Principal Investigator: Peter Dutton (SWFSC)
Co-Principal Investigators: Michael Jensen (SWFSC)


Project title

Improving stock boundary delineation and demographic parameters for green turtles

Background

Use of mitochondrial DNA (mtDNA) provided the basis for the distinct population segment (DPS) designation of green turtles in the Pacific. The next stage in the process is to identify Critical Habitat and perform risk assessment for each DPS, which will require an assessment of in-water distribution of all stage classes in order to draw meaningful boundaries around them. While mtDNA has been useful in the past, it does have limitations that make it not ideal for the identification of finer scale geographical, temporal, and demographic aspects of green turtle populations. However, nuclear DNA (nDNA) can be used to estimate the nesting origin of individual turtles. The capacity to generate large rookery baseline datasets with multiple new markers will now allow fine scale stock structure analysis, and enable individual assignment of turtles to nesting beaches. This will provide a basis to integrating multiple lines of data (often for a specific individual turtle) such as satellite telemetry, stable isotopes, toxicology, and hormone sex determination to provide important demographic parameters needed for risk assessment of Pacific green turtle populations.  

Research Objectives

The overall goal of this research is to improve analysis of nuclear population genetic structure of Pacific green turtles and to trace back the nesting origin of turtles sampled at foraging grounds or in fisheries by-catch using individual assignment testing. There are three main objectives:

  1. Improve understanding of the stock structure of Pacific green turtles using new nuclear (microsatellite, SNP) and previously analyzed mtDNA markers to provide a comprehensive assessment of demographic history, colonization/migration patterns, male and female gene flow and effective population size.
  2. Improve Stock ID of turtles from foraging grounds and fisheries by-catch by using individual assignment testing to define connectivity by linking individual turtles to their nesting origin.
  3. Use individual assignment testing to assess differences in connectivity between age-classes (e.g. juveniles and adults), between turtles sampled in different years and between males and females.

These objectives all relate to priorities listed in all the Marine Turtle Recovery Plans (Recovery Goal 1.1.5.3 Pacific Sea Turtle Recovery Plans, and are identified as highest priority in the Marine Turtle and Marine Mammal SAIP (NMFS 2004). The objectives also link directly to Theme A: (Stock Identification) in particular information that will help the “Development of sex-specific models to evaluate male vs. female connectivity” of the NMFS Sea Turtle Assessment Research Themes.

Project significance, impacts, and applications

The use of nuclear genetic data for population structure and individual assignments of turtles at foraging areas are essential components of improved stock assessments for sea turtle population segments as outlined in the NMFS Stock Assessment Improvement Plan (SAIP; (NMFS 2004; NMFS 2013). The findings from this study will provide a better understanding of complex population dynamics that may be used for population viability studies. In particular, understanding how connectivity change through time and how the connectivity of males and females differ are vital for risk assessment of sea turtle populations likely to be affected by a changing climate. Being able to infer stock-ID of individual turtles will play a critical role in identifying threats to specific sea turtle rookeries, such as determining the effects of by-catch on specific sea turtle rookeries. The application of individual assignments will be the first of its kind for green turtles and will pave the way for future comprehensive analyses in other ocean basins (e.g the Atlantic and Caribbean). As recommended by NMFS SAIP (2004), this project will improve stock structure, fill demographic data gaps and investigation of anthropogenic impacts for endangered green sea turtle populations, thus helping transition their SAIP assessment statuses to the Tier 2 level.