Abstract
Atolls are at risk of losing their ability to physically adapt due to rising sea levels and coral reefs’ reduced sediment supply, resulting in faster erosion of reef islands. This research examines Aldabra, a raised atoll and UNESCO World Heritage Site in the Indian Ocean with diverse coastal ecosystems, to track shoreline changes against a regional sea level rise of 2–3 mm yr−1. Aerial and satellite images in 1960 and 2011 were used to study 85% of the atoll’s shoreline through a Digital Shoreline Analysis System. Over 51 years, 61% of the shoreline remained unchanged, while 24% changed at an average rate of 0.25 ± 0.36 m yr−1, a low rate compared to global atoll changes. Among the areas that did change, rates of accretion and erosion in absolute values were nearly balanced and affected similar percentages (12%) of the shoreline. However, localized changes were pronounced: for example, part of the lagoon shoreline transformed from a sandy beach to a mangrove habitat, accreting by 214 m over the period. Erosion occurred at crucial turtle nesting sites and the research station. The lagoon shoreline underwent more rapid changes than the erosion-resistant ocean shoreline, particularly in areas exposed to wind and waves. Despite its dynamic shoreline, Aldabra maintained its net shoreline and likely total land area over the past 51 years, akin to other Indo-Pacific atolls—underscoring its adaptive capacity. Our research suggests that current knowledge of geomorphological processes of low reef islands is transferable to the raised Aldabra Atoll, reconfirming similar mechanisms of island-building processes at the island crest. These insights highlight an urgent need to minimize local impacts on sediment availability and transfer that might alter the natural dynamics of the shoreline of reef islands and hence limit adaptation potential. Ongoing shoreline monitoring will remain crucial for informing timely adaptation strategies for the conservation of Aldabra’s unique ecosystem.
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Introduction
Reef islands, including mid-ocean atolls, are considered highly vulnerable to sea level rise because of their low elevation and reliance on healthy coral reefs that are undermined by the impacts of climate change1,2,3. Beyond being the sole habitable area for atoll countries, atolls play a crucial role in maintaining high levels of biodiversity4. Their diverse vegetated ecosystems sequester disproportionately high rates of carbon dioxide contributing to national climate change mitigation efforts5. As sea levels rise, physical changes to atoll’s shoreline and total land area will likely have wide-ranging consequences for the rich biodiversity they support6,7.
Despite their low elevation (with maximum elevations averaging less than 4 m2) and associated vulnerability, atolls are not static landforms that erode and inundate automatically with sea level rise and associated climate change3,8,9. Instead, atolls are dynamic and have evolved to vertically accrete at a pace commensurate with changing sea levels over centennial and even millennial time scales10,11,12,13. By definition, atoll rim islands are actually low-lying accumulations of reef-derived carbonate sediment deposited and organized on coral reef platforms by the dynamic interplay of wave and ocean current processes3,14. The equilibrium of island building relies on the availability of loose, unconsolidated sediments from nearby coral reefs3,15. Such island adjustment involves wave overtopping, which transfers sediment from the front of the island to the crest (highest point) and back of the island9.
Contemporary observations of shoreline and platform changes support atoll island capacity to adjust to current sea level and ocean climate conditions. A global assessment spanning 709 islands across the Pacific and Indian Oceans—representing 30 different atolls—underscored the areal stability of atolls. Specifically, 73.1% of islands remained unchanged in area, while 15.5% increased and 11.4% decreased in size12. Similarly, Webb and Kench, 2010 investigated reef island shoreline change in the central Pacific Ocean over a period that had seen a 2 mm yr−1 increase in sea level (1944–2006) and found that 86% of the atoll’s 27 islands remained stable (shoreline accretion and erosion rates across the atoll were nearly at similar magnitude) or accreted10. Varied mean changes in atolls’ shorelines have been documented in the Indian Ocean region12,16,17,18,19,20,21, with direct human modification of the shoreline contributing to higher rates of shoreline change across different islands17,19,20,21.
Despite recent progress in understanding atoll island morphological responses and increasing evidence of their shoreline resilience, several challenges remain for their future. First, the capacity of coral reefs to supply sediments for island building is increasingly undermined by climate change and ocean warming2,15. Second, under faster rates of sea level rise, the frequency and magnitude of wave-driven flooding events will increase, eventually reaching a threshold preventing recovery of shorelines or entire islands9,22. In addition, anthropogenic impacts including reclamation further exacerbate the situation, leading to diminished adaptive capacities of landforms8,9,23. When island elevation lags behind rising sea levels, a deficit occurs. Consequently, the island crest has minimal or no accretion and is gradually lowered, potentially tilting the balance toward accelerated reef island erosion and destruction3,9.
