- To assess the population of Red Snapper on artificial reefs, natural bottom, and other structures to provide a Gulf-wide estimate of absolute abundance of fish Age-2 and older by age-groups in the U.S. Gulf of Mexico.
- To estimate habitat-specific biological parameters such as growth and natural mortality rates by specific age-groups.
- To engage the Gulf of Mexico scientific community and other GOM stakeholders.
- To ensure design will result in estimates that will be used for comparison and integration into NOAA’s Red Snapper stock assessment.
Additional PI: Marcus Drymon, University of South Alabama
We have assembled a team of some of the most qualified Red Snapper researchers in the GOM along with expert statisticians in the field of sampling and animal population estimation. This group of experts will lead a series of experimental design workshops with the overarching goal of proving robust experimental design(s) for carrying out an intensive research initiative that will solve one of most pressing issues currently facing GOM Red Snapper fishery management - estimating absolute abundance. Overall, we propose to develop a multi-faceted approach that combines Gulf-wide tagging approaches including mark-recapture studies, modified stratified sampling designs, and state-of-the art advanced technologies (ROV, sonar, camera arrays) that will count Red Snapper on both artificial reefs and natural bottom (both structured and unstructured) across their range in the northern GOM. In developing the design, we propose to use several complementary methods including remotely-operated vehicle surveys with novel but powerful emerging technologies for calculating density along fixed transects, vertical-line fishing surveys (CPUE and depletion studies), side-scan and multi-beam sonar, acoustic telemetry, and other methods to determine Red Snapper abundance on multiple habitat types. Additionally, by collecting these specimens and data in this manner, it will also allow for estimates of age-specific growth and mortality among these areas. Together this group will form a leadership team to assemble and engage scientific experts from across the Gulf in key areas of sampling expertise to meet the goals of the proposal as well as engage the other Gulf constituent partners. During a series of workshops that will be paired with pre- and post-workshop webinars we will develop (1) a robust Gulf-wide sampling design, (2) a detailed plan for statistical treatment of data collected, and (3) a scalable (intensity) product including a detailed budgeting tool, where sampling can be adjusted based on final funding parameters that will not compromise regional representation.
Our team is very experienced in research with a variety of sampling gears and methodologies for assessing reef fish (including Red Snapper) population dynamics but also experimental design. We will be conducting a series of webinars and workshops throughout the Gulf States to conceptualize the most valid, robust, and reliable design to assess the population of red snapper on artificial reefs and other structures as the basis for a Gulf-wide estimate (with estimates also produced for natural habitats) of absolute abundance. We anticipate hosting a webinar prior to meeting in person for a 2-3 day workshop on the key design topics in the proposal: (1) tagging approaches, (2) random stratified sampling, and (3) advanced technologies. For each workshop topic our team will also invite leading regional and national experts to help ensure that the final design will be usable by NOAA Fisheries to incorporate into larger advanced technology and mark-recapture requests for proposals planned for Fiscal Year 2017. During these series of workshops a variety of design methodologies will be vetted, such as those described above, that have the most potential for success will be included in a final design product as the main deliverable for this funding.
This proposal addresses one of the most pressing issues currently facing Gulf of Mexico (GOM) fisheries management – estimating absolute abundance of Red Snapper. Clearly, much of the controversy surrounding the management and assessment of Red Snapper could be allayed by building confidence and improving our understanding of the population dynamics for this species with improved estimates of their abundance and age-specific growth and mortality across their range and distribution. Thus, the primary rationale for the proposed design is that the implementation of a well-planned study will generate a robust understanding of Red Snapper population dynamics across the U.S. GOM allowing managers to make the most informed decisions relating to this controversially managed species.
We have assembled a multidisciplinary team with extensive leveraging capabilities with ongoing research to address this problem. We will use a combination of approaches that takes advantage of existing resources throughout the GOM in developing a comprehensive design. The design we propose to develop here has been formulated based on long-standing and rigorous Red Snapper research in various related arenas. The principal investigators collaborating on the proposed work (and with others throughout the GOM) are leading fisheries scientists in their respective regions with extensive ongoing research programs and experience using traditional but also advanced technological approaches to quantify fisheries stocks and characterize key life history attributes of reef fishes inhabiting natural, artificial reefs, and other areas with a specialty of sampling Red Snapper using these habitat types.
The combined expertise in these areas makes this research team well-suited to lead a design by bringing together teams of experts from a wide geographic scope across the GOM that is scalable, applicable to the objectives of this proposal, and can build upon the wealth existing resources and substantially leverage these funds. Additionally, the expertise of Dr. Lynne Stokes, particularly in statistical theory and methodology behind capture/recapture modeling and familiarity with Red Snapper data collection and management, will ensure that appropriate statistical models are integrated into a rigorous experimental design.