Abstract
<jats:title>Abstract</jats:title><jats:p>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 (<jats:italic>Caretta caretta</jats:italic>) and green turtle (<jats:italic>Chelonia mydas</jats:italic>) 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.</jats:p>
Original language | English |
---|---|
Pages (from-to) | 753-762 |
Number of pages | 0 |
Journal | Global Change Biology |
Volume | 25 |
Issue number | 2 |
Early online date | 12 Dec 2018 |
DOIs | |
Publication status | Published - Feb 2019 |