Zhu Mingjian, Hoctor Tom, Volk Mike, Frank Kathryn, Linhoss Anna
Department of Urban Planning Beijing Jiaotong University Beijing 100044 China ; Department of Landscape Architecture University of Florida Gainesville Florida 32611.
Department of Landscape Architecture University of Florida Gainesville Florida 32611.
Ecol Evol. 2015 Sep 18;5(19):4376-88. doi: 10.1002/ece3.1669. eCollection 2015 Oct.
Many studies have explored the value of using more sophisticated coastal impact models and higher resolution elevation data in sea-level rise (SLR) adaptation planning. However, we know little about to what extent the improved models and data could actually lead to better conservation outcomes under SLR. This is important to know because high-resolution data are likely to not be available in some data-poor coastal areas in the world and running more complicated coastal impact models is relatively time-consuming, expensive, and requires assistance by qualified experts and technicians. We address this research question in the context of identifying conservation priorities in response to SLR. Specifically, we investigated the conservation value of using more accurate light detection and ranging (Lidar)-based digital elevation data and process-based coastal land-cover change models (Sea Level Affecting Marshes Model, SLAMM) to identify conservation priorities versus simple "bathtub" models based on the relatively coarse National Elevation Dataset (NED) in a coastal region of northeast Florida. We compared conservation outcomes identified by reserve design software (Zonation) using three different model dataset combinations (Bathtub-NED, Bathtub-Lidar, and SLAMM-Lidar). The comparisons show that the conservation priorities are significantly different with different combinations of coastal impact models and elevation dataset inputs. The research suggests that it is valuable to invest in more accurate coastal impact models and elevation datasets in SLR adaptive conservation planning because this model-dataset combination could improve conservation outcomes under SLR. Less accurate coastal impact models, including ones created using coarser Digital Elevation Model (DEM) data can still be useful when better data and models are not available or feasible, but results need to be appropriately assessed and communicated. A future research priority is to investigate how conservation priorities may vary among different SLR scenarios when different combinations of model-data inputs are used.
许多研究探讨了在海平面上升（SLR）适应规划中使用更复杂的海岸影响模型和更高分辨率高程数据的价值。然而，我们对改进后的模型和数据在SLR情况下实际能在多大程度上带来更好的保护成果知之甚少。了解这一点很重要，因为在世界上一些数据匮乏的沿海地区可能无法获得高分辨率数据，而且运行更复杂的海岸影响模型相对耗时、昂贵，并且需要合格的专家和技术人员的协助。我们在确定应对SLR的保护优先事项的背景下解决这个研究问题。具体而言，我们研究了使用基于更精确的光探测和测距（LiDAR）的数字高程数据和基于过程的海岸土地覆盖变化模型（海平面影响沼泽模型，SLAMM）来确定保护优先事项的保护价值，与基于佛罗里达州东北部沿海地区相对粗略的国家高程数据集（NED）的简单“浴缸”模型进行对比。我们使用三种不同的模型数据集组合（浴缸 - NED、浴缸 - LiDAR和SLAMM - LiDAR）比较了保护区设计软件（Zonation）确定的保护成果。比较结果表明，海岸影响模型和高程数据集输入的不同组合会导致显著不同的保护优先事项。该研究表明，在SLR适应性保护规划中投资更精确的海岸影响模型和高程数据集是有价值的，因为这种模型 - 数据集组合可以改善SLR情况下的保护成果。当无法获得或不可行更好的数据和模型时，不太精确的海岸影响模型，包括使用更粗糙的数字高程模型（DEM）数据创建的模型，仍然可能有用，但结果需要进行适当评估和传达。未来的一个研究重点是调查当使用不同的模型 - 数据输入组合时，不同SLR情景下保护优先事项可能会如何变化。
