The identification of variables that influence the nesting beach selection and the specific nesting site location within the beach by marine turtles has been a focus of ecological research for a long time. Despite this effort, there is still a basic conservation and ecological need to understand the reasons for nesting preferences because of the implications that this has for adequate protection strategies for critical nesting habitats and nesting populations.

A large number of variables influence nesting-site selection by sea turtles around the world, including beach morphology (beach slope, orientation, width), nearshore oceanographic conditions, and a series of microscale variables, such as grain size, humidity, pH, temperature, sand compression, among others (Provancha and Ehrhart 1987; Mortimer 1990; Horrocks and Scott 1991; Glen and Mrosovsky 2004; Kamel and Mrosovsky 2006; Mrosovsky 2006).

The Yucatán Peninsula, located in southeast Mexico, harbors the largest nesting population of hawksbill turtles (Eretmochelys imbricata) and 1 of the 5 largest of green turtles (Chelonia mydas) in the Atlantic (Hirth 1997; Meylan and Donnelly 1999). However, the coast of the Yucatan peninsula is experiencing dramatic erosive processes, hence, negatively modifying, and even destroying, important segments of sea turtle nesting beaches in the region. This problem already had been recognized by Abreu-Grobois et al. (2005), when the evaluation of the degradation of nesting habitat for the hawksbill and green turtles, especially for hawksbills because of its critically endangered situation around the world (Mortimer and Donnelly 2007) and particularly on the Yucatán Peninsula (Abreu-Grobois et al. 2005), was defined as a research and conservation priority. Based on these facts and also by recognizing this problem, field work was conducted to study beach morphology in El Cuyo, Mexico, and assess its link to hawksbill and green turtles nesting activity in that area.

Methods

The sea turtle nesting beach at El Cuyo is located at the northeast corner of the Yucatán Peninsula, within the Ria Lagartos Biosphere Reserve and Rio Lagartos Sea Turtle Sanctuary. This nesting beach is 25-km long, and it is split approximately in half by the community El Cuyo. The Mexican nongovernmental organization Pronatura Península de Yucatán has monitored this beach for sea turtle nesting activity since 1988; for the purpose of this research, the nesting records from 1990 to 2006 were used. This period of time was selected because it was considered that in 1988 and 1989, the monitoring procedure was still being standardized by Pronatura, hence, we took data starting on 1990. This study was done in 2006, which is the limiting year for this study.

El Cuyo is one of the most important hawksbill nesting beaches on the Yucatán Peninsula (Garduño et al. 1999) and the second-most important for green turtles on the north coast of the peninsula (K. López, unpubl. data, 1999; Xavier et al. 2006).

Based on the highest sea turtle nesting densities in El Cuyo in the last 17 years, we established 14 shore-normal transects based on a stratified design, with a shorter separation distance between benchmarks at the zones with highest nest densities, for monitoring beach profiles every month from April to September 2006 during sea turtle nesting season in the region (Fig. 1). At each site, a benchmark was installed as a reference, and beach elevations were measured approximately every 5 m along the shore-normal transects with a SOKKIA C3₁₀ auto level. The presence of any significant topographic features (e.g., small steps, hills, and trenches caused by previous wave action on the beach) and the water-line position were recorded as well. These measurements were made once a month during the 6 months (April through September) that nesting season lasts.

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Data from the beach profiles were integrated into a database for basic first-order statistical analysis. Then, each profile was individually interpolated by using a 1-dimension linear method, which estimates unknown values between 2 known points by using a linear mathematical function (MATLAB Function Reference, 2007). The obtained results were beach profiles that contained elevation values every 10 cm in the offshore coordinate rather than having elevation values at irregular offshore intervals; this also aided in accomplishing the linear assumption between neighbor points imposed by the mathematical function. This whole procedure also allowed the temporal comparisons of beach profiles at each survey site standardizing the beach height measurement sites.

