从立项到数据入库的年度节奏Annual rhythm from approval to data deposit
E-Tides 的申报与评审同时确认项目的指南方向和科学位置。每个项目都对应一个或多个核心过程：协同演化、临界要素、临界过程、级联效应、趋势预测或可持续路径。这样的定位使观测、模型和区域结论汇入同一比较体系。E-Tides application and review identify both a project's fit to the call and its scientific position. Each project relates to one or more core processes: co-evolution, tipping elements, tipping processes, cascading effects, trajectory prediction, or sustainable pathways. This positioning brings observations, models, and regional conclusions into one comparison system.
数据共享从项目早期开始，与观测设计、变量定义和质量控制同步推进。岸线、潮滩、C/N/P 通量、溶解氧、叶绿素、pH、生态群落、风暴潮和社会经济暴露等变量，在采集阶段就同步记录时间、空间、方法和不确定性。数据入库后，直接连接区域模式验证、数字孪生更新和跨区域综合分析。Data sharing begins early and moves together with observation design, variable definition, and quality control. Shoreline, tidal flats, C/N/P fluxes, dissolved oxygen, chlorophyll, pH, ecological communities, storm surge, and socioeconomic exposure are recorded with time, space, method, and uncertainty from the moment they are collected. Once deposited, the data connect directly to regional model validation, digital-twin updates, and cross-region synthesis.
评审和年度检查关注两个层面：科学进展沿核心问题推进，数据与模式资产达到复用条件。前者涉及理论判断、区域证据和机制链条，后者涉及元数据、质量控制、版本记录和引用方式。两者同时推进，年度交流才能形成实质性的科学比较。Review and annual checks focus on two levels: scientific progress along the core questions, and reusable data and model assets. The first level concerns theory, regional evidence, and mechanism chains; the second concerns metadata, quality control, version records, and citation practice. Moving both together turns annual exchange into substantive scientific comparison.
年度节点Annual milestones
- 项目申报、年度检查、阶段评估和专家咨询Applications, annual checks, staged reviews, and expert consultation.
- 观测数据、遥感产品、模式输出、社会经济数据和治理信息入库Observation data, remote sensing products, model outputs, socioeconomic data, and governance information.
- 会议报名、材料提交、成果登记和开放引用记录Meeting registration, material submission, outcome registration, and open citation records.
数据记录的重点Data-record priorities
每个数据产品同时记录空间范围、时间范围、变量定义、处理流程、质量控制、版本号和访问权限。这样的记录让数据来源、处理过程和引用方式能够逐项追踪，也让同一变量在不同重点区域之间具有比较意义。Each data product records spatial scope, temporal scope, variable definitions, processing workflow, quality control, version, and access level together. This makes sources, processing history, and citation traceable, while allowing the same variable to be compared across focus regions.
数据共享的核心是让观测、遥感、模式和社会经济信息在同一变量体系中相互校验。当数据能够复算、复用和引用，临界前兆、级联效应和适应路径的判断便具有跨团队讨论的基础。The core of data sharing is mutual checking among observations, remote sensing, models, and socioeconomic information within the same variable system. When data can be recomputed, reused, and cited, tipping signals, cascades, and adaptive pathways gain a shared basis for cross-team discussion.