Abstract Ponds are common features on salt marshes, yet it is unclear how they affect large-scale marsh evolution. We developed a spatially explicit model that combines cellular automata for pond formation, expansion, and drainage, and partial differential equations for elevation dynamics. We use the mesotidal Barnstable marsh (MA, USA) as a case study, for which we measured pond expansion rate by remote sensing analysis over a 41-year time span. We estimated pond formation rate by comparing observed and modeled pond size distribution, and predicted pond deepening by comparing modeled and measured pond depth. The Barnstable marsh is currently in the pond recovery regime, i.e.,every pond revegetates and recovers the necessary elevation to support plant growth after re-connecting to the channel network. This pond dynamic creates an equivalent (i.e.,spatially and temporally averaged over the whole marsh) 0.5–2 mm/yr elevation loss that needs to be supplemented by excess vertical accretion. We explore how the pond regime would change with decreased sediment supply and increased relative sea-level rise (RSLR) rate, focusing on the case in which the vegetated marsh keeps pace with RSLR. When the RSLR rate remains below the minimum unvegetated deposition rate, the pond dynamics is nearly unaltered and ponds always occupy ~10% of the marsh area. However, when RSLR rate exceeds this threshold, the ponds in the marsh interior – which receive the least amount of suspended sediment – do not recover after drainage. These ponds transition to mudflats and permanently occupy up to 30% of the marsh area depending on RSLR rate. For marshes with a small tidal range, such as the microtidal Sage Lot Pond marsh on the opposite side of the peninsula from Barnstable marsh, high RSLR rates could bring every portion of the marsh into the pond runaway regime, with the whole marsh eventually converting into mudflats. In this regime, the existing marsh would disappear within centuries to millennia depending on the RSLR rate. Because of the spatial and temporal components of marsh evolution, a single RSLR threshold value applied across the entire marsh landscape provides a limited description of the marsh vulnerability to RSLR.

中文翻译：

---

新英格兰盐沼沼泽池空间动态建模

摘要 池塘是盐沼的共同特征，但对大规模盐沼演化的影响尚不清楚。我们开发了一个空间显式模型，该模型结合了用于池塘形成、扩展和排水的元胞自动机以及用于高程动态的偏微分方程。我们使用中间潮汐 Barnstable 沼泽（美国马萨诸塞州）作为案例研究，为此我们通过遥感分析测量了 41 年时间跨度内的池塘扩张率。我们通过比较观察到的和模拟的池塘大小分布来估计池塘形成率，并通过比较模拟和测量的池塘深度来预测池塘深度。Barnstable 沼泽目前处于池塘恢复状态，即每个池塘重新植被并恢复必要的海拔，以在重新连接到渠道网络后支持植物生长。这个池塘动态创建了一个等效的（即，整个沼泽的空间和时间平均) 0.5-2 毫米/年的海拔损失，需要通过额外的垂直增加来补充。我们探讨了池塘状况如何随着沉积物供应的减少和相对海平面上升 (RSLR) 速率的增加而变化，重点关注植被沼泽与 RSLR 保持同步的情况。当 RSLR 率保持在最低无植被沉积率以下时，池塘动态几乎没有改变，池塘总是占据约 10% 的沼泽面积。然而，当 RSLR 率超过这个阈值时，沼泽内部的池塘——接收最少数量的悬浮沉积物——在排水后不会恢复。这些池塘过渡到泥滩，并根据 RSLR 率永久占据多达 30% 的沼泽面积。对于潮差较小的沼泽，例如半岛对面巴恩斯特布尔沼泽的微潮 Sage Lot Pond 沼泽，高 RSLR 率可能会使沼泽的每一部分都进入池塘失控状态，整个沼泽最终变成泥滩。在这种情况下，现有的沼泽将在数百到数千年内消失，具体取决于 RSLR 率。由于沼泽演化的空间和时间组成部分，应用于整个沼泽景观的单一 RSLR 阈值提供了对 RSLR 对沼泽脆弱性的有限描述。现有的沼泽将在数百到数千年内消失，具体取决于 RSLR 率。由于沼泽演化的空间和时间组成部分，应用于整个沼泽景观的单一 RSLR 阈值提供了对 RSLR 对沼泽脆弱性的有限描述。现有的沼泽将在数百到数千年内消失，具体取决于 RSLR 率。由于沼泽演化的空间和时间组成部分，应用于整个沼泽景观的单一 RSLR 阈值提供了对 RSLR 对沼泽脆弱性的有限描述。