Eliminating the dark matter of data deficiency by predicting the conservation status of Northeast Atlantic and Mediterranean Sea sharks and rays

Abstract

Sharks and rays are threatened by overfishing, yet we have little idea of the conservation status of the hundreds of Data Deficient species. Here, we developed an ecological trait model to predict the categorical conservation status of 22 Northeast Atlantic and 13 Mediterranean Sea Data Deficient sharks and rays. We first developed an explanatory cumulative link mixed model based on regionally data-sufficient species on the International Union for Conservation of Nature (IUCN) Red List of Threatened Species™ using maximum body size, median depth, and reproductive mode, then predicted the statuses of Data Deficient species. Species exclusive to the Mediterranean were 3.8 times more likely to be threatened than species exclusive to the Northeast Atlantic. Over half of Northeast Atlantic (55%, n = 12 of 22), and two-thirds of Mediterranean (62%, n = 8 of 13) Data Deficient species were predicted to be threatened. When applied to all data-sufficient species, the mean predictive accuracy was 71% and 66% for the Northeast Atlantic and Mediterranean models, respectively. Overall, Northeast Atlantic Data Deficient species are predicted to be 1.4 times more threatened than data-sufficient species proportionally (39% assessed-threatened, n = 38 of 98), whereas threat levels in the Mediterranean Sea are similarly high for both (65% assessed-threatened, n = 39 of 60 data-sufficient). With the growing availability of vertebrate trait databases, trait-based, categorical prediction of conservation status is a cost-effective approach towards incorporating Data Deficient species into unbiased (i) estimates of lineage-wide extinction rates, (ii) protected species lists, and (iii) Red List Indices, thus preventing poorly-known species from reaching extinction unnoticed.