Data from: Filling in socio‐ecological knowledge gaps to support marine spatial planning in data‐scarce areas: Example from Zanzibar

Marine spatial planning (MSP) is one of the most important tools for ensuring sustainable use of marine areas. Although MSP is a well‐established method, its adoption in rapidly developing countries is a challenge. One of the main concerns is data adequacy, as the MSP process typically requires a large amount of spatial data on human activities, biodiversity, and socio‐ecological interactions within the planning area. Drawing from an institutional cooperation project in Zanzibar, Tanzania, we share our experience and demonstrate how to fill in socio‐ecological data gaps to support the development of MSP in areas with limited data availability. We developed a rapid and cost‐effective system for collecting biological data, which, together with remote sensing and place‐based participatory mapping, helped formulate the first pilot ecologically informed MSP for Zanzibar. By sharing our results and experiences, we aim to provide best practices, lessons learned, and recommendations for future projects with a similar ecological setting and socio‐economic context. This Zenodo deposit includes the collected biological inventory data, PGIS survey data, habitat models produced based on Sentinel-2 images and habitat inventories, and related scripts. Details of the data are described in the article Filling in socio‐ecological knowledge gaps to support marine spatial planning in data‐scarce areas: Example from Zanzibar (https://doi.org/10.1111/csp2.13284).海洋空间规划（Marine Spatial Planning, MSP）是保障海洋区域可持续利用的关键工具之一。尽管海洋空间规划已是成熟的方法论体系，但其在快速发展中国家的推广仍面临诸多挑战。其中一项核心关切为数据充足性问题：海洋空间规划流程通常需要规划区域内大量关于人类活动、生物多样性及社会-生态交互作用的空间数据。 依托坦桑尼亚桑给巴尔的一项机构合作项目，我们分享实践经验，并展示如何填补社会-生态数据缺口，以支撑数据匮乏地区的海洋空间规划开发工作。我们研发了一套快速且高性价比的生物数据采集系统，结合遥感技术与基于场所的参与式绘图方法，助力桑给巴尔完成了首个具备生态参考依据的试点海洋空间规划方案。通过分享研究成果与实践经验，我们旨在为具有相似生态环境与社会经济背景的未来项目提供最佳实践范式、经验教训与针对性建议。 本Zenodo存档包含采集得到的生物清查数据、参与式地理信息系统（Participatory Geographic Information System, PGIS）调查数据、基于Sentinel-2影像与生境清查结果构建的生境模型，以及相关配套脚本。数据详情已发表于论文《填补数据匮乏地区的社会-生态知识缺口以支撑海洋空间规划：以桑给巴尔为例》（https://doi.org/10.1111/csp2.13284）。