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Remote Sensing Applications for Sea Turtle Conservation

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: closed (31 May 2022) | Viewed by 35641

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Special Issue Editors

Dr. John F. Weishampel

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Guest Editor

Department of Biology, University of Central Florida, Orlando, FL 32816, USA
Interests: landscape ecology; ecological modeling; geospatial analysis

Dr. Simona A. Ceriani

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Guest Editor

Fish and Wildlife Research Institute, Florida Fish and Wildlife Conservation Commission, Saint Petersburg, FL 33701, USA
Interests: marine turtles; nesting ecology; foraging ecology; conservation biology; population assessment; migration; telemetry; intrinsic markers

Dr. Mariana M.P.B. Fuentes

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Guest Editor

Department of Earth, Ocean, and Atmospheric Science, Florida State University, Tallahassee, FL 32306, USA
Interests: marine turtles; conservation planning; spatial pattern analysis; biologging; impact assessment; ecological modeling

Special Issue Information

Dear Colleagues,

Sea turtles represent a taxonomic reptile superfamily of long-lived, highly-migratory keystone species that are designated as threatened and endangered. Their wide geographic distribution occupying pelagic, coastal, and beach habitats lends itself to a diversity of spatiotemporal remote sensing techniques and analyses to decipher their somewhat cryptic, complex lifestyles and to assist with their stewardship and conservation. Recent environmental changes such as those associated with climate, coastal development, fishing, and marine and atmospheric pollution have impacted the behaviors and populations of sea turtle species.

For this Special Issue, we seek innovative approaches that use remote sensing to collect biological and environmental data that elucidate sea turtle ecology and define their dynamics with conservation applications. Submissions could be based on pilot-studies or long-term datasets collected by drone, airborne, and/or satellite sensors including GPS telemetry. Example research questions could revolve around the use of sea turtle nesting, foraging, migratory habitats as depicted by LiDAR (e.g., beach topography), optical (e.g., Sargassum, seagrass habitat), Radar (e.g., ocean current), and thermal (e.g., sea surface temperature) instruments. Questions could explore connections between sea turtle behavioral patterns and environmental changes associated with natural (e.g., hurricanes, ocean oscillations) and anthropogenic (e.g., fishing practices, oil pollution) disturbances and coastal restoration (e.g., beach renourishment, artificial light management). We welcome review papers, case studies, modeling exercises, and methodological examples.

Dr. John F. Weishampel
Dr. Simona A. Ceriani
Dr. Mariana M.P.B. Fuentes
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Marine turtles
Remote sensing
Beach, coastal, open ocean habitats
GPS telemetry
Foraging, migratory, nesting behaviors
Spatial pattern analyses
Environmental modeling
Conservation and management

Published Papers (9 papers)

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17 pages, 4086 KiB

Open AccessArticle

The Influence of Satellite-Derived Environmental and Oceanographic Parameters on Marine Turtle Time at Surface in the Gulf of Mexico

by Kelsey E. Roberts, Lance P. Garrison, Joel Ortega-Ortiz, Chuanmin Hu, Yingjun Zhang, Christopher R. Sasso, Margaret Lamont and Kristen M. Hart

Remote Sens. 2022, 14(18), 4534; https://doi.org/10.3390/rs14184534 - 11 Sep 2022

Cited by 2 | Viewed by 2087

Abstract

The aftermath of the 2010 Deepwater Horizon oil spill highlighted the lack of baseline spatial, behavioral, and abundance data for many species, including imperiled marine turtles, across the Gulf of Mexico. The ecology of marine turtles is closely tied to their vertical movements within the water column and is therefore critical knowledge for resource management in a changing ocean. A more comprehensive understanding of diving behavior, specifically surface intervals, can improve the accuracy of density and abundance estimates by mitigating availability bias. Here, we focus on the proportion of time marine turtles spend at the top 2 m of the water column to coincide with depths where turtles are assumed visible to observers during aerial surveys. To better understand what environmental and oceanographic conditions influence time at surface, we analyzed dive and spatial data from 136 satellite tags attached to three species of threatened or endangered marine turtles across 10 years. We fit generalized additive models with 11 remotely sensed covariates, including sea surface temperature (SST), bathymetry, and salinity, to examine dive patterns. Additionally, the developed model is the first to explicitly examine the potential connection between turtle dive patterns and ocean frontal zones in the Gulf of Mexico. Our results show species-specific associations of environmental covariates related to increased time at surface, particularly for depth, salinity, and frontal features. We define seasonal and spatial variation in time-at-surface patterns in an effort to contribute to marine turtle density and abundance estimates. These estimates could then be utilized to generate correction factors for turtle detection availability during aerial surveys. Full article

