Defining the appropriate ‘Unit-To-Conserve’ under the International Whaling Commission’s Revised Management Procedure

Abstract

Identifying the appropriate ‘Unit to Conserve’ (UTC) is critical to the success of any management scheme. While the need to define the UTC appropriate to the IWC’s Catch Limit Algorithm (CLA) has long been recognised by its Scientific Committee, little progress has been made on this issue. The CLA was rigorously tested prior to its adoption. However, most of those original performance trials focused on single-population scenarios or two-population scenarios with no ongoing dispersal. None of the trials considered the performance of the CLA across a range of dispersal rates. In this study, the performance of the CLA under a variety of population structure scenarios is examined. This is the first study to investigate the levels of connectivity (i.e. dispersal rate) for which populations require separate management to meet the conservation goals of the CLA. All the trials consisted of two populations that were managed as a single stock for 100 years. Both historical and modern hunts were spatially-biased so that population 1 was the primary target of hunting. Parameters that varied among trials were the relative carrying capacities (K) of the populations, the dispersal rate between them, maximum sustainable yield rate (MSYR1+), and the precision in simulated abundance estimates. All of these parameters had strong effects on the conservation performance of the CLA. Trials with a low MSYR1+ (1%) generally ended with the abundance of population 1 below 0.54K, regardless of the dispersal rate or relative carrying capacities of the two populations. The same was true of trials in which the carrying capacity of population 1 represented only 10% of the total landscape carrying capacity and the CV of the abundance estimates was low, even when dispersal between populations was high (5 × 10–3yr–1) and MSYR1+ was 4%. The results suggest that the appropriate UTCs under the RMP are likely to exchange dispersers at high enough rates that they will be difficult to delineate using existing methods. These results also highlight the value of spatially-diffuse hunting patterns that avoid potential overhunting of unrecognised stocks.