By using the interpolated data, the temporal average profile was estimated at each site and the associated morphological variables were estimated. The following variables were examined: total, dune, backshore (area on the beach lying between the mean high tide mark and the dune vegetation) and foreshore (area of the beach lying between the mean high tide mark and the average low tide mark) slopes, and beach width (dry zone) available for sea turtle nesting.

To summarize and extract the most of the variability from the morphological measurements (5 morphological variables), a principal components analysis (PCA) was performed for each profile (centering and standardizing the variables). The 2 components (eigenvectors) that concentrated the highest percentage of variability were considered for the following performed analysis, and the most relevant morphological variables for each component was determined for the correlation analysis with nesting records (Ficetola 2007). Nesting data from 2006 were also recorded along the entire beach and included date, position on the beach profile (swash [the beach profile zone over which waves wash freely], berm, and vegetated zones), and geographic coordinates for each nest.

The spatial analyses made in this assessment considers the evaluation of the phenomenon known as spatial autocorrelation, which is present when the values of the studied variables in neighbor sites are not independent (Dormann et al. 2007). Among the causes of the spatial correlation is the interaction between species in same site (as in this study), nonlinear relationships between the habitat and the evaluated process (Lichstein et al. 2002). This spatial autocorrelation has been recognized as an indicator of a nonrandom nesting-site selection on the beach by the marine turtles (Weishampel et al. 2003); therefore, the spatial autocorrelation was evaluated by using the global Moran's I index for the nest records from 1990 throughout 2006 by using the program GeoDa (v.0.9.i5, Anselin and the Regents of the University of Illinois, 2004). The analysis was made with the mean density of nests per 0.5-km polygon segments of beach, by attributing the geographic coordinates of the polygon segment's centroid to its corresponding density. Correlograms were made, and their statistical significances were assessed by 999 Monte Carlo permutations (Fortín and Dale 2005; Schabenberger and Gotway 2005).

The assessment approach adopted here was a population level 1 for the evaluation of the resources usage and their availability, by considering the used, nonused, and available resource units in the study area and for the whole nesting population (Manley et al. 2002). A 500-m buffer was established around each monitored benchmark and the registered nests in 2006 for both species were recorded inside that area. Ordinary linear Spearman correlation analyses were made between the number of registered nests in the range and the dominant morphological feature in each of the 2 main components from the PCA to assess the influence of beach slope and width on the sea turtle nesting activity.

To verify the proper application of the ordinary Spearman correlation analysis for these data, the spatial autocorrelation in the residuals derived from the above correlations was assessed. The Moran's I index and 999 Monte Carlo permutation analyses were repeated. No significant statistical autocorrelation was found; hence, it was not necessary to use more complex spatial analysis for the correlation analyses (Lichstein et al. 2002; Kühn 2006; Dormann et al. 2007). Finally, when considering the number of recorded nests per species in each portion of the nesting beach (east and west sides), the nesting preferences were evaluated by using a 2 × 2 contingency table (Zar 1999).

Results

Based on the estimated morphological variables, we were able to discern 2 distinct beach profile groups, each one corresponding to different portions of the total beach, one on the east and the other on the west side (Table 1). The eastern portion has wider and flatter beaches than the western one, and the dune is more conspicuous and steeper at the west. Also, the morphological data showed that this beach had the largest variability in the swash zone within sites along the 6 months study period; hence, it suggested that this region is where sediment transport occurs the most.

Table 1 Descriptive statistics for the profile morphological features at each beach survey site at El Cuyo, Mexico (ELC).^a

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The PCA showed that the first 2 components explained 85.4% of the variability in beach profile. The eigenvalues showed that the first component was strongly correlated with the berm slope (r  =  −0.91, p < 0.05) and the second one with the total width (r  =  −0.58, p < 0.05) (Table 2).

Table 2 Eigenvalues for the first 3 axes resulted from the principal component analysis (PCA) for the 4 beach morphological variables at El Cuyo, Yucatán.

