Rapid assessment of management options for promoting stock rebuilding in data‐poor species under climate change

: The development of species recovery plans requires considering likely outcomes of different management interventions, but the complicating effects of climate change are rarely evaluated. Here, we demonstrate how Qualitative Network Models (QNMs) can be deployed to support decision-making when data, time, and funding limitations restrict use of more demanding quantitative methods. We used QNMs to evaluate management interventions intended to promote rebuilding of a collapsed stock of blue king crab Paralithodes platypus (BKC) around the Pribilof Islands (eastern Bering Sea) and show how their potential efficacy may change when considered under climate change. Based on stakeholder input and a literature review, we constructed a QNM that described the life cycle of BKC, key ecological interactions, and potential climate change impacts. In addition, we applied a simple and computationally efficient simulation procedure that incorporates information on relative interaction strengths using inequality conditions into predictions. Under a scenario