Given these threats, more research is needed to quantify the ongoing rates of physical changes on atolls. This need is particularly pronounced in the Indian Ocean, where data on island shoreline change rates and locations is scarce. The shoreline dynamism of geologically raised atolls—specifically, atoll rim islands composed of compacted, consolidated subaerially exposed limestone structures—also remain largely unresolved. This lack of understanding poses a challenge when attempting to generalize findings from low-lying reef islands to raised atolls. Consequently, our ability to comprehend the variations in their adaptive capacities in response to sea level rise and associated ocean climate changes is hindered. Developing context-dependent management strategies is especially critical for protected reef islands of ecological significance.
This study aims to fill the gap in knowledge for one of the world’s largest raised atolls, Aldabra. Aldabra is a UNESCO World Heritage Site in the Indian Ocean. The atoll’s four rim islands feature steep cliffs rising approximately 4 to 6 m on the ocean shoreline. Inland from the cliff, the surface rises steeply to a ridge (up to 8 m), which then slopes down to the lagoon side to a low mangrove-vegetated limestone zone at about 1 to 2 m above mean sea level24,25. By examining Aldabra’s shoreline, we contribute to ongoing research on reef island adjustment capacities. Importantly, we extend our understanding beyond low-lying reef islands to include raised atoll islands. In addition, Aldabra is a largely pristine marine area that supports a wealth of endemic and threatened biodiversity, including the world’s largest population of giant tortoises26 and the second-largest breeding population of green turtles in the Western Indian Ocean27,28. Strong linkages exist between the distribution of animals, habitats, and shoreline processes on Aldabra25,29,30,31. Given these linkages and the 2–3 mm yr−1 sea level rise for coastal areas within the Mozambique Channel from 1993 to 201318, it is important to assess the rate and location of shoreline change at this ecologically important site. Finally, Aldabra’s lack of human settlements, aside from a research station, renders it an ideal baseline for understanding the natural dynamics of shoreline, in contrast to other atolls that human activities have extensively modified.
Our study focuses on relative shoreline changes across the atoll, taking into account both the rise in sea level and any potential changes in land elevation from island uplift or subsidence. We use modern and historical datasets to examine shoreline change at Aldabra and specifically answer three questions: (1) What is the rate of shoreline change on Aldabra from 1960 to 2011? (2) Where are shoreline changes occurring and how do the changes relate to shoreline aspects? (3) Do shoreline change rates differ between the lagoon and ocean coasts?
Methods
Study site
Aldabra Atoll (9°24′S, 46°22′E) is part of the Seychelles archipelago and is ca. 1000 km southwest of the main island of Mahé, 420 km northeast of Madagascar and 630 km east of the East African coast. Aldabra is a raised atoll elongated east–west, with a maximum length of 34 km25. The atoll has a land area of 155 km2 and a mean elevation of 8 m above sea level25. The four atoll-rim islands that encircle Aldabra’s central (203 km2) lagoon are Polymnie, Picard, Malabar, and Grande Terre25,32.
Aldabra has experienced dramatic sea level fluctuations during glacial and interglacial periods, resulting in its transformation into a steep-sided, large rocky island, possibly up to 100 m high relative to sea level during glacials, and partial or complete submergence during interglacials33,34. The atoll consists of four major Late Pleistocene marine limestone units. Among these, the Aldabra Limestone is the youngest and has been reliably dated to be 118,000–136,000 years old35. Additionally, terrestrial sediments have accumulated in shallows and cavities, all younger than the limestone layers they overlay24,35.
Aldabra’s current climate is influenced primarily by the prevailing wind direction. The east and southeast monsoons blow strongly and consistently over the atoll from May to October31,36, during which the atoll receives ca. 25% of its yearly mean rainfall of 975 mm37. From November to April, the wet northwest trade wind brings calmer conditions31,36. Aldabra’s south and east shorelines experience higher wave activity and are more exposed to the prevailing wind and waves than the north coast29.
Imagery processing
We compared the shoreline extracted from aerial and satellite imagery acquired in 1960 and 2011, respectively. Aerial imagery of Aldabra was captured from an aircraft in June 1960 by the Directorate of Overseas Surveys (DOS), a British government agency responsible for mapping the British Empire and countries throughout the Commonwealth. Prints of the original greyscale images and metadata containing flight height and survey date were stored at Aldabra’s research station. In March 2013, the University of Zurich secured the imagery for processing. We obtained the calibration and test report for the air camera used in the survey from the National Collection of Aerial Photography, the official custodian of imagery generated by the DOS. The metadata and calibration report were crucial for the aerial imagery processing. We scanned the aerial imagery at a resolution of 1600 dpi to yield a digital image with a ground sampling distance of 0.25 m. We used Erdas imagine software v 16.5 (Hexagon Geospatial, Nasdaq, Stockholm, Sweden) to orthorectify and project the digitized aerial image prints onto the UTM coordinate system using a ‘photogrammetric workflow’ for historical aerial imagery (Appendix A).
