<p>The stock-recruitment relationship (SRR) is a key concept in fish population dynamics. However, it can be easily affected by various uncertainties. In particular, it may exhibit non-stationarity under pressure from global climate change. These factors might negatively impact the effectiveness of fisheries management, especially for data-poor fish stocks. In this research, the whitespotted conger (<i>Conger myriaster</i>), a commercial marine eel with complex life history and recruitment processes, was studied to test the hypothesis. The Beverton-Holt model was employed to simulate its recruitment dynamic and evaluate the impacts of variability and non-stationarity in SRR on the robustness of a selected set of data-limited management procedures (MPs). Specifically, we studied the effects of stochastic variability and autocorrelation of SRR, as well as the uncertain parameter steepness. Among them, the non-stationarity was reflected by simulating a series of time-varying steepness scenarios. The results demonstrate that although most MPs are impaired by the increasing recruitment variability and autocorrelation, they still retain the ability to recover the resource. Currently, while the observation errors of steepness have a minor impact on our performance metrics, sensitivity analyses reveal the risks in actual management associated with the potential uncertainties in steepness. Regarding the time-varying steepness scenarios, most MPs demonstrate satisfied robustness, although their performance in achieving both conservation and harvest objectives has declined. We highlight that accurate identification of uncertainties in conger recruitment is crucial for scientific management. Although some data-limited MPs perform well, it’s necessary to make improvements to them and develop robust management strategies for realizing the sustainable exploitation of conger.</p>