Freshwater ecosystems are negatively affected by climate change and human interventions modifying together supply and demand of ecosystem services (ES). Research on ES focused on assessing risks arising from the interaction among both stressors, integrating empirical data with expert knowledge. This work aims at incorporating Bayesian Networks (BN) approaches into ES appraisal, identifying key factors driving changes and trade-offs among ES potential under different scenarios. Applying the designed BN to the Taro River basin (TRB) in Italy, the outcomes showed a limited space to improve ES potential, as well as trade-offs between water yield and nutrient retention services due to changes in precipitation and land use patterns. Moreover, the analysis of key input variables highlighted that precipitation is the main driver affecting provisioning services while land use for the regulating ones. The results imply a low capacity to provide services in the medium term for the TRB where water was exploited for multiple competing objectives. Therefore, “win-win” spatial planning and water management strategies are needed to improve freshwater ES potential. The designed BN model represents a valuable decision support tool to quickly perform ES assessment and to identify the most suitable management plan to maintain benefits from freshwater ecosystems.

淡水生态系统受到气候变化和人为干预的共同影响，共同改变了生态系统服务的供求关系。ES的研究侧重于评估两个压力源之间相互作用产生的风险，将经验数据与专家知识相结合。这项工作旨在将贝叶斯网络（BN）方法纳入ES评估中，确定在不同情况下驱动ES潜力变化和权衡的关键因素。将设计的BN应用于意大利的塔罗河流域（TRB），结果显示出有限的空间来提高ES潜力，并且由于降水量和土地利用方式的变化，水的产量和养分保留服务之间也需要权衡取舍。而且，对关键输入变量的分析表明，降水是影响供应服务的主要驱动力，而土地使用则是调节服务的主要驱动力。结果表明，从中期来看，TRB的水提供多种服务目标的能力很弱。因此，需要“双赢”的空间规划和水管理策略来提高淡水ES潜力。设计的BN模型代表了一种宝贵的决策支持工具，可以快速执行ES评估并确定最合适的管理计划，以维持淡水生态系统的收益。需要“双赢”的空间规划和水管理策略来提高淡水ES潜力。设计的BN模型代表了一种宝贵的决策支持工具，可以快速执行ES评估并确定最合适的管理计划，以维持淡水生态系统的收益。需要“双赢”的空间规划和水管理策略来提高淡水ES潜力。设计的BN模型代表了一种宝贵的决策支持工具，可以快速执行ES评估并确定最合适的管理计划，以维持淡水生态系统的收益。