IUCN Red List Assessment
Red List Category
Red List Criteria
Assessment Procedure: In accord with the IUCN criterion that Red List Assessments focus on the number of mature individuals (IUCN 2001a), this assessment measures changes in the annual number of nesting females. Because reliable data are not available for all subpopulations, the present report focuses on 32 Index Sites (Figure 1, Table 1; see link to additional information below). These Index Sites include all of the known major nesting areas as well as many of the lesser nesting areas for which quantitative data are available. Despite considerable overlap at some foraging areas, each is presumed to be genetically distinct (Bowen et al. 1992, Bowen 1995) except for the Turtle Islands of Malaysia (Sabah) and Philippines (Moritz et al. 1991). These two Index Sites are, however, treated independently because of the different management practices exercised by the two governments and the resultant differences in subpopulation trends. Selection of the 32 Index Sites was based on two primary assumptions: (1) they represent the overall regional subpopulation trends and (2) the number of individuals among Index Sites in each region is proportional to the actual population size in that region. Any regional inconsistencies in this proportion may result in a biased global population estimate.
It should be noted that a major caveat of using the number of nesting females to assess population trends is that this data type provides information for the proportion of the adult females that nest in any given year, not the total adult female population. However, when monitored over many years, this index can be reliable for assessing long-term population trends (Meylan 1982, Limpus 1996). In the case of green turtles, which display high inter-annual variability in magnitude of nesting (Limpus and Nichols 1987, Broderick et al. 2001a), using short-term or single-season data sets could misrepresent the actual mean number of nesters over a longer timeframe. To alleviate this potential source of error, we used multiple-year data sets whenever available. However, when single-season datasets represented the only quantitative information for a given time period, these data were used as long as they were in accord with qualitative information from other references.
Because data on annual number of nesting females are not always available, we also used data on number of nests per season, annual hatchling production, annual egg production and annual egg harvest. When these proxies were used, we converted units to number of nesting females based on a constant figure of 100 eggs/nest and three nests/season/female, unless otherwise noted. These conversions were based on the assumptions that (1) the mean number of eggs/nest and nests/female/season differ insignificantly through time, and (2) efforts to monitor nesting female activity and egg production are consistent through time. When using egg harvest data, we also assumed that harvest effort was consistent during all years for which data are available and 100% of the eggs were harvested in any given year. We believe these assumptions are accurate, but their absolute validation is very difficult. Qualitative information does, however, suggest that they are reasonable assumptions. For example, in the case of historic egg harvest, the same group of people usually harvested the eggs at a particular nesting beach each year, and they typically took every egg they could find (e.g., Parsons 1962, Pelzer 1972).
In the present assessment, population abundance estimates are based on raw data, linear extrapolation functions, and exponential extrapolation functions. In most subpopulations, more than one trajectory was exhibited over the 3–generation interval; changes in subpopulation size are thus often based on a combination of raw data and extrapolations. If no change is believed to have occurred outside the time interval for which published abundance data are available, the raw data were used to determine the change in population size. However, when it is believed that change in subpopulation abundance occurred outside the interval for which raw data were available, extrapolations we performed to determine the overall change. Linear extrapolations were used when it was believed that the same amount of change occurred each year, irrespective of total subpopulation size. Exponential extrapolations were used when it was believed that change was proportional to the subpopulation size. In cases where there is a lack of information on the specific rate of change, both linear and exponential extrapolations were used to derive population estimates. However, if extrapolations resulted in obviously false estimates, their results were discarded (see Table 5; see link to additional information below).
Generation Length. Generation length is based on the age to maturity plus one half the reproductive longevity (Pianka 1974). Although there appears to be considerable variation in generation length among sea turtle species, it is apparent that all are relatively slow maturing and long-lived (Chaloupka and Musick 1997). Green turtles exhibit particularly slow growth rates, and age to maturity for the species appears to be the longest of any sea turtle (Hirth 1997). As a result, this assessment uses the most appropriate age-at-maturity estimates for each index site. At Index Sites for which there are local age-to-maturity data, those data are used to establish generation length. When data are lacking, as they are for a majority of subpopulations, information from the closest subpopulation for which data are available are used to generate age-at-maturity estimates (Table 2; see link to additional information below).
