Data-limited management reference points to avoid collapse of stocks dependent on learned migration behaviour

Risk of stock collapse associated with the loss of a stock's migrational knowledge may be underestimated by conventional reference points. In this paper, I describe three different approaches: a data-poor precautionary approach is to ensure that individuals spawn at least twice; a data-intermediate approach is to calculate a repeat spawning potential ratio (rSPR), which is analogous to the conventional SPR; and for data-rich cases, age-structured population simulations are recommended.