We used four satellite images of Aldabra acquired by the GeoEye-1 satellite from Digital Globe (Digital Globe, 2011). These images, with a spatial resolution of 2 m, were obtained in November 2011 and consist of four bands with spectral ranges 450–510 nm (blue), 510–580 nm (green), 655–690 nm (red) and 780–920 nm (near-infrared; NIR). Philip Haupt preprocessed the four images using methods described in Walton et al., 201930.
Shoreline extraction
The edge of vegetation often serves as a shoreline indicator, the boundary between land and ocean10. However, on Aldabra, the vegetation line does not necessarily correspond to the boundary on the ocean-facing shores. Here, the limestone shelf or outcrops, fronted by an intertidal and shallow subtidal platform, are often bare, and there is a considerable absence of sandy foreshore or vegetation. For this reason, we determined the shoreline to be the boundary between the atoll’s limestone shelf and the ocean. The limestone deposits extending seaward align with the definition of the shoreline as a stability line11,17, emphasizing features that correspond to the external limit of the stable part of the shoreline. For the lagoon shores, we used the edge of vegetation as the shoreline indicator. Mangroves predominantly cover the limestone boundary of the lagoon, finding niches within crevices, limestone blocks, or undercut creeks where soil has accumulated. The presence of mangroves suggests specific substrate conditions, as well as tidal and wave influences, that support tree growth29,31 and thus accurately approximate the island’s boundary with the lagoon. Further, these two boundaries (limestone shelf-ocean and mangrove-lagoon) are discernible from remotely sensed imagery. They are representative of the longer-term shoreline changes we expect on the atoll (see also17,38). We used ENVI (NV5 Geospatial, Boulder, Colorado) and ArcGis 10.8.1 software (Environmental Systems Research Institute) to extract the shoreline from the 2011 GeoEye imagery. We initially applied a band math expression in ENVI, specifically the NIR-Red Ratio (NRR) index39,40, to the bands of the 2011 GeoEye raster (Fig. 1). The NRR has been effectively used for distinguishing water and land pixels in imagery40. It is defined as:
whereas \({\rho }_{NIR},\) \({\rho }_{red}\) are the reflectance values in the NIR and red spectral bands, respectively. Pixels with lower NRR (greater than, but close to zero) have small differences between the red and NIR reflectance and are indicative of water surfaces; bare soil or other non-green materials have slightly higher positive values (> 1). The greater the difference between the red and near-infrared reflectance (far beyond 1), the greater the amount of green vegetation present41. We applied a histogram threshold of 1 to the band ratio output to separate water (≤ 1) and land pixels42. The output was a binary image where 0 values corresponded to water and 1 corresponded to land. Upon visual analysis, all 1’s corresponded to land, but a few water pixels were assigned to land (1) as well. The water pixels that the NRR had not distinguished were mostly shallow coral heads in the water. We used the binary image from the thresholding to create a water mask. Then we applied the water mask to the GeoEye imagery and performed an ISODATA unsupervised classification, resulting in the identification of two distinct classes43. This step effectively separated water pixels that had not been correctly picked up by the NRR (e.g., shallow coral heads in the water) from the actual land pixels. We used the 'raster to polygon’ tool in ArcGIS to extract a land polygon and then converted the polygon into polylines to get the 2011 shoreline. We overlaid the shoreline on the 2011 image and visually assessed and manually digitized portions of the shoreline that deviated from the image.
Workflow for shoreline extraction of 2011 (left column) and 1960 (right column) imagery. The example is developed using a southeast section of Grande Terre Island of Aldabra (A). The NIR-Red Ratio (NRR) is applied on the bands of the GeoEye 2011 imagery, and the output (shown) is used to create a water mask based on histogram thresholding (B). The water mask created from B is applied to the GeoEye imagery and an unsupervised classification of the remaining pixels of the 2011 imagery is done to group them into two classes according to their spectral properties. The effect of the classification is to remove water pixels, such as shallow coral heads (blue pixels shown) that are not picked up by the NRR (C). The land polygon is attributed and a polyline layer is extracted from the polygon boundary. The polyline is visually assessed to adjust for errors and a final 2011 shoreline is created (D). The 2011 shoreline is used as the reference layer for the 1960 shoreline and overlaid on the 1960 imagery (E). The 1960 imagery is segmented—pixels are grouped according to similar spectral, spatial, and texture values—so that they represent objects showing land-based features, e.g. edge of limestone reef (F). The segments created simplify the process of tracing shoreline change hence are used for the computer-aided visual interpretation of the shoreline. The shoreline is backdated by interpreting the reference shoreline and tracing the changes. The identified changes can only be accepted with the criteria of a minimum width of 2 m from the reference shoreline to account for the difference in spatial resolution of the two imageries and corresponding uncertainty (G). The polylines of change in 1960 are merged to the polylines that remained the same from 2011 and the rest are eliminated, providing the final 1960 shoreline layer (H). Appendix C for workflow in higher resolution. The workflow was generated from the 2011 GeoEye-1 satellite imagery (left) and greyscale imagery (right) using ENVI NV5 Geospatial software (https://www.nv5geospatialsoftware.com/Products/ENVI) and ArcGIS 10.8.1 (https://www.arcgis.com/index.html).
