SPATIAL DISTRIBUTION AND MIGRATORY CONNECTIVITY OF SHARKS IN THE GULF OF MEXICO

Abstract

Since the 1950s, highly migratory shark species worldwide have experienced severe declines, with some populations in the Gulf of Mexico showing decreases of more than 90%. As a result, there is a clear need for better data and tools to inform the spatial and temporal management of shark populations. In recent years, the use of satellite and acoustic tracking has increased, but there has been limited critical assessment of the current state of knowledge resulting from these studies. In partnership with The Nature Conservancy’s Migratory Blueways Project, this study aims to fill this gap through 1) a comprehensive, systematic literature review of available telemetry data and 2) a comparative analysis of multiple methods for processing satellite telemetry data. The literature review analyzed telemetry tagging papers for 10 species of highly migratory sharks in the Gulf of Mexico: Whale sharks, silky sharks, great white sharks, great hammerheads, scalloped hammerheads, tiger sharks, bull sharks, oceanic whitetips, shortfin makos, and longfin makos. These species were chosen based on their highly migratory behavior and the level of threat to their populations. The review used the very broad search terms “shark” and “Gulf of Mexico” which returned over 1000 results. After filtering the results for relevancy, only 15 telemetry tagging studies for these species were identified. Two of the most threatened species, oceanic whitetips and silky sharks, had no coverage in the literature. The date range for the papers was 2008-2019, with an increasing trend in number of publications over time. Many species were missing tagging data from regions of the Gulf of Mexico, with no tagging occurring in the southwestern Gulf. Scalloped hammerheads showed a heavily male skewed sex ratio in the individuals tagged, indicating missing information about female behavior. Recommendations from this review include better collaboration between institutions to help reduce costs of collecting data and to increase the amount of data available. The second part of this research compared methods for processing satellite telemetry data used by The Nature Conservancy (TNC) and the Migratory Connectivity in the Ocean (MiCO) projects on the same dataset of 12 hammerhead sharks. TNC utilized a line density method, while MiCO utilized state-space modeling to generate kernel density estimates (KDE). TNC’s work was conducted using Python coding language, while MiCO uses R packages. The results showed that the overall products are similar, with the TNC product covering 22% more area of the Gulf, likely due to MiCO’s more rigorous filtering methods. TNC’s methods were faster but are less supported by scientific literature, so MiCO’s methods are likely preferred for making management decisions. Overall, choosing a method depends on the expertise and intentions of the user group. Introducing more data from other spatial regions of the Gulf would contribute to developing better products for use in conservation and policy.