NSFDEB-NERC: Collaborative Research: Informing population models with evolutionary theory to infer species' conservation status

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Marine species are very hard to census. This is especially true of large, high value fishes that are vulnerable to overfishing because of their biology. For example, one third of shark and ray species are known to have declined in recent history, but it is unknown whether most of the remaining two-thirds are also declining, or if they are stable. Likewise, population sizes of predatory fishes such as groupers and tuna have decreased substantially due to intense fishing, yet little is known about the extent of decline and risk of extinction for some of these species. This project uses the evolutionary history of well-studied related species to provide estimates of basic demographic properties of little-studied species of fisheries and conservation importance. This knowledge provides important information to guide management efforts, such as limits on catch and trade, until more direct research can be carried out. The researchers will also engage in educational outreach on mathematical biology for undergraduates and on marine biodiversity science for the general public. Scientists often have some knowledge of individual traits such as reproductive behavior, lifespan, and metabolic rates of many related fish species, even in the absence of population-level information. Evolutionary theory can predict the co-evolution of these unique trait combinations of various groups. This theory can be used to infer demographic rates and project species' status, but previous efforts have not incorporated the unique details of each species' biology. This project will develop comprehensive theory linking the evolution of these traits to species status projections for tunas, groupers, and sharks and rays. Modern statistical methods will allow information from models of data-rich species, which have formal assessments, to be shared with poorly studied species in similar habitats, or with relatives. With this new understanding of population trajectories, the team will produce recommendations for use by organizations like the International Union for Conservation of Nature, as well as managers and scientists.