We used a backdating, computer-aided visual approach44,45 to extract the shoreline from the 1960 imagery in ArcGIS 10.8.1 software (Fig. 1). The 2011 shoreline was overlaid on the 1960 imagery and used as the reference for the 1960 shoreline layer. Unchanged shorelines were maintained without any modifications. We traced the correctly aligned polylines in locations where we identified changes using the ‘tracing’ tool. The tracing of the changed 1960 shoreline was guided by polygons that represented segments of the 1960 imagery pixels grouped according to similar spectral, spatial, and texture values—so that they represent objects showing land-based features, e.g. the edge of limestone reef. We used ENVIs 'feature-based extraction’ to segment the 1960 imagery with settings; scale (45), merge (90) and kernel (11). The identified changes were accepted with the criteria of a minimum width of 2 m from the reference shoreline to account for the difference in spatial resolution of the two imageries44,45. Finally, we merged the updated and unchanged polylines to obtain the 1960 shoreline. The 1960 shoreline used in the analysis represented 85% of the total shoreline of Aldabra—the unanalyzed sections of the 1960 imagery were the result of individual images that lacked control points for correct orthomosaicking (Appendix A). The missing data was distributed across the atoll without specific spatial patterns, meaning no systematic lack of data for a specific location or island was observed. The benefit of this backdating approach was to minimize the introduction of errors into shoreline change detection as a result of independent generation of shorelines from data of different spectral and spatial resolutions16,44,45. In addition, this approach improved confidence on the 1960 shoreline extraction because we visually inspected the shoreline in relation to tidal uncertainties that could not be accounted for in the definition of the shoreline (see “Shoreline change rates” section).
Statistical analysis
Shoreline change rates
We used the Digital Shoreline Analysis System (DSAS) software to detect changes in shorelines between 1960 and 2011 on Aldabra. We used the DSAS version 5.046 as an extension within ArcGIS 10.8.1. Firstly, we generated transects at 50-m intervals along a reference baseline. This interval was deemed sufficient to capture the trend in shoreline change on Aldabra, especially around narrow shore bends46. We generated the baseline from a smoothed buffer of the 2011 shoreline to maintain the general meandering of the shore. The transects were generated at a 90° angle along the reference baseline and they intersected the 1960 and 2011 shorelines at specific positions. Secondly, we calculated two shoreline change metrices (distance and rate) from the DSAS based on the shoreline intersections. The net shoreline change is the distance between two shoreline positions intersecting a given transect. Because we analyzed net shoreline change for only two shorelines, this metric is equivalent to the shoreline change envelope (distance between the shoreline furthest from and closest to the baseline at each transect). The rate of shoreline change (also known as end point rate) is the net shoreline change divided by the time elapsed between the two shorelines. Positive (negative) values indicate an accretional (erosional) change or change rate. Thirdly, for each shoreline, we calculated two uncertainty values (Table 1; Eqs. 1 and 2). The shoreline uncertainty (\({U}_{l}\)) (Eq. 1) accounts for three critical factors related to shoreline extraction47,48—the level of detail in the image (spatial resolution), the accuracy in the digitization of the shoreline (tracing), and the georeferencing that ensures that the shorelines from different times align correctly (georeferencing). The shoreline change rate uncertainty (\({U}_{c}\))46 in Eq. 2 estimates the uncertainty introduced when calculating how fast the shorelines changed by taking the square root of the sum of squared shoreline uncertainties (\({U}_{l}\)) for two different years (2011 and 1960) divided by the time difference between those years. We did not include tidal correction in our uncertainty estimates for two main reasons. First, the 1960 imagery was acquired over two days, introducing significant tidal variability during data collection, hence it was not possible to assign a single tide level to the imagery. Second, the tidal data for Aldabra is accurate only at the research station, with a time lag of up to four hours in the lagoon, which restricts our ability to extend corrections accurately across the entire atoll.
where: \({U}_{l}\) is the shoreline uncertainty for shoreline i, \({U}_{r}\) is the spatial resolution of the image, \({U}_{t}\) is the tracing uncertainty associated with digitizing the shoreline, \({U}_{g}\) is the georeferencing uncertainty between images of the two time points, \({U}_{c}\) is the shoreline change rate uncertainty and \({{D}_{l}}_{start}\) is the start year (1960) and \({{D}_{l}}_{end}\) the end year (2011) of the time range of shoreline change. We used the root mean square error of ground control points during the orthorectification as the georeferencing uncertainty for the 1960 imagery (Table 1). We used a tracing uncertainty of 1.00 m for the 2011 imagery in line with studies based on imagery with a similar spatial and spectral resolution47,48. The tracing uncertainty for the 1960 imagery was inherent to the 2011 tracing uncertainty (1.00 m) because of the backdating approach we used to derive the 1960 shoreline. We added 1.00 m to the tracing uncertainty of the 1960 shoreline (2.00 m training uncertainty overall), notably due to difficulties in determining the position of the shoreline in a few areas with shallow reefs close to the shoreline.
