How can GIS be used to model sea turtle nesting sites?

Answer from top 10 papers

Habitat suitability modeling for sea turtle nesting sites is a critical conservation tool, particularly in the face of environmental changes and anthropogenic pressures. Geographic Information Systems (GIS) have been increasingly utilized to assess and predict the suitability of nesting habitats for sea turtles (Fuentes et al., 2023; Veelenturf et al., 2020). These models incorporate various biophysical criteria, such as sand temperature, vegetation, beach slope, and sand particle size, which are essential for determining the optimal conditions for sea turtle nesting (Veelenturf et al., 2020).
However, the accuracy and effectiveness of these models can be influenced by dynamic coastal processes and climate change. For instance, studies have shown that sea level rise (SLR) and coastal erosion can lead to significant habitat loss, as evidenced by the projected loss of nesting habitat on Bioko Island and the documented northward shift of nesting sites for Olive Ridley Sea Turtles due to substantial coastal erosion (García et al., 2015; Mishra et al., 2024). Additionally, the presence of microplastics in nesting beaches has been found to alter sand properties, potentially impacting nest temperature and hatchling sex ratios (Gammon et al., 2023).
Interestingly, while GIS-based models are powerful, they must be calibrated against actual nesting activities to ensure their predictive validity. In some cases, sites identified as suitable through GIS and multi-criteria decision support models do not always correlate with observed turtle nesting activities, suggesting that other external factors may influence nesting choices (Veelenturf et al., 2020). Moreover, historical losses of nesting beaches, which are often undocumented, could lead to an overestimation of conservation successes and misrepresent the actual status of sea turtle populations (Hill et al., 2019).
In summary, GIS-based habitat suitability models are invaluable for the conservation of sea turtle nesting sites, yet they must be used in conjunction with ongoing monitoring and adjusted for regional environmental dynamics and anthropogenic threats. The integration of remote sensing data, GIS, and multi-criteria decision support models offers a robust approach to managing and conserving these critical habitats (Azizan et al., 2023). However, the models' effectiveness is contingent upon their ability to accurately reflect the complex interplay between sea turtles' nesting behaviors and the rapidly changing coastal environment (Lopez et al., 2015; Maneja et al., 2020). Therefore, continuous refinement of these models, informed by empirical data and adjusted for regional threats such as SLR, erosion, and microplastic pollution, is essential for effective conservation planning (Dunkin et al., 2016; Gammon et al., 2023; García et al., 2015).

Source Papers

Site Suitability Analysis for Sea Turtle Nesting Area by using AHP and GIS

Sea turtles are among the endangered marine life not only in Malaysia but also in the world. There are various criteria required in finding a suitable turtle nest site, it may be necessary to suit the needs of the environment in the study area, and it was found that there are four (4) most important criteria in studying turtle nesting suitability site namely (1) sand temperature, (2) vegetation, (3) beach slope, and (4) sand particle size. The use of GIS with the help of AHP can get a better result in finding the site suitability for sea turtle nesting by using weighted overlay analysis. The highest weight value is sand particle size with 0.616, followed by beach slope with 0.220, sand temperature with 0.114, and vegetation with 0.049 was derived from the use of AHP techniques. As a result, the suitability index in the study area was measured and analyzed with the sea turtles’ activities. As a result, the suitability index in the study area was measured and analyzed with the sea turtles’ activities. It was found that there is a low correlation between the site suitability index and the sea turtles’ activities which matches the expert’s opinion that though the site is deemed suitable for sea turtles nesting, they may not be crawled up and nest due to other external factors. The sites with the highest index were verified to be the most suitable by the experts as it is true that sea turtles were ascending to the sites for nesting. In conclusion, integrating GIS with the help of AHP can be an important technique to find a suitable site for the sea turtle nesting area.

Open Access
Predicting the impacts of sea level rise in sea turtle nesting habitat on Bioko Island, Equatorial Guinea.

Sea level is expected to rise 44 to 74 cm by the year 2100, which may have critical, previously un-investigated implications for sea turtle nesting habitat on Bioko Island, Equatorial Guinea. This study investigates how nesting habitat will likely be lost and altered with various increases in sea level, using global sea level rise (SLR) predictions from the Intergovernmental Panel on Climate Change. Beach profiling datasets from Bioko’s five southern nesting beaches were used in GIS to create models to estimate habitat loss with predicted increases in sea level by years 2046–2065 and 2081–2100. The models indicate that an average of 62% of Bioko’s current nesting habitat could be lost by 2046–2065 and 87% by the years 2081–2100. Our results show that different study beaches showed different levels of vulnerability to increases in SLR. In addition, on two beaches erosion and tall vegetation berms have been documented, causing green turtles to nest uncharacteristically in front of the vegetation line. We also report that development plans are currently underway on the beach least susceptible to future increases in sea level, highlighting how anthropogenic encroachment combined with SLR can be particularly detrimental to nesting turtle populations. Identified habitat sensitivities to SLR will be used to inform the government of Equatorial Guinea to consider the vulnerability of their resident turtle populations and projected climate change implications when planning for future development. To our knowledge this is the first study to predict the impacts of SLR on a sea turtle nesting habitat in Africa.