Estimates of reproductive longevity range from 17 y to 23 y (Carr et al. 1978, Fitzsimmons et al. 1995). Data from the apparently pristine Green Turtle stock at Heron Island in Australia’s southern Great Barrier Reef show a mean reproductive life of 19 y (Chaloupka et al. 2004). Because Heron Island is the only undisturbed stock for which reproductive longevity data are available (M. Chaloupka, pers. comm.), this datum is used for all Index Sites (Table 3; follow link to additional information below). Thus, based on the range of ages-at-sexual-maturity (26 yrs to 40 yrs) and reproductive longevity from the undisturbed Australian stock (19 yr), the generation lengths used for this assessment range from 35.5 yrs to 49.5 yrs (Table 3; see link to additional information below).
Uncertainties in assessment process: As with any assessment based on historic data or small datasets, there is a great deal of uncertainty relating to the final results of this report. The sources of uncertainty are rooted in both the procedure itself as well as in the stochastic nature green of turtle biology. Both sources of uncertainty are ultimately related to a lack of information, which can be a common issue when dealing with an animal as long-lived as a Green Turtle.
First and foremost is the uncertainty related to the assumptions invoked for this assessment. For example, if, contrary to our assumption, efforts to monitor nesting female activity and egg production were not consistent through time, then our results may be biased. Similarly, our estimates may be inaccurate if harvest effort or the relative amount of eggs harvested was not consistent through time. In addition, the use of extrapolations may have resulted in erroneous estimates of population change. The potential for this increased when extrapolations were made over long time intervals, when they were based on short-term data sets, or if the start and/or end points of extrapolations were erroneous.
Uncertainty may also be tied to Green Turtle biology. In particular, the substantial variability in the proportion of a population that nests in any given year may result in inaccurate comparisons between past and present data sets. For example, if the proportion of a subpopulation’s adult female cohort nesting each year oscillates over decadal or longer time frames, then it is conceivable that our estimates of annual change in nesting numbers do not correspond to actual changes in the entire subpopulation. Moreover, if our conversion values for eggs/nest and nests/female/season are not accurate for the specific subpopulation being addressed, inaccuracies may result. Lastly, with respect to the migratory behaviour of green turtles, it is expected that each of the Index Sites included in this assessment represent a distinct subpopulation. Indeed, current genetic data support this claim, however, in the absence of complete data for all rookeries, it is possible that turtles moving back and forth between nesting areas in close proximity could have gone undetected. It is thus conceivable that a female could be counted twice. This would, of course, only be a problem when subpopulation size is based on an actual count of individual turtles visiting the beach. Although unlikely, it amounts to an additional source of uncertainty in this assessment.
Population trends. Based on the actual and extrapolated changes in subpopulation size at the 32 Index Sites, it is apparent that the mean annual number of nesting females has declined by 48% to 67% over the last three generations (Table 5; see link to additional information below). In addition, it is apparent that the degree of population change is not consistent among all Index Sites or among all regions (Tables 5 and 6; see link to additional information below). Because many of the threats that have led to these declines are not reversible and have not yet ceased, it is evident that green turtles face a measurable risk of extinction. Based on this assessment, it is apparent that green turtles qualify for Endangered status under Criteria A2bd.
The key supporting documentation is presented in the tables (see link to additional information below), and the full assessment is also available from the Marine Turtle Specialist Group web site.
- 1994Endangered(Groombridge 1994)
- 1990Endangered(IUCN 1990)
- 1988Endangered(IUCN Conservation Monitoring Centre 1988)
- 1986Endangered(IUCN Conservation Monitoring Centre 1986)
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