Lastly, we integrated the calculation of the shoreline change rate with the overall uncertainty for each transect (Eq. 246). Transects with change rates that fell within an envelope of change, i.e. ± \({U}_{c}\), were regarded as having no change. Transects with change rates outside of this interval were regarded as having measurable changes in the shoreline. Example: A shoreline change rate of − 1.20 m yr−1 with a \({U}_{c}\) value of 0.50 would be considered significant, as it reports a range of − 1.27 to − 0.70 m yr−1, where the minimum and maximum values are still negative. The calculation of the shoreline change rate and uncertainty ensures that only shoreline changes surpassing a determined threshold—which includes uncertainties such as spatial resolution—are deemed significant, thus substantially reducing the likelihood of false detections.
To understand shoreline change rates on Aldabra, we tabulated a summary of shoreline change rates recorded across all transects for accretional, erosional and atoll-wide changes for individual islands, lagoon or ocean transects. The summary for accretional and erosional shoreline change rates used transects with measurable changes. Shoreline change rates for the smallest island of Polymnie were merged with those for adjacent Malabar Island.
Shoreline change location, aspect influence and lagoon-ocean comparison
We summarized the information on shoreline change location in three ways. First, to make generalizations about the location of changes in relation to the three main islands, we mapped the net shoreline change on Aldabra. Second, we assessed the relationship between shoreline change location and shoreline aspect, by calculating the aspect for transects with significant change. Aspect is pivotal as it determines exposure to prevailing winds and the waves they generate. The aspect was deduced from transect azimuths (direction of the transect clockwise from north, in degrees) in ArcGIS, with a north-facing coast represented by an aspect of N (0°). We grouped the transects and calculated their mean shoreline change rates across eight 45° cardinal directions sectors. The sectors are defined as follows: parentheses mean open interval (non-inclusive), and square brackets mean closed interval (inclusive). N: north (337.5–22.5 degrees]; NE: northeast (22.5–67.5 degrees]; E: east (67.5–112.5 degrees]; SE: southeast (112.5–157.5 degrees]; S: south (157.5–202.5 degrees]; SW: southwest (202.5–247.5 degrees]; W: west (247.5–292.5 degrees]; NW: northwest (292.5–337.5 degrees]. Third, we compared differences in shoreline change rates for lagoon and ocean shorelines using an unpaired t-test. We used an unequal variance t-test, as the two groups of data had unequal variances based on the results of a Levene’s test.
Results
Shoreline change rates
We analyzed 85% of Aldabra’s total shoreline for changes over 51 years. From 1960 to 2011, 24% of the shoreline on Aldabra changed at a mean rate of 0.25 ± 0.36 m yr−1. Erosion affected 12% of the shoreline, with a mean rate of -0.25 ± 0.38 m yr−1, while 12% accreted at a mean rate of + 0.24 ± 0.33 m yr−1 (Table 2). Picard had the maximum accretion rate of + 3.13 m yr−1, equivalent to a net change of 161 m over 50 years, on the lagoon (see appendix B for net shoreline change values). The maximum erosion rate of − 214 m (− 4.20 m yr−1) was recorded on the lagoon shoreline of Grande Terre. No measurable shoreline change was recorded on 61% of Aldabra’s shoreline during this time period.
Shoreline change location, aspect influence and lagoon-ocean comparison
Among Aldabra’s rim islands, Grande Terre experienced the most shoreline change in 51 years, with 20% of its analyzed shoreline eroding, while 17% accreted. The ocean shoreline on east and southeast Grande Terre was generally erosional, especially from Anse Cèdres to Dune Jean-Louis (Fig. 2). Notable erosion (> 10 m) was observed within about 4 km of the lagoon shores of Grande Terre in Cavalier area. Accretion was observed East of Point aux Vaqua and Dune d’Messe. On Picard, the net shoreline change was more variable: the highest accretion recorded for the entire atoll occurred in the relatively sheltered sandy area of La Gigi (Appendix D). Settlement Beach, the atoll’s most extensive beach, exhibited a shift from accretion to erosion along its length from north to south. Additionally, the Picard shoreline experienced further erosion extending from the northern end of Settlement Beach towards Anse Var. In total, 16% of Picard’s shoreline accreted and 10% eroded. Amongst islands, Malabar experienced the least shoreline change, with 75% of its shoreline showing no change over 51 years.
Net shoreline change on Aldabra Atoll from 1960 to 2011. Insets show two areas with the highest accretion (La Gigi) and erosion (Cavalier) recorded across the atoll during the study period. The map was generated using GeoEye-1 satellite imagery (Digital Globe, 2011) and processed with ArcGis 10.8.1, https://www.arcgis.com/index.html. Insets on the map have been modified from GeoEye-1 satellite imagery (left) and orthorectified greyscale imagery captured in 1960 by the Directorate of Overseas Surveys (right).