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Twenty years of nesting records along the beach in El Cuyo showed the existence of a well-defined spatial differentiation of nesting beach selection between the 2 species of sea turtles. Hawksbill turtles nest mostly on the eastern section of the beach (67% of mean total nests per year), whereas green turtles nest primarily on the western section of the beach (99% of mean total nests per year), with very few nests in the eastern section where the hawksbill turtles nest the most.

A significant spatial autocorrelation was found for the mean nesting densities of both turtle species along 17 years of records (green turtle: Moran's I  =  0.974, mean, −0.046 ± 0.2083 SD; p  =  0.001; hawksbill turtle: Moran's I  =  0.744, mean, −0.04 ± 0.2077 SD; p  =  0.001), which suggests a strong and evident spatial structure for nesting records (Fig. 2). The correlogram obtained for the hawksbill records showed a well-defined spatial structure that covered the whole range of nesting range for this species; whereas, the correlogram for the green turtle records showed an incomplete cover of its nesting activity, which appeared like a linear process without reaching an inflection point.

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Integrating nesting data and morphological variables, a significant correlation was only found between the number of green turtle nests and the first component (which is strongly correlated with the berm slope in the profiles) (r  =  −0.68, p < 0.05). The hawksbill turtle nesting data did not show any significant correlation with the 2 components. Given this strong correlation of the green turtle nesting activity with the first component, we explored the direct correlation between the green turtle data and the berm slope, which resulted in a significant negative correlation (r  =  −0.67).

As previously mentioned, none of correlations' residuals showed a statistically significant autocorrelation (p > 0.05), thus, it was not necessary to include a complex spatial correlation model for the data analysis; hence, the ordinary Spearman correlation analysis was adequate under the parsimony principle.

The contingency table evaluation between the 2 species showed a significant preference of the green turtles for nesting in the western portion of the El Cuyo beach (Yates corrected χ²  =  116.17, p  =  0.001), the same beach segment where it was found significant correlation between the number of green turtle nests and the berm slope.

Discussion

This study analyses the observed spatial differentiation in nesting range for the 2 sea turtle species nesting on the beach at El Cuyo on the Yucatan Peninsula and demonstrates the influence of beach slope and width on the sea turtle nesting preferences. The beach profiles measured at all the established benchmarks cannot be spatially compared (i.e., to generate an approximate shoreline for the entire beach), because there were no nearby control points that refer to mean sea level or analogous reference height. Nevertheless, given that ecological correlations were found between intrinsic variables for each profile site, we were able to extract some relevant and basic ecological information about the association between beach morphology and the nesting activity of the sea turtles.

The beach at El Cuyo is free from any kind of artificial barrier blocking the natural sediment flux along the shoreline and provoking erosion processes; even more, satellite images show the presence of pronounced sand banks submerged in front of the eastern side of the beach. This sediment accumulation dissipates wave energy and naturally protects the eastern portion of El Cuyo beach, promoting its growth. This partly explains the wider beaches at the east, in contrast with the west side that is more exposed to the physical oceanographic conditions of the north coast of the Yucatán Peninsula.

Given the absence of artificial barriers on the beach, we suggest that the beach dynamics in our study area are in very good condition. Such conservation status is reflected on the low spatial and temporal variation in the morphology of the survey sites, mainly in the backshore and vegetated zones for the entire nesting beach. By linking such beach morphological conditions to sea turtle nesting activities and when considering the spatial autocorrelation found for the nesting densities of both species, it is suggested that they do select their particular nesting sites in El Cuyo (Wood and Bjorndal 2000) and that it is not a process that occurs randomly along the nesting beach.

For the hawksbill nesting data, we were able to analyze the whole spatial variance as it is evident when observing the correlogram for this species. The shape of the correlogram suggests a patch distribution of the nesting records (there is a clustering nesting pattern around a given site on the beach) and a complete cover of the nesting range as it reaches the asymptote (Fortin and Dale 2005).

