Department of Geography, University of California, Los Angeles, California.
Department of Environmental Health Sciences, Institute of the Environment and Sustainability, University of California, Los Angeles, California.
Glob Chang Biol. 2019 Jan;25(1):78-92. doi: 10.1111/gcb.14429. Epub 2018 Oct 30.
Sea level rise (SLR) threatens coastal wetlands worldwide, yet the fate of individual wetlands will vary based on local topography, wetland morphology, sediment dynamics, hydrologic processes, and plant-mediated feedbacks. Local variability in these factors makes it difficult to predict SLR effects across wetlands or to develop a holistic regional perspective on SLR response for a diversity of wetland types. To improve regional predictions of SLR impacts to coastal wetlands, we developed a model that addresses the scale-dependent factors controlling SLR response and accommodates different levels of data availability. The model quantifies SLR-driven habitat conversion within wetlands across a region by predicting changes in individual wetland hypsometry. This standardized approach can be applied to all wetlands in a region regardless of data availability, making it ideal for modeling SLR response across a range of scales. Our model was applied to 105 wetlands in southern California that spanned a broad range of typology and data availability. Our findings suggest that if wetlands are confined to their current extents, the region will lose 12% of marsh habitats (vegetated marsh and unvegetated flats) with 0.6 m of SLR (projected for 2050) and 48% with 1.7 m of SLR (projected for 2100). Habitat conversion was more drastic in wetlands with larger proportions of marsh habitats relative to subtidal habitats and occurred more rapidly in small lagoons relative to larger sites. Our assessment can inform management of coastal wetland vulnerability, improve understanding of the SLR drivers relevant to individual wetlands, and highlight significant data gaps that impede SLR response modeling across spatial scales. This approach augments regional SLR assessments by considering spatial variability in SLR response drivers, addressing data gaps, and accommodating wetland diversity, which will provide greater insights into regional SLR response that are relevant to coastal management and restoration efforts.
海平面上升 (SLR) 威胁着全球沿海湿地,但由于局部地形、湿地形态、泥沙动态、水文过程和植物介导的反馈等因素的存在,各个湿地的命运将有所不同。这些因素的局部变异性使得难以预测整个湿地的 SLR 影响,也难以从整体上了解不同类型湿地对 SLR 的反应。为了提高对沿海湿地 SLR 影响的区域预测能力,我们开发了一种模型,该模型解决了控制 SLR 响应的尺度相关因素,并适应了不同的数据可用性水平。该模型通过预测单个湿地地形学的变化,量化了整个区域内由 SLR 驱动的栖息地转换。这种标准化方法可以应用于该区域的所有湿地,无论数据可用性如何,因此非常适合在各种尺度上模拟 SLR 响应。我们的模型应用于南加州的 105 个湿地,这些湿地涵盖了广泛的类型和数据可用性范围。我们的研究结果表明,如果湿地保持在当前的范围之内,那么在 0.6 米的海平面上升(预计在 2050 年达到)和 1.7 米的海平面上升(预计在 2100 年达到)的情况下,该地区将失去 12%的沼泽生境(植被沼泽和无植被滩涂),48%的沼泽生境将消失。在沼泽生境比例相对较大的湿地中,生境转换更为剧烈,而在较小的泻湖中,生境转换更为迅速。我们的评估可以为沿海湿地脆弱性管理提供信息,提高对与单个湿地相关的 SLR 驱动因素的理解,并突出阻碍跨空间尺度的 SLR 响应建模的数据差距。这种方法通过考虑 SLR 响应驱动因素的空间变异性、解决数据差距以及适应湿地多样性,增强了区域 SLR 评估,从而为与沿海管理和恢复工作相关的区域 SLR 响应提供了更深入的见解。