(This article belongs to the Special Issue Remote Sensing Applications for Sea Turtle Conservation)

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28 pages, 4885 KiB

Open AccessArticle

One Shell of a Problem: Cumulative Threat Analysis of Male Sea Turtles Indicates High Anthropogenic Threat for Migratory Individuals and Gulf of Mexico Residents

by Micah Ashford, James I. Watling and Kristen Hart

Remote Sens. 2022, 14(16), 3887; https://doi.org/10.3390/rs14163887 - 11 Aug 2022

Cited by 5 | Viewed by 2621

Abstract

Human use of oceans has dramatically increased in the 21st century. Sea turtles are vulnerable to anthropogenic stressors in the marine environment because of lengthy migrations between foraging and breeding sites, often along coastal migration corridors. Little is known about how movement and threat interact specifically for male sea turtles. To better understand male sea turtle movement and the threats they encounter, we satellite-tagged 40 adult male sea turtles of four different species. We calculated movement patterns using state-space modeling (SSM), and quantified threats in seven unique categories; shipping, fishing, light pollution, oil rigs, proximity to coast, marine protected area (MPA) status, and location within or outside of the U.S. Exclusive Economic Zone (EEZ). We found significantly higher threat severity in northern and southern latitudes for green turtles (Chelonia mydas) and Kemp’s ridleys (Lepidochelys kempii) in our study area. Those threats were pervasive, with only 35.9% of SSM points encountering no high threat exposure, of which 47% belong to just two individuals. Kemp’s ridleys were most exposed to high threats among tested species. Lastly, turtles within MPA boundaries face significantly lower threat exposure, indicating MPAs could be a useful conservation tool. Full article

(This article belongs to the Special Issue Remote Sensing Applications for Sea Turtle Conservation)

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16 pages, 3807 KiB

Open AccessArticle

Modeling Artificial Light Exposure after Vegetation Trimming at a Marine Turtle Nesting Beach

by Mark A. Barrett and Kristen Nelson Sella

Remote Sens. 2022, 14(11), 2702; https://doi.org/10.3390/rs14112702 - 04 Jun 2022

Cited by 3 | Viewed by 2425

Abstract

Light pollution caused by poorly directed artificial lighting has increased globally in recent years. Artificial lights visible along marine turtle nesting beaches can disrupt natural brightness cues used by hatchling turtles to orient correctly to the ocean for their offshore migrations. Natural barriers, such as tall dunes and dense vegetation, that block coastal and inland lights from the beach may reduce this disruption. However, coastal areas are often managed toward human values, including the trimming of vegetation to improve ocean views. We used viewshed models to determine how reducing the dune vegetation height (specifically that of seagrape, Cocoloba uvifera) might increase the amount of artificial light from upland buildings that reaches a marine turtle nesting beach in Southeast Florida. We incorporated three data sets (LiDAR data, turtle nest locations, and field surveys of artificial lights) into a geographic information system to create viewsheds of lighting from buildings across 21 vegetation profiles. In 2018, when most seagrape patches had been trimmed to <1.1 m tall, female loggerhead turtles nested in areas with potential for high light exposure based on a cumulative viewshed model. Viewshed models using random (iterative simulations) and nonrandom selections of buildings revealed that untrimmed seagrape heights (mean = 3.1 m) and especially taller vegetation profiles effectively reduced potential lighting exposure from three building heights (upper story, midstory, and ground level). Even the tallest modeled vegetation, however, would fail to block lights from the upper stories of some tall buildings. Results from this study can support management decisions regarding the trimming of beach dune vegetation, any associated changes in the visibility of artificial lighting from the nesting areas, and modifications to existing lighting needed to mitigate light exposure. Full article

(This article belongs to the Special Issue Remote Sensing Applications for Sea Turtle Conservation)

