, multi-tier approach to support NBS mainstreaming.
交互气候和人为压力引起的环境风险不断增加,威胁着海洋沿海生态系统 (MCE) 的生存和增长及其提供的生态系统服务。基于自然的解决方案 (NBS),包括基于生态系统的方法,已成为应对生物多样性丧失和社会挑战的气候适应和缓解的重要工具。确定在海洋沿海地区实施蓝色 NBS 的适宜环境条件是推动强大且具有成本效益的基于自然的适应途径的关键优先事项。本研究开发了一个蓝色 NBS 的适宜性模型,重点是地中海的波西多尼亚海草床在基线情景下。基于 GIS 的多标准决策分析 (MCDA) 用于数据集成和地理形态学 (例如,深度)、水质 (WQ) (例如,盐度) 和气候 (例如,热应激) 子组中的不同环境变量的优先级排序。使用统计分布确定每个变量的适宜性等级和分数,确保了定义环境适宜性的基于数据的方法。变量的权重是根据专家判断从层次分析法 (AHP) 中得出的,然后与分数结合生成用于管理海草上蓝色 NBS 的适宜性图。深度被发现是最主要的环境变量,浅水区 (例如,亚得里亚海北部,加贝斯湾) 显示出更高的适宜性。地中海的南部地区 (例如,埃及) 气候和 WQ 的得分都相对较低,而亚得里亚海北部的 WQ 得分最低。本研究首次尝试在生态区域尺度上评估基于自然的蓝色 NBS 对海草床的适宜性,使用地理形态学、WQ 和气候变量为在不同环境条件下选择和分配基于自然的蓝色 NBS 提供决策支持。由此产生的环境适宜性图为将社会经济和治理相关指标纳入更复杂的多层方法以支持 NBS 主流化提供了基础。