Open Access
Modeling sea-level change, inundation scenarios, and their effect on the Colola Beach Reserve – a nesting-habitat of the black sea turtle, Michoacán, Mexico

The effects of climate change will vary regionally. However, the mean temperature will rise worldwide, and the concomitant rise in sea level will affect most coastal beaches and consequently all populations of sea turtles in the short, medium and long term. Models of expected beach inundation and loss of nesting habitat due to sea-level rises are required to assess coastal changes and the conservation of the sea-turtle nesting areas. Colola Beach in Michocán, Mexico, is the main nesting area of the black sea-turtle (Chelonia mydas agassizii), also referred as Eastern Pacific green turtle, a species listed as being in danger of extinction. We assessed the effects of sea-level change in this beach using three different scenarios. With this purpose, we surveyed the topography of Colola Beach in detail to produce a digital elevation model (DEM) and modeled beach inundation expected to accompany sea-level rises of 0.5 m, 1.40 m and 5 m; recorded sea-turtle nesting sites and areas using global positioning systems (GPS), and finally modeled using geographic information systems (GIS), satellite images and a digital elevation model. The produced models suggest that rises of 0.5 m or 1.40 m would affect the Colola beach area by reducing it. Most significantly, a sea-level rise of 5 m would have a dramatic effect, with the loss of 54% of the beach and nesting area. This approach and predicted scenarios through detailed topographic survey and GIS modeling should assist in creating strategies for the conservation of the sea turtle populations in this beach reserve and elsewhere.

Open Access
Vulnerability of sea turtle nesting sites to erosion and inundation: A decision support framework to maximize conservation

AbstractSandy beaches provide essential nesting habitats for sea turtles but are threatened globally by a rapidly changing climate. Identifying which nesting sites are at the greatest risk from erosion and inundation remains an important goal of sea turtle conservation globally. Yet, efforts to identify at‐risk sites have been hindered by the ability to model complex processes and incomplete information on nesting distribution and abundance. To assess the erosion and inundation risk to the reproductive success of a discrete genetic stock of flatback turtles (Natator depressus) across its nesting range in the Pilbara region of Western Australia, we used the Integrated Valuation of Ecosystem Services and Trade‐offs (InVEST) Coastal Vulnerability Model. A relative exposure index was calculated for 402 nesting beaches in terms of six geophysical variables: wind and wave exposure, surge potential, relief, observed sea level rise, and coastal geomorphology, and coupled with published information on the distribution and abundance of turtle tracks in the region. The majority of beaches (74%) had intermediate to high exposure. In particular, 36% of beaches with a high abundance of flatback tracks (the top 25% of the frequency distribution) had a high exposure (the top 25% of the frequency distribution). This suggests that coastal exposure is a key vulnerability to the reproductive success of sea turtles that nest in this region. Promisingly, five beaches with a high abundance of turtle tracks also had a low exposure (bottom 25% of the frequency distribution), and these beaches may be critical for the long‐term resilience of the stock against sea level rise and severe storms. Exposure varied across nesting sites, and the approach presented here allows for a rapid and broadscale assessment of relative erosion and inundation risks at a scale most relevant to management.

Open Access
Coastal development at sea turtles nesting ground: Efforts to establish a tool for supporting conservation and coastal management in northeastern Brazil

While tropical and subtropical coastal areas are considered prime areas for a wide range of tourism projects, they also host important sea turtle nesting grounds. Preserving these nesting areas is critical to ensure reproductive success and maintain viable sea turtle populations. The northern coast of the State of Bahia, in northeastern Brazil, is an important sea turtle nesting ground. Sea turtle conservation activities in Brazil began in 1980, focusing initially on reducing harvesting of nesting females and egg collection. Recently, new threats resulting from unplanned coastal development have emerged. In this paper, a geospatial tool, as an initiative of the Brazilian National Sea Turtle Conservation Program (TAMAR) to identify key areas for sea turtle nesting along the coast northern coast of Bahia, is presented. A Sensitivity Map was created, using a detailed GIS map graded by colors representing relevance levels of the coast for sea turtle nesting. From this map, recommendations of management practices that correspond to each sensitivity category can be made. This methodology allows for the identification of critical sea turtle habitats and the subsequent implementation of mitigation measures at nesting beaches, as well support coastal management policies.