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20 pages, 28729 KiB

Open AccessArticle

Regional Ranking of Marine Turtle Nesting in Remote Western Australia by Integrating Traditional Ecological Knowledge and Remote Sensing

by Anton D. Tucker, Kellie L. Pendoley, Kathy Murray, Graham Loewenthal, Chris Barber, Jai Denda, Gina Lincoln, Dean Mathews, Daniel Oades, Scott D. Whiting, Miriuwung Gajerrong Rangers, Balanggarra Rangers, Wunambal Gaambera Rangers, Dambimangari Rangers, Mayala Rangers, Bardi Jawi Rangers, Nyul Nyul Rangers, Yawuru Rangers, Karajarri Rangers, Nyangumarta Rangers and Ngarla Rangers Show full author list Hide full author list

Remote Sens. 2021, 13(22), 4696; https://doi.org/10.3390/rs13224696 - 20 Nov 2021

Cited by 4 | Viewed by 2677

Abstract

Western Australia’s remote Kimberley coastline spans multiple Traditional Owner estates. Marine turtle nesting distribution and abundance in Indigenous Protected Areas and newly declared Marine Parks were assessed by aerial photogrammetry surveys for the Austral summer and winter nesting seasons. Images of nesting tracks were quantified in the lab and verified by ad hoc ground patrols. The rankings of log-scaled plots of track abundance and density give guidance to regional co-management planning. Spatial and temporal differences were detected in that remoter islands had higher nesting usage and few terrestrial predators. The surveys found year-round green turtle nesting peaking in summer, as well as spatial boundaries to the summer and winter flatback stocks. Summer surveys recorded 126.2 island activities per km and 17.7 mainland activities per km. Winter surveys recorded 65.3 island activities per km and quantified a known winter mainland rookery with 888 tracks/km. The three highest density rookeries were found to be winter flatback turtles at Cape Domett, summer green turtles at the Lacepede Islands and summer flatback turtles at Eighty Mile Beach. Moderate to lesser density nesting by summer green turtles and winter flatback turtles occurred in the North Kimberley offshore islands. Traditional Ecological Knowledge and ground-based surveys verified the harder-to-detect species (olive ridley or hawksbill turtles) with irregular nesting, low track persistence and non-aggregated nesting. Higher-density rookeries may provide locations for long-term monitoring using repeated aerial or ground surveys; however, the sparse or infrequently nesting species require insights gleaned by Tradition Ecological Knowledge. Common and conspicuous nesters are easily detected and ranked, but better-informed co-management requires additional ground surveys or surveys timed with the reproductive peaks of rarer species. Full article

(This article belongs to the Special Issue Remote Sensing Applications for Sea Turtle Conservation)

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18 pages, 1471 KiB

Open AccessArticle

Exposure of Loggerhead Sea Turtle Nests to Waves in the Florida Panhandle

by Matthew Ware, Simona A. Ceriani, Joseph W. Long and Mariana M.P.B. Fuentes

Remote Sens. 2021, 13(14), 2654; https://doi.org/10.3390/rs13142654 - 06 Jul 2021

Cited by 4 | Viewed by 4743

Abstract

Wave wash-over poses a significant threat to sea turtle nests, with sustained exposure to waves potentially resulting in embryonic mortality and altered hatchling locomotor function, size, and sex ratios. Identifying where and under what conditions wave exposure becomes a problem, and deciding what action(s) to take (if any), is a common issue for sea turtle managers. To determine the exposure of sea turtle nests to waves and identify potential impacts to hatchling productivity, we integrated a geographic information system with remote sensing and wave runup modeling across 40 nesting beaches used by the Northern Gulf of Mexico Loggerhead Recovery Unit. Our models indicate that, on average, approximately 50% of the available beach area and 34% of nesting locations per nesting beach face a significant risk of wave exposure, particularly during tropical storms. Field data from beaches in the Florida Panhandle show that 42.3% of all nest locations reported wave exposure, which resulted in a 45% and 46% decline in hatching and emergence success, respectively, relative to their undisturbed counterparts. Historical nesting frequency at each beach and modeled exposure to waves were considered to identify priority locations with high nesting density which either experience low risk of wave exposure, as these are good candidates for protection as refugia for sustained hatchling production, or which have high wave exposure where efforts to reduce impacts are most warranted. Nine beaches in the eastern Florida Panhandle were identified as priority sites for future efforts such as habitat protection or research and development of management strategies. This modeling exercise offers a flexible approach for a threat assessment integration into research and management questions relevant to sea turtle conservation, as well as for other beach species and human uses of the coastal environment. Full article

(This article belongs to the Special Issue Remote Sensing Applications for Sea Turtle Conservation)

