marine-mammal populations to determine a maximum removal rate that a population can absorb without a large increase in the probability of decline (Barlow et al., 1995; Wade, 1998). PBR is based on the precautionary approach in a very explicit way. A simple algebraic formula is based on the concept of optimum sustainable yield (Taylor et al., 2000), which is a function of population productivity. PBR determines a maximum human-caused removal of individuals from a population on the basis of half its potential net productivity rate, adjusted by a recovery factor (F) that varies from 0.1 to 1 depending on the status of protection. The equation requires a minimum population estimate (Nmin), the maximum rate of increase predicted (or measured) for a population (Rmax), and predetermined risk criteria (low risk to minimal risk) for the recovery factor. PBR is generally applied to an entire population or stock but could be set for specific life stages; the PBR value represents cumulative removals due to all anthropogenic sources. PBR and various modifications to accommodate sea-turtle life history have been explored (Bolten et al., 1996; Turtle Expert Working Group, 2000) but not yet used to set bycatch limits or evaluate human-caused mortality.

Each of those modeling approaches has merit in potential application to sea-turtle demographic analysis and assessment. However, no model can be useful without data for both setting values of parameters and evaluating model behavior, particularly for applications that require precision. Increasing model complexity provides biological realism and the ability to estimate population status precisely, but data need to increase also (see Table 6.1). The most biologically realistic and complex models for sea turtles have been developed for populations with long time series of in-water abundance, breeding frequency, survival-rate estimates, and nesting abundance (e.g., Chaloupka, 2003a, b). All of the published sea-turtle assessment reports (e.g., the Turtle Expert Working Group reports and National Marine Fisheries Service [NMFS] technical memoranda summarized in Table 1.2) have highlighted the paucity of basic data for population modeling, as have reviews of sea-turtle modeling efforts in the United States (e.g., Heppell et al., 2003). The most recent sea-turtle status assessments (National Marine Fisheries Service and U.S. Fish and Wildlife Service, 2007a, b, c, d, e, f) also comment on the need for basic information on population structure and vital rates to identify changes in populations and their listing designations properly.


In addition to identification of appropriate assessment tools, it is important to have standard procedures for evaluation that ensure rig-

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