Multidecadal analysis of beach loss at the major offshore sea turtle nesting islands in the northern Arabian Gulf

Undocumented historical losses of sea turtle nesting beaches worldwide could overestimate the successes of conservation measures and misrepresent the actual status of the sea turtle population. In addition, the suitability of many sea turtle nesting sites continues to decline even without in-depth scientific studies of the extent of losses and impacts to the population. In this study, multidecadal changes in the outlines and area of Jana and Karan islands, major sea turtle nesting sites in the Arabian Gulf, were compared using available Kodak aerographic images, USGS EROS Declassified satellite imagery, and ESRI satellite images. A decrease of 5.1% and 1.7% of the area of Jana and Karan islands, respectively, were observed between 1965 and 2017. This translated to 14,146 m2 of beach loss at Jana Is. and 16,376 m2 of beach loss at Karan Is. There was an increase of island extent for Karan Is. from 1965 to 1968 by 9098 m2 but comparing 2017 with 1968, Karan Is. lost as much as 25,474 m2 or 2.6% of the island extent in 1968. The decrease in island aerial extent was attributed to loss of beach sand. The southern tips of the island lost the most significant amount of sand. There was also thinning of beach sand along the middle and northern sections that exposed the rock outcrops underneath the beach. The process of beach changes of both islands was tracked by the satellite imagery from Landsat 1,3,5,7 and Sentinel-2 during 1972 to 2020. Other factors including the distribution of beach slope, sea level changes, as well as wind & current from both northward and eastward components were analyzed to show its impact on the beach changes. The loss of beach sand could potentially impact the quality and availability of nesting beach for sea turtles utilizing the islands as main nesting grounds. Drivers of beach loss at the offshore islands are discussed in the context of sea level rise, dust storms, extreme wave heights and island desertification.

Open Access
A Spatially Explicit, Multi-Criteria Decision Support Model for Loggerhead Sea Turtle Nesting Habitat Suitability: A Remote Sensing-Based Approach

Nesting habitat for the federally endangered loggerhead sea turtle (Caretta caretta) were designated as critical in 2014 for beaches along the Atlantic Coast and Gulf of Mexico. Nesting suitability is routinely determined based on site specific information. Given the expansive geographic location of the designated critical C. caretta nesting habitat and the highly dynamic coastal environment, understanding nesting suitability on a regional scale is essential for monitoring the changing status of the coast as a result of hydrodynamic forces and maintenance efforts. The increasing spatial resolution and temporal frequency of remote sensing data offers the opportunity to study this dynamic environment on a regional scale. Remote sensing data were used as input into the spatially-explicit, multi-criteria decision support model to determine nesting habitat suitability. Results from the study indicate that the morphological parameters used as input into the model are well suited to provide a regional level approach with the results from the optimized model having sensitivity and detection prevalence values greater than 80% and the detection rate being greater than 70%. The approach can be implemented in various geographic locations to better communicate priorities and evaluate management strategies as a result of changes to the dynamic coastal environment.

Open Access
The effects of microplastic on the thermal profile of sand: implications for marine turtle nesting grounds

IntroductionMicroplastics (i.e., plastic debris smaller than 5mm) found in coastal areas can impact the marine habitat used by endangered species since they may alter sand properties including temperature and permeability. Such alterations may pose a significant threat to marine turtle populations as nest productivity, sexual development, and hatchling fitness are dependent on conditions within the nest, which incubate in the sand. Given that there is a record of microplastic presence at marine turtle nesting sites, this study was conducted to explore the potential influence of microplastics on the thermal profile of sediment typical of marine turtle nesting habitat.MethodsThe experiment was conducted at the Florida State University Coastal and Marine Laboratory where the temperatures of containers of sand mixed with 5-30% v/v of either black or white microplastics were recorded from July to September 2018.ResultsThe addition of microplastics in the sand resulted in an increase in temperature – 0.017°C for each 1% v/v increase in microplastic. However, the color of the microplastic did not have a significant effect on sand temperature. Overall, the container with 30% v/v black particles had the highest mean temperature increase of 0.58°C (± 0.34°C) over the control.DiscussionThe results obtained from this study indicate that extreme concentrations of microplastics could be an issue for marine turtles as any changes in sand temperature may affect the sex ratio of hatchlings and/or alter nest productivity.

Open Access