Lagoon shorelines on Aldabra Atoll had the greatest accretional and erosional change when exposed to the dominant east and southeast winds (Fig. 3). Ocean transects showed varying shoreline change according to their aspect—none of the east-facing shoreline experienced accretion except for a few embayed beaches on Malabar. Overall, the lagoon shoreline had a higher mean change (0.32 ± 0.45 m yr−1) than the ocean shoreline (0.15 ± 0.09 m yr−1, P < 0.001, t = 8.93, df = 710).
Accretional (left) and erosional (right) change on Aldabra Atoll, Seychelles. The mean accretion and erosion change in meters is displayed (grey dashed circles indicate 0, 10 and 50 m change for scale) according to aspect for the lagoon and ocean shorelines. A shoreline with a northerly aspect (0°) corresponds to a north-facing coast (land on south side, ocean on north side of the shoreline).
Discussion
Between 1960 and 2011, 61% of Aldabra’s shoreline showed no measurable change. Shoreline accretion and erosion rates across the atoll were of similar magnitude and affected similar percentages (12%) of the shoreline. Where the shoreline changed, it did so at an average rate of 0.25 ± 0.36 m yr−1, which is in the lower range for the average rate of shoreline change on atolls over centennial time scales in studies spanning more than 15 years10,17,18. Palmyra Atoll in the Pacific Ocean recorded the highest average change rate of 0.50–0.80 m yr−1 over 126 years, primarily due to extensive military construction between 1940 and 1945, which included the creation of a dredged channel into the lagoon49. In contrast, Maiana Atoll of the Gilbert Island chain in the Pacific Ocean had the lowest recorded rate of shoreline change of < 0.20 m yr−1 from 1969 to 2009. Our results are consistent with those of Purkis et al.17, who observed similar shoreline change rates in Diego Garcia, a militarized atoll in the Indian Ocean, from 1963 to 2013. The average rate of shoreline change there was 0.30 m yr−1, although this value doubled to 0.60 m yr−1 for the area of shoreline with the military base. Our study concurs with previous findings10,12,17,18,50, emphasizing that despite their apparent intrinsic vulnerability, atolls are dynamic landforms that can adjust their shoreline morphology by balanced erosion and accretion processes, thereby maintaining or even increasing island area.
Our study looked at changes averaged over more than 50 years and did not capture the dynamics of shoreline change across shorter time scales, which could reveal distinct patterns and trends. For example, we could not assess if the rates of change have increased in recent decades due to accelerated sea level rise or coral reef deterioration. Recent studies highlight the vulnerability of Aldabra and other islands to sea level rise and flooding from waves1,51,52. Global sea level is expected to rise by 0.44 ± 0.17 m (under RCP2.6) by the end of the century51. Under a high greenhouse gas emission scenario (RCP8.5), 17% of Aldabra’s total area will be exposed to flooding events52. Although these flooding projections represent worst-case scenarios based on the inert reef island model, the frequency of overwash processes and magnitude of wave-driven flooding events will be enhanced by sea level rise1,2,22,53. Eventually, a critical threshold may be reached, which limits vertical accretion, compromising the adaptive capacity of atolls in the coming decades9. These predictions underscore the urgent need for continued shoreline monitoring to inform timely adaptive management strategies for atolls. Notably, our study focused on relative shoreline change rates, not separately analyzing uplift and sea level rise effects. Yet, from a management perspective, uplift’s < 0.2 mm yr−154 impact seems negligible in the context of climate change.
Despite the low average rate of shoreline change on Aldabra, net shoreline changes of up to 161 m were recorded over 51 years on a single transect at La Gigi, where the shoreline accreted from a sandy to a mangrove-vegetated shoreline (Fig. 2). Aldabra has been strictly protected since 1979; mangroves were harvested for timber and bark until 196655. Images captured in the 1900s25,55 show infrastructure on a sandy shoreline at La Gigi—close to the atoll’s settlement—to process and accommodate mangrove wood for export to the inner Seychelles. It is likely that once mangrove logging stopped, the sandy shoreline faced progressive sediment deposition, with greater sediment retention provided by growing mangroves. Thus, historical human modification of this shoreline is likely to have contributed to one of the highest rates of shoreline change recorded on the atoll over the study period. This is consistent with findings that local factors, including human modification of the shoreline, increase exposure and vulnerability to shoreline hazards8 and underscores the importance of conservation efforts to mitigate further human impact. Importantly, it also suggests that affected shorelines can revert to former conditions once disturbance has ended.