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20 pages, 2940 KiB

Open AccessArticle

Using Aerial Photogrammetry to Assess Stock-Wide Marine Turtle Nesting Distribution, Abundance and Cumulative Exposure to Industrial Activity

by Sabrina Fossette, Graham Loewenthal, Lauren R. Peel, Anna Vitenbergs, Melanie A. Hamel, Corrine Douglas, Anton D. Tucker, Florian Mayer and Scott D. Whiting

Remote Sens. 2021, 13(6), 1116; https://doi.org/10.3390/rs13061116 - 15 Mar 2021

Cited by 8 | Viewed by 3607

Abstract

The lack of accurate distribution maps and reliable abundance estimates for marine species can limit the ability of managers to design scale-appropriate management measures for a stock or population. Here, we tested the utility of aerial photogrammetry for conducting large-scale surveys of nesting marine turtles at remote locations, with a focus on the flatback turtle (Natator depressus) in the Pilbara region of Western Australia. Aerial surveys were conducted between 29 November and 6 December 2016 to overlap with the peak nesting season for flatback turtles and collected imagery was used to examine marine turtle distribution, abundance, and cumulative exposure to industrial activity relative to overlap with protected areas. Two observers independently reviewed aerial georeferenced photographs of 644 beaches and recorded turtle tracks and other evidence of turtle nesting activity. A total of 375 beaches showed signs of nesting activity by either flatback, green (Chelonia mydas) or hawksbill (Eretmochelys imbricata) turtles. Most of these beaches (85.3%) were located on islands, and the rest (14.7%) on the mainland. Half (n = 174) of the active beaches showed evidence of fresh (0–36 h. old) flatback nesting activity, with track abundance varying from 1.0 to 222.0 tracks·night⁻¹. Six rookeries accounted for 62% of the Pilbara flatback stock. Remarkably, 77% of identified flatback rookeries occurred within protected areas. However, one-third (34%) of those were also located within 5 km of a major industrial site, including eight of the highest abundance beaches (50–250 tracks·night⁻¹). Several key rookeries were also identified as being relatively unexposed to industry-related pressures but currently unprotected, highlighting the need for a cumulative impact assessment to be completed for this flatback stock. Finally, our aerial tallies and multiple ground-survey flatback track tallies were highly correlated and together with low intra- and inter-observer errors suggested that reliable data can be collected via aerial photogrammetry for nesting marine turtles. Such large-scale digitized surveys can therefore be used to assess the cumulative exposure of marine turtles to pressures, and to reveal new conservation opportunities. Full article

(This article belongs to the Special Issue Remote Sensing Applications for Sea Turtle Conservation)

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19 pages, 6177 KiB

Open AccessArticle

Quantifying the Impact of Light Pollution on Sea Turtle Nesting Using Ground-Based Imagery

by James Vandersteen, Salit Kark, Karina Sorrell and Noam Levin

Remote Sens. 2020, 12(11), 1785; https://doi.org/10.3390/rs12111785 - 01 Jun 2020

Cited by 19 | Viewed by 7234

Abstract

Remote sensing of anthropogenic light has substantial potential to quantify light pollution levels and understand its impact on a wide range of taxa. Currently, the use of space-borne night-time sensors for measuring the actual light pollution that animals experience is limited. This is because most night-time satellite imagery and space-borne sensors measure the light that is emitted or reflected upwards, rather than horizontally, which is often the light that is primarily perceived by animals. Therefore, there is an important need for developing and testing ground-based remote sensing techniques and methods. In this study, we aimed to address this gap by examining the potential of ground photography to quantify the actual light pollution perceived by animals, using sea turtles as a case study. We conducted detailed ground measurements of night-time brightness around the coast of Heron Island, a coral cay in the southern Great Barrier Reef of Australia, and an important sea turtle rookery, using a calibrated DSLR Canon camera with an 8 mm fish-eye lens. The resulting hemispheric photographs were processed using the newly developed Sky Quality Camera (SQC) software to extract brightness metrics. Furthermore, we quantified the factors determining the spatial and temporal variation in night-time brightness as a function of environmental factors (e.g., moon light, cloud cover, and land cover) and anthropogenic features (e.g., artificial light sources and built-up areas). We found that over 80% of the variation in night-time brightness was explained by the percentage of the moon illuminated, moon altitude, as well as cloud cover. Anthropogenic and geographic factors (e.g., artificial lighting and the percentage of visible sky) were especially important in explaining the remaining variation in measured brightness under moonless conditions. Night-time brightness variables, land cover, and rock presence together explained over 60% of the variation in sea turtle nest locations along the coastline of Heron Island, with more nests found in areas of lower light pollution. The methods we developed enabled us to overcome the limitations of commonly used ground/space borne remote sensing techniques, which are not well suited for measuring the light pollution to which animals are exposed. The findings of this study demonstrate the applicability of ground-based remote sensing techniques in accurately and efficiently measuring night-time brightness to enhance our understanding of ecological light pollution. Full article

