ABSTRACTThe time lag between data collection and management implementation is a source of uncertainty and bias in the calculation of acceptable biological catch. Here, we developed a method to use small-scale survey data for juvenile Japanese pufferfish (Takifugu rubripes) to shorten this time lag and achieve accurate short-term forecasting. A survey of juvenile fish at a local sandy beach in Ise-Mikawa Bay, Japan provides data for the strength of year classes before fisheries recruitment; however, it is difficult to use the raw data owing to the small sample size and large observation errors. We found that a random-effect model overcame these problems and more accurately predicted pulse patterns of catch rates to derive a standardized recruitment index compared with a fixed-effect model. We then showed that a stock assessment model using the standardized recruitment index from the random-effect model outperformed models without the standardized recruitment index with respect to retrospective forecasting ability. This study highlights the applicability of a latent-variable approach for standardizing small-scale survey data and thereby for unbiased forecasting of short-term fish dynamics.