Shallow seafloor marine litter (ML) is the least studied component of ML, and a better understanding of its distribution and accumulation patterns is needed to develop efficient management practices. Abundance and composition of seafloor ML were quantified in two eastern Adriatic Natura 2000 sites (Vis Island and Pakleni Islands), applying a structured sampling design to test whether the intensity of nautical tourism or exposure to prevailing winds and currents are significant drivers determining the ML distribution on shallow, coastal seafloor. ML was widespread and present in considerable amounts across the entire studied area, regardless of the remoteness from most known potential ML sources. Tourism intensity and exposure seem not to be significant predictors of ML accumulation in the investigated Natura 2000 sites. ML abundances displayed large small-scale spatial variation, while for ML composition at a larger scale, regional differences between the two Natura 2000 sites were detected. The Pakleni Islands are mainly polluted by glass items, suggesting a local vessel-based source. The ML composition on Vis Island, with a predominance of plastics, is more determined by long-distance transport. The study indicates the complexity and multi-layeredness of processes driving the patterns of seafloor ML accumulation. Hence, it is suggested to mitigate the issue by addressing the root causes: inadequate waste management and lack of public awareness.

浅层海底垃圾是ML中最少研究的组成部分，因此需要对它的分布和累积模式有更好的了解，以开发有效的管理实践。在两个亚得里亚海纳图拉东部2000年地点（维斯岛和帕克利尼群岛）对海底ML的含量和组成进行了定量，采用结构化抽样设计来测试航海旅游的强度或暴露于盛行风和洋流是否是确定ML分布的重要驱动力在浅的沿海海底。ML遍及整个研究区域，并且存在很多，而与大多数已知的潜在ML来源相距遥远。在被调查的Natura 2000站点中，旅游强度和暴露程度似乎不是ML积累的重要预测指标。ML的丰度显示出较大的小范围空间变化，而对于更大范围的ML组成，则检测到两个Natura 2000站点之间的区域差异。帕克利尼群岛主要被玻璃物品污染，这表明是当地船只的来源。维斯岛（Vis Island）上的ML成分以塑料为主，更多地取决于长途运输。研究表明，驱动海底ML积累模式的过程非常复杂且具有多层性。因此，建议通过解决根本原因来缓解该问题：废物管理不足和公众意识不足。建议使用本地船只资源。维斯岛（Vis Island）上的ML成分以塑料为主，更多地取决于长途运输。研究表明，驱动海底ML积累模式的过程非常复杂且具有多层性。因此，建议通过解决根本原因来缓解该问题：废物管理不足和公众意识不足。建议使用本地船只资源。维斯岛（Vis Island）上的ML成分以塑料为主，更多地取决于长途运输。研究表明，驱动海底ML积累模式的过程非常复杂且具有多层性。因此，建议通过解决根本原因来缓解该问题：废物管理不足和公众意识不足。