(This article belongs to the Special Issue Remote Sensing Applications for Sea Turtle Conservation)

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13 pages, 3181 KiB

Open AccessTechnical Note

Comparison of UAV and Boat Surveys for Detecting Changes in Breeding Population Dynamics of Sea Turtles

by Adam Yaney-Keller, Ricardo San Martin and Richard D. Reina

Remote Sens. 2021, 13(15), 2857; https://doi.org/10.3390/rs13152857 - 21 Jul 2021

Cited by 11 | Viewed by 4039

Abstract

Surveying the breeding population of a given species can be difficult for many logistic reasons. Marine turtles are a challenging taxon for the study of reproductive ecology and breeding strategies, because turtles aggregate off-shore and males remain exclusively at sea. For successful management of sea turtle populations, determining operational sex ratios (OSRs) on a continuing basis is critical for determining long-term population viability, particularly in the context of changing hatchling sex ratios due to temperature-dependent sex determination in a warming climate. To understand how survey technique and stage of the breeding season might influence the ability to detect turtles and determine OSRs, we surveyed the presence and identified the sex of adult male and female green sea turtles (Chelonia mydas) using a boat and small commercial unoccupied/unmanned aerial vehicle (UAV), at the start (October) and peak (December) of a nesting season at an important breeding site at Heron Island, Great Barrier Reef, Australia. The ratio of males to females within the breeding ground detected by both survey methods changed from being male-biased in October to heavily female-biased in December, indicating that most males cease their reproductive effort and depart before the peak of the nesting season. Surveying with a UAV more than doubled the rate of turtles seen per minute of survey effort compared with surveying solely from the boat and allowed surveys to be conducted at times and/or places unsafe or inaccessible for boats. The sex of a slightly greater proportion of turtles seen could not be identified by observers using a UAV versus a boat, although more turtles were detected using the UAV. The departure of many males during the peak of the nesting season is likely due to an increasing biological cost of residency in the area because males encounter fewer receptive females as the season progresses and the limited foraging opportunity is insufficient to support the number of males present. Overall, we found that UAVs are an effective tool for studying important but difficult to observe aspects of sea turtle biology. Full article

(This article belongs to the Special Issue Remote Sensing Applications for Sea Turtle Conservation)

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10 pages, 1214 KiB

Open AccessLetter

A Global Analysis of Anthropogenic Development of Marine Turtle Nesting Beaches

by Sarah J. Biddiscombe, Elliott A. Smith and Lucy A. Hawkes

Remote Sens. 2020, 12(9), 1492; https://doi.org/10.3390/rs12091492 - 08 May 2020

Cited by 12 | Viewed by 3875

Abstract

The Intergovernmental Panel on Climate Change predicts that sea levels will rise by up to 0.82 m in the next 100 years. In natural systems, coastlines would migrate landwards, but because most of the world’s human population occupies the coast, anthropogenic structures (such as sea walls or buildings) have been constructed to defend the shore and prevent loss of property. This can result in a net reduction in beach area, a phenomenon known as “coastal squeeze”, which will reduce beach availability for species such as marine turtles. As of yet, no global assessment of potential future coastal squeeze risk at marine turtle nesting beaches has been conducted. We used Google Earth satellite imagery to enumerate the proportion of beaches over the global nesting range of marine turtles that are backed by hard anthropogenic coastal development (HACD). Mediterranean and North American nesting beaches had the most HACD, while the Australian and African beaches had the least. Loggerhead and Kemp’s ridley turtle nesting beaches had the most HACD, and flatback and green turtles the least. Future management approaches should prioritise the conservation of beaches with low HACD to mitigate future coastal squeeze. Full article

(This article belongs to the Special Issue Remote Sensing Applications for Sea Turtle Conservation)

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