Centre for Ecology and Conservation, University of Exeter, Exeter, UK.
MARE - Marine and Environmental Sciences Centre, ISPA- Instituto Universitário, Lisboa, Portugal.
Glob Chang Biol. 2019 Feb;25(2):753-762. doi: 10.1111/gcb.14526. Epub 2018 Dec 12.
Climate change associated sea-level rise (SLR) is expected to have profound impacts on coastal areas, affecting many species, including sea turtles which depend on these habitats for egg incubation. Being able to accurately model beach topography using digital terrain models (DTMs) is therefore crucial to project SLR impacts and develop effective conservation strategies. Traditional survey methods are typically low-cost with low accuracy or high-cost with high accuracy. We present a novel combination of drone-based photogrammetry and a low-cost and portable real-time kinematic (RTK) GPS to create DTMs which are highly accurate (<10 cm error) and visually realistic. This methodology is ideal for surveying coastal sites, can be broadly applied to other species and habitats, and is a relevant tool in supporting the development of Specially Protected Areas. Here, we applied this method as a case-study to project three SLR scenarios (0.48, 0.63 and 1.20 m) and assess the future vulnerability and viability of a key nesting habitat for sympatric loggerhead (Caretta caretta) and green turtle (Chelonia mydas) at a key rookery in the Mediterranean. We combined the DTM with 5 years of nest survey data describing location and clutch depth, to identify (a) regions with highest nest densities, (b) nest elevation by species and beach, and (c) estimated proportion of nests inundated under each SLR scenario. On average, green turtles nested at higher elevations than loggerheads (1.8 m vs. 1.32 m, respectively). However, because green turtles dig deeper nests than loggerheads (0.76 m vs. 0.50 m, respectively), these were at similar risk of inundation. For a SLR of 1.2 m, we estimated a loss of 67.3% for loggerhead turtle nests and 59.1% for green turtle nests. Existing natural and artificial barriers may affect the ability of these nesting habitats to remain suitable for nesting through beach migration.
气候变化引起的海平面上升预计将对沿海地区产生深远影响，影响许多物种，包括海龟，它们依赖这些栖息地来孵化卵。因此，能够使用数字地形模型（DTM）准确地模拟海滩地形对于预测海平面上升的影响和制定有效的保护策略至关重要。传统的调查方法通常是低成本、低精度或高成本、高精度。我们提出了一种基于无人机摄影测量和低成本、便携式实时动态（RTK）GPS 的新组合方法，创建了高精度（<10 厘米误差）和视觉逼真的 DTM。这种方法非常适合沿海地区的调查，可以广泛应用于其他物种和栖息地，是支持特别保护区发展的相关工具。在这里，我们将该方法应用于案例研究，以预测三个海平面上升情景（0.48、0.63 和 1.20 米），并评估在地中海一个关键筑巢地中，同时生活的红海龟（Caretta caretta）和绿海龟（Chelonia mydas）关键繁殖地未来的脆弱性和生存能力。我们将 DTM 与 5 年的巢调查数据相结合，描述了位置和卵窝深度，以确定（a）巢密度最高的区域，（b）按物种和海滩划分的巢高度，以及（c）在每个海平面上升情景下估计淹没的巢比例。平均而言，绿海龟的筑巢高度高于红海龟（分别为 1.8 米和 1.32 米）。然而，由于绿海龟挖掘的巢比红海龟深（分别为 0.76 米和 0.50 米），它们面临着类似的淹没风险。在海平面上升 1.2 米的情况下，我们估计红海龟巢的损失为 67.3%，绿海龟巢的损失为 59.1%。现有的自然和人工障碍可能会影响这些筑巢栖息地通过海滩迁移保持适合筑巢的能力。
