Fishing-effort distributions are subject to change, for autonomous reasons and in response to management regulations. Ignoring such changes in a stock-assessment procedure may lead to a biased perception. We simulated a stock distributed over two regions with inter-regional migration and different trends in exploitation and tested the performance of extended survivors analysis (XSA) and a statistical catch-at-age model in terms of bias, when spatially restricted tuning series were applied. If we used a single tuning index that covered only the more heavily fished region, estimates of fishing mortality and spawning-stock biomass were seriously biased. If two tuning series each exclusively covering one region were used (without overlap but together covering the whole area), estimates were also biased. Surprisingly, a moderate degree of overlap of spatial coverage of the two tuning indices was sufficient to reduce bias of the XSA assessment substantially. However, performance was best when one tuning series covered the entire stock area.