In contrast, the correlogram for green turtle nesting data did not reach the asymptote, which suggests a spatial gradient pattern distribution for the nesting records, condition provoked by the missing of the total spatial green turtle nesting range in the area (Fortin and Dale 2005). In fact, the nesting beach at El Cuyo is close to another important nesting beach, Las Coloradas, and they share some of the nesting sea turtles every year. For the purposes of this study, we only considered the nesting data from El Cuyo, because it was not possible to obtain the nesting records for Las Coloradas for the same monitoring period; although we suggest that, in future ecological assessments, El Cuyo and Las Coloradas be considered as a whole nesting beach so as to obtain more integral ecological information for the area.

Previous studies that concerned similar ecological issues showed that the beach slope and its width are 2 of the most relevant morphological variables in determining the sea turtle nesting-site selection; this is the reason why this study directly evaluated the influence of such beach morphological features on the nesting activity in El Cuyo (Fish et al. 2005; Ficetola 2007). For example, Fish et al. (2005) found that Caribbean hawksbill turtles prefer nesting beaches with steep slopes (Fish et al. 2005), whereas Horrocks and Scott (1991) reported flatter nesting beaches (similar to the present study) for this species in Barbados. Such variation in the preferences of hawksbill turtles suggests plasticity of the hawksbill nesting populations in the Caribbean, making them capable of dealing with a certain range of variation in the slope of the available nesting beaches. Kamel and Mrosovsky (2006) explain that such discrepancies in nesting beach preferences between hawksbill populations may be linked with population genetics and inheritance, which suggests that genetically differentiated hawksbill populations may have different nesting beach conditions preferences. Alternatively, this apparent contradiction could imply that this morphological feature is not the determinant environmental variable that defines the nesting site for hawksbill females in the region.

The aim of this study was to evaluate the influence of specific beach morphological features on the nesting activity when taking into account the already reported information about the theme. However, it is worth mentioning that the 2 portions of the nesting beach (east and west) have vegetation with observable differences in average height. The eastern portion has tall vegetation that casts shadows on the dune zone; in contrast, the western portion has shorter vegetation and, hence, poor shade conditions. Horrocks and Scott (1991) suggested a link between shade conditions and nesting preference of hawksbill turtles. The landscape characteristics of the dune in El Cuyo add to the morphological explanation of nesting preference. Even out of these analyses, it is worth mentioning that, at El Cuyo, hawksbill turtles apparently prefer shaded areas, and green turtles being more oblivious to this shade limiting condition.

The latter mentioned preferant is used here supporting the wider nesting distribution of the hawksbills in El Cuyo in contrast to the greens, which are clearly restricted to the western portion of the beach. To determine the contribution of dune vegetation and other physical variables present in the nesting beach, future studies will have to go deeper in assessing their influence on the sea turtle nesting activity for more determinant site preferences by both species.

The results of this study suggest that green turtles select beaches with slightly steeper slopes, mainly in the berm zone, in comparison with the beaches selected by hawksbill turtles, which seem to have a wider variation range of beach morphological features preferences in the area.

Mortimer (1990) reports a set of important beach features that influence green turtle nest-site selection (e.g., shoreline orientation, beach slope, dune vegetation, and sand texture); however, no information was presented on the variation of these beach features selected for nesting by the species. The highest green turtle nest densities in this study were on beaches free of physical obstacles, including rocks (Mortimer 1990), similar to those conditions present at El Cuyo. Comer-Santos et al. (2006) report that beach features such as sand compaction and absence of artificial lights on the beach are 2 of the more optimal conditions for the green turtle nesting success in a given beach. Similar conditions (e.g., lack of compaction and lack of illumination) are found at El Cuyo's green turtle nesting areas.

The present findings help to identify the criteria used by sea turtles to select a nesting beach and provide basic ecological information about the sea turtle nesting process on El Cuyo beach. Conservation management depends on good data when decision makers evaluate potential actions that may threaten nesting populations and their preferred beach zones. This information also gives the basis for the design of conservation strategies in the area and establishes a baseline for evaluating the future consequences of climate change in this important nesting beach and its effects on the endangered sea turtle nesting populations.