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Karl, 2007). This genetic structure is a necessary premise for inferring the connectivity between sea turtle
aggregations and nesting populations (sources or rookeries) through the application of mixed stock analysis
(MSA) (Pella and Masuda, 2001). For the purposes of conservation, identifying origins in aggregations is
important because the sources, reproductively isolated, are concomitant in the mixed aggregations (Avise, 2007;
Bowen et al., 2007). Therefore, a negative impact on these areas or the migratory routes that connect them with
breeding/nesting areas may affect several sources as well as other foraging grounds (Proietti et al., 2012).
Of all sea turtle species reported for the Wider Caribbean (WC),
Eretmochelys imbricata
is one of the most
suitable biological models to make inferences about regional management and conservation through the MSA.
This species is circumtropical (Baillie and Groombridge, 1996) with little genetic flow between Brazilian and WC
rookeries (Vilaça et al., 2013; Proietti et al., 2014), and limited transoceanic migrations (Marcovaldi and Filippini,
1991; Bellini et al., 2000; Grossman et al., 2007; Monzón-Argüello et al., 2011). On the other hand, the WC has
the largest number of genetically characterized
E. imbricata
aggregations and rookeries (Bowen et al., 2007;
Velez-Zuazo et al., 2008; Richardson et al., 2009; Blumenthal et al., 2009a; Leroux et al., 2012; Gorham et al.,
2014). These sources temporarily exhibit genetic stability (Velez-Zuazo et al., 2008), and significant genetic
structure between them and feeding aggregations (Bowen et al., 2007). In addition, most of these sources have
historical demographic estimates (Richardson et al., 2006; Beggs et al., 2007; Mortimer and Donnelly, 2007).
Finally, the complex life cycle of the hawksbill (Bolten, 2003) along with solitary nesting (Witzell, 1983) and
persistent consumptive use (Moncada et al., 2012), and further, the additional value of its shell (Mortimer and
Donnelly, 2007), make this a Critically Endangered species (IUCN, 2016).
Currently, most MSAs are performed using the ―many to many‖ method, where the rookery size
i.e.
number of
nesting females or nests per year (Nr) is included as a constraint (Bolker et al., 2007) since Nr is an important
determinant of the contributions from each rookery. In
E. imbricata
many studies use the Nr most recently
reported (Blumenthal et al., 2009a; Wood et al., 2013; Gorham et al., 2014), which may be biased considering that
this parameter has had a general increasing trend in WC (Mortimer and Donnelly, 2007). If the aggregation is a
breeding area or composed of adult individuals, it is most appropriate to select the Nr that temporarily coincides
with the aggregation sampling, because these individuals potentially belong to the effective size of these rookeries.
Conversely, if the aggregation is composed of non-adult individuals then the selected Nr should coincide with the
approximate moment at which these individuals hatched. This is because
E. imbricata
juveniles which have
arrived at neritic habitats after their oceanic stage may take up to two or more decades to reach maturity (Boulon,
1994; Miller and Limpus, 2003), and the Nr can vary significantly over this period (Mortimer and Donnelly, 2007),
thereby affecting the contributions.
On the other hand, many authors have used the cumulative frequencies from many years in each rookery to
execute the MSA (Bowen et al., 2007), which increases the N but this assumption can overestimate some
haplotypes. In other cases, the cumulative haplotype frequency in the rookeries may exceed the number of annual
nesting females as in the
E. imbricata
rookery of Tortuguero (Costa Rica), which has 10 nesting females/year but
42 with assigned haplotypes between 2000 and 2003 (Troëng et al., 2005). In addition, the use of maritime
distance between rookeries and aggregations should be treated cautiously when inferring sea turtle
dispersal/migration. There are two maritime distances to consider: the shortest distance between the rookery and
the aggregation, and the distance representing the trajectory taken by the turtle depending on sea currents and
other factors. With the first variant, correlations and regression models have been tested which generally do not
show any significance or have relatively low coefficients (Luke et al., 2004; Bowen et al., 2007; Naro-Maciel et
al., 2007; Prosdocimi et al., 2012). With the second variant, the results have indicated significant correlations
between the contributions of rookeries to juvenile aggregations calculated with the haplotype frequencies and
those calculated by passive dispersion of particles from rookeries to aggregations by means of ocean currents
(Bowen et al., 2004; Blumenthal et al., 2009a; Proietti et al., 2012). However, turtle trajectory to a
feeding/breeding ground does not always follow a logic of phylopatry, residence, or occur in accordance with sea
currents (Cuevas et al., 2008; van Dam et al., 2008).
