Abstract:
The olive ridley sea turtle (Lepidochelys olivacea, Eschcholtz 1829) is a pantropical
species that nests through most of its distribution range. Although it is a widely
distributed species this turtle reaches its highest abundance in the Indian Ocean
and along the coastal areas of the Eastern Tropical Pacific (ETP) Ocean (Cornelius,
1986). This species is thought to be the most abundant sea turtle species in the
world (Marcovaldi, 2001). This belief is primarily supported by the fact that, aside
from nesting solitarily, this turtle can nest en masse giving rise to a phenomenon
known as arribada (Valverde et al., 1998). This mass nesting phenomenon is
characterized by the participation of tens or hundreds of thousands of females that
nest synchronously on a relatively small section of beach over a few nights (Richard
and Hughes, 1972; Hughes and Richard, 1974). Today this mass nesting
phenomenon still occurs in large numbers in Gahirmatha and Rushikulya beaches
in India (Pandav et al., 1994; Shanker et al., 2004), in La Escobilla in Mexico
(Márquez-M. et al., 1996), and at Ostional beach in Costa Rica (Russell et al., 2000).
In addition, minor arribada rookeries are known to occur in Nicaragua and
Panama. Unfortunately, the gregariousness of olive ridleys has contributed to the
decimation of at least three arribada assemblages in Mexico due to overexploitation
(Cliffton et al., 1982), and perhaps also at Nancite Beach in Costa Rica, due to low
hatching rates that may occur under high density conditions (Valverde et al., 1998).
Illegal take of adult ridleys in Mexico and legal use of their eggs in Ostional for
human consumption continue today, but the impact of this take on the adult
population has not been elucidated (Plotkin, 2007). The decimation of arribada
assemblages mentioned above underscores one of the main reasons to designate the
species as endangered or threatened (Groombridge, 1994). It is perhaps due to these
designations and associated protection measures that some arribada assemblages,
such as those at La Escobilla and Ostional Beaches, appear to be exhibiting signs of
good health, although these and others, such as those in India, continue to suffer
from high mortality as a consequence of fisheries bycatch (Shanker et al., 2004).
However, arribada nesting beaches are characterized by the lack of sound historical
records regarding the abundance of the various arribada populations. It is
important to emphasize that the lack of long-term monitoring of the nesting
populations using sound methodology prevents biologists from determining the
actual impact of natural events and anthropogenic activities on the health of
regional populations.
Population status is one of the most difficult aspects of the biology of sea turtles to
ascertain. This is because sea turtles exhibit long life cycles, wide distribution, and
complex life histories, which make it difficult to obtain direct, long-term reliable
data on particular life stages (Meylan, 1995). Thus, the long-term monitoring of the
nesting population remains one of the best, albeit imperfect, proxies to assess the
health of a population (Bjorndal et al., 1999). When monitoring nesting populations
it is generally accepted that a persistent significant decline in nesting may be
indicative of the extinction of a rookery (Márquez-M. et al., 1996). Thus, it is
fundamental to generate accurate nesting population estimates that can be used as
an index of population stability and health. Currently, although few estimates exist,
most methodologies used to generate nesting population estimates are flawed, making these estimates unreliable. In addition, these methodologies tend to be
rookery-specific, preventing direct comparison of nesting numbers among rookeries.
This precludes the use of interannual nesting abundance as a reliable index of the
health of the populations. Given the lack of reliable information on sea turtle
abundance it is imperative that sound and consistent methodology be used at all
major arribada beaches to monitor annual and interannual nesting population
fluctuations.