In contrast, considerable erosion at 4.20 m yr−1 occurred at the Cavalier area along nearly 4 km of shoreline on Aldabra from 1960 to 2011. This mangrove-vegetated part of the lagoon shoreline experiences the highest range of wave power on the atoll31. It is likely facing continued erosion of the limestone substrate, leading to the inundation of mangrove trees and loss of the shoreline due to its exposure to the longest fetch (total distance over the water that the wind can blow) of the strongest wind power from the east/southeast in the lagoon31. From May to October, the monsoon reaches the highest mean wind speed throughout the year31,36, mainly affecting shorelines with an east- and southeast aspect. The ocean shoreline along the east and southeast of Grande Terre also experienced significant erosion (Fig. 2). This stretch of coastline faces the highest wave and wind activity on the atoll29.
Waves also contribute to building and shaping coastlines23. Specifically, the localized erosion and accretion observed on Aldabra’s shoreline in our study might partially stem from the timing of image capture during different monsoonal seasons—1960 in June and 2011 in November. Reef island beaches exhibit significant shifts in shoreline position between seasons, reflecting changes in sediment movement due to biannual reversals in wind and wave conditions56. Despite these seasonal fluctuations, the overall net change remains relatively small56. For Aldabra, we anticipate a more pronounced seasonal response along the sandy shoreline of the lagoon with heightened impact from seasonal wave conditions29,35. In contrast, the ocean shoreline, which is not fetch limited, experiences less extreme external wave conditions reversal year-round, likely resulting in minimal morphological changes seasonally.
Our study also investigated the difference in change rates between the lagoon and ocean shorelines of Aldabra over 51 years to understand their responses to longer-term changes in wind, wave and sea level conditions. The lagoon shoreline of Aldabra had a higher average rate of change compared to the ocean shoreline, highlighting an important difference in the interaction of intrinsic drivers (e.g. island crest, sediment supply and transfer, reef growth, substrate type) and extrinsic factors (including the rate of sea level rise and overtopping frequency) that govern shoreline changes in this unique dual-type reef island shoreline. Fundamentally, the lagoon shoreline is lower and characterized by a flat supra-tidal landscape heavily influenced by sediment deposition, transport and mangrove extent change29,31. Mangroves can respond to changes in sea level rise and wave regimes, up to a certain threshold, by vertical elevation from sedimentation and organic matter preservation57. In this sense, the lagoon shoreline of Aldabra Atoll can be likened to other dynamic low-lying atolls where sediment transfer from nearby reefs helps the vegetated shoreline to accrete by the action of waves on the island crest. On Aldabra, the lagoon shoreline benefits further from a supplement of consolidated sediments from the limestone deposits substrate34. That the mangrove extent on Aldabra has increased at a rate of 0.23% yr−1 over 21 years31 suggests that the rate of deposition on the lagoon is currently higher than the rate of substrate loss.
In comparison, the ocean shoreline presents a steeper and more resilient rock morphology, changing at half the rate observed in the lagoon. After the widespread deposition of Aldabra limestone during the Late Pleistocene35, a subsequent interrupted fall in sea level formed an 8 m ridge on the ocean coastline and a prominent 4–6 m terrace (24,25 p. 38 for map of Aldabra’s topography). Notwithstanding the complex geology of these separate depositions, where the widespread 4–6 m terrace occurs on Aldabra, we observed both erosion and accretion processes. However, the majority of the shoreline did not change. Further, we observed no shoreline change and slight shoreline accretion where present-day erosion intersects the 8 m ridge directly (absence of the 4–6 m terrace), such as at Point aux Vaquas, east of Dune d’ Messe and on Malabar and Polymnie Islands. These high vertical cliffs on Aldabra are likely collapsing in blocks of resistant limestone, which fall in position25. The fallen reef platform over time has produced fine carbonate sands and formed perched beaches, especially on the windward south coast of Aldabra24,33. Occasionally, sand continues to accrete into sand dunes that reach up to 18 m on Grande Terre. This island-building response observed on Aldabra, where wave overtopping—likely during spring tides, storms, and extreme weather events—drives substantial crest accretion on the ocean shoreline, is in keeping with models of island change for low-lying atolls3. However, due to Aldabra’s wide expanse (approximately 1 km at its narrowest point, except near the channels), the extent to which sediment accretion on the ocean shoreline can facilitate lagoon shoreline accretion is uncertain. Elsewhere along the ocean shoreline, particularly on Malabar, differential erosion of various limestone deposits likely contributed to the formation of embayed beaches and observed dynamics of the shoreline.
The raised limestone ocean shoreline of the atoll presents an erosion-resistant face to ocean conditions. However, over time, albeit slowly, the cliff line will gradually weaken and retreat landward3,24,25. The extent to which the frequency of the overtopping processes at the ocean shoreline will continue to raise the land surface through sediment deposition relies also on the health of coral reefs9. Reef productivity not only ensures sediment production but also helps attenuate wave energy21,58. Remarkably, erosion observed from Cinq Cases to Dune Jean-Louis along Aldabra’s ocean shoreline, an area of high wind and wave activity, coincides with the only marine site not meeting the resilience threshold for coral reefs on Aldabra59. Despite increasing reef bleaching frequency and intensity60, Aldabra’s reefs have remained resilient so far61,62 and are a vital source of larvae for the region63. From a management perspective, it is essential to reduce local direct human impacts, including tourism, affecting coral reef resilience and health and thoughtfully evaluate any infrastructure changes affecting reef sediment injection into the island system21.
We identified shoreline change occurring in locations of importance to endemic and threatened species on Aldabra. Notably, the main green turtle nesting beaches, including Settlement Beach, Anse Var, Dune d’Messe, and Dune Jean-Louis27, have experienced varying rates of erosion. Despite this, the green turtle population has not only recovered to historic numbers28 but turtles may also be exhibiting adaptive nesting behavior by favoring areas of the beach that are accreting. Aldabra’s biodiversity will be challenged by island erosion and accretion, among many other factors. Consequently, the adaptability of species and habitats to these physical changes becomes increasingly crucial. Our findings underscore the importance of Aldabra as a baseline for regional conservation efforts and highlight the need for ongoing monitoring to safeguard its endemic and threatened species.
Aldabra’s settlement on Picard faces severe erosional threat. The erosional change endangers existing infrastructure, including the south of Settlement Beach research station. We have validated the observed shoreline change (Fig. 2) with historical images55 and anecdotal reports, especially since 2010 from Aldabra. Historical images reveal a cemetery on Settlement Beach that is now almost completely eroded. In the 1960s, this cemetery was more than 20 m away from the highest water mark (55, p 612). Additionally, where over eight adult trees stood on Settlement Beach in 1908, only two remain today, with exposed roots and a significantly altered shoreline landscape. The research station itself, initially constructed more than 30 m inland from the highest water mark, now bears deep erosion scars (A. Constance, pers. obs., Feb 2023) and is currently unusable during spring tides. This erosion is likely to persist, demanding urgent adaptation strategies, including relocating the research station.
Conclusion
This study quantified the long-term shoreline change of Aldabra Atoll, a protected, raised atoll in the Indian Ocean, to understand its vulnerability to climate change effects, especially sea level rise. We found that the majority of the atoll’s shoreline did not change from 1960 to 2011. Where the shoreline changed, it did so at a slower rate (0.25 ± 0.36 m yr−1) than other atolls in the world. The extent and magnitude of shoreline erosion and accretion were balanced, meaning that Aldabra’s overall shoreline (and likely total land area) remained unchanged and stable over the 51-year study period. Changes were evident for locations with an east and southeast aspect, around Aldabra’s main infrastructure, and, especially in the lagoon, due to exposure to wind and waves. Additionally, Aldabra’s geological history, characterized by limestone deposition, has influenced the differential rates of shoreline erosion and accretion, as well as their specific locations. We emphasize the importance of continued shoreline monitoring as sea level rise accelerates and physical conditions for species, habitats and infrastructure change.
Our study provides essential data for Aldabra’s adaptation measures, including identifying locations of greatest shoreline change, understanding rates and implications, and advising the immediate relocation of the research station. Furthermore, our findings reveal that akin to low-lying unconsolidated reef islands, Aldabra’s raised rim islands have maintained their net shoreline. Notably, they exhibit a variable response—from stability to erosion and accretion—reaffirming similar mechanisms of island-building processes at the island crest using consolidated and unconsolidated sources. These insights contribute to our understanding of how uplift impacts the reef island adjustment process, building upon existing knowledge derived from the study of unconsolidated reef islands. Finally, our study sets a regional baseline for shoreline change rates on an atoll minimally affected by human activity.
Data availability
Data is provided within the manuscript or supplementary information files.
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Acknowledgements
The authors would like to thank the Seychelles Islands Foundation and Zurich-Aldabra Research Platform for facilitating the image scanning work and providing access to original imagery captured in 1960 over Aldabra. Many thanks to John Shekeine, who digitized more than 400 original 1960 images. The authors would like to thank Philip Haupt for preparing the GeoEye imagery captured in 2011 over Aldabra and the Global Environment Fund (project ID 3295), which funded the imagery’s acquisition. Thanks also to Elena Plekhanova for discussions on methods. The University Research Priority Program on Global Change and Biodiversity of the University of Zurich (URPP-GCB) supported the contributions of Annabelle Constance and Gabriela Schaepman-Strub.
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A.C: conceptualization, methodology, formal analysis, writing—original draft preparation. N.B: conceptualization, writing—review and editing, supervision. N.L: software, methodology, validation, formal analysis. S.N: software, methodology, validation. D.O: writing—review and editing F.FD: investigation, resources, writing—review and editing. G.S: conceptualization, methodology, validation, writing—review and editing, resources, funding acquisition, supervision. All authors reviewed the manuscript.
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Constance, A., Bunbury, N., Lack, N. et al. Low average shoreline change rate in 51 years on the raised Aldabra Atoll. Sci Rep 14, 28970 (2024). https://doi.org/10.1038/s41598-024-74595-y
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DOI: https://doi.org/10.1038/s41598-024-74595-y