Modeled Sea Level Rise Impacts on Coastal Ecosystems at Six Major Estuaries on Florida’s Gulf Coast: Implications for Adaptation Planning

The Sea Level Affecting Marshes Model (SLAMM) was applied at six major estuaries along Florida’s Gulf Coast (Pensacola Bay, St. Andrews/Choctawhatchee Bays, Apalachicola Bay, Southern Big Bend, Tampa Bay and Charlotte Harbor) to provide quantitative and spatial information on how coastal ecosystems may change with sea level rise (SLR) and to identify how this information can be used to inform adaption planning. High resolution LiDAR-derived elevation data was utilized under three SLR scenarios: 0.7 m, 1 m and 2 m through the year 2100 and uncertainty analyses were conducted on selected input parameters at three sites. Results indicate that the extent, spatial orientation and relative composition of coastal ecosystems at the study areas may substantially change with SLR. Under the 1 m SLR scenario, total predicted impacts for all study areas indicate that coastal forest (-69,308 ha; -18%), undeveloped dry land (-28,444 ha; -2%) and tidal flat (-25,556 ha; -47%) will likely face the greatest loss in cover by the year 2100. The largest potential gains in cover were predicted for saltmarsh (+32,922 ha; +88%), transitional saltmarsh (+23,645 ha; na) and mangrove forest (+12,583 ha; +40%). The Charlotte Harbor and Tampa Bay study areas were predicted to experience the greatest net loss in coastal wetlands The uncertainty analyses revealed low to moderate changes in results when some numerical SLAMM input parameters were varied highlighting the value of collecting long-term sedimentation, accretion and erosion data to improve SLAMM precision. The changes predicted by SLAMM will affect exposure of adjacent human communities to coastal hazards and ecosystem functions potentially resulting in impacts to property values, infrastructure investment and insurance rates. The results and process presented here can be used as a guide for communities vulnerable to SLR to identify and prioritize adaptation strategies that slow and/or accommodate the changes underway.

海平面影响湿地模型（Sea Level Affecting Marshes Model, SLAMM）被应用于佛罗里达州墨西哥湾沿岸的六大河口——彭萨科拉湾、圣安德鲁斯/乔克托奇湾、阿巴拉契科拉湾、南大本德区域、坦帕湾与夏洛特港，旨在获取海岸生态系统随海平面上升（Sea Level Rise, SLR）发生演变的定量与空间信息，并探究此类信息如何服务于适应规划的决策参考。研究采用了截至2100年的三种海平面上升情景（0.7米、1米与2米）下的高分辨率激光雷达（Light Detection and Ranging, LiDAR）衍生高程数据，并针对三个选定站点的输入参数开展了不确定性分析。研究结果显示，研究区域内海岸生态系统的分布范围、空间格局与相对组成可能随海平面上升发生显著改变。在1米海平面上升情景下，至2100年时所有研究区域的总预估影响表明，海岸森林（减少69308公顷，降幅18%）、未开发旱地（减少28444公顷，降幅2%）以及潮滩（减少25556公顷，降幅47%）的覆盖面积损失最为显著。而覆盖面积增幅最大的生态类型依次为盐沼（增加32922公顷，增幅88%）、过渡型盐沼（增加23645公顷，无对应数据）与红树林（增加12583公顷，增幅40%）。其中，夏洛特港与坦帕湾区域预估将出现海岸湿地净损失最为严重的情况。不确定性分析结果显示，当部分SLAMM数值输入参数发生变动时，研究结果仅出现低至中等程度的波动，这凸显了收集长期沉积、淤积与侵蚀数据以提升SLAMM模型精度的必要性。SLAMM预测的生态系统变化将影响邻近人类社区面临的海岸灾害暴露程度与生态系统服务功能，进而可能对房产价值、基础设施投资以及保险费率造成影响。本研究提供的结果与实施流程，可作为易受海平面上升影响的社区的参考指南，帮助其识别并优先制定减缓或适配当前变化的适应策略。