| dc.creator |
Varela, MR |
|
| dc.creator |
Patricio, AR |
|
| dc.creator |
Anderson, K |
|
| dc.creator |
Broderick, AC |
|
| dc.creator |
DeBell, L |
|
| dc.creator |
Hawkes, LA |
|
| dc.creator |
Tilley, D |
|
| dc.creator |
Snape, R |
|
| dc.creator |
Westoby, MJ |
|
| dc.creator |
Godley, BJ |
|
| dc.date |
2018-11-16T14:31:02Z |
|
| dc.date |
2018-11-14 |
|
| dc.date.accessioned |
2022-05-27T01:01:37Z |
|
| dc.date.available |
2022-05-27T01:01:37Z |
|
| dc.identifier |
Published online 14 November 2018 |
|
| dc.identifier |
10.1111/gcb.14526 |
|
| dc.identifier |
http://hdl.handle.net/10871/34793 |
|
| dc.identifier |
1354-1013 |
|
| dc.identifier |
Global Change Biology |
|
| dc.identifier.uri |
http://localhost:8080/xmlui/handle/CUHPOERS/241845 |
|
| dc.description |
This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record |
|
| dc.description |
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 (1) regions with highest nest densities, (2) nest elevation by species and beach, and (3) 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. |
|
| dc.description |
The long-term monitoring data used in this
article is supported in part by fundraising support from Karşıyaka Turtle Watch, Kuzey Kıbrıs
Turkcell, Erwin Warth Foundation, the MAVA foundation, Tony and Angela Wadsworth and
the English School of Kyrenia |
|
| dc.language |
en |
|
| dc.publisher |
Wiley |
|
| dc.rights |
© 2018 Wiley. All rights reserved |
|
| dc.rights |
2019-11-14 |
|
| dc.rights |
Under embargo until 14 November 2019 in compliance with publisher policy |
|
| dc.subject |
Climate Change |
|
| dc.subject |
Sea Level Rise |
|
| dc.subject |
Sea Turtles |
|
| dc.subject |
Photogrammetry |
|
| dc.subject |
Drones |
|
| dc.subject |
UAV |
|
| dc.subject |
Piksi |
|
| dc.subject |
Remote Sensing |
|
| dc.title |
Assessing climate change associated sea level rise impacts on sea turtle nesting beaches using drones, photogrammetry and a novel GPS system |
|
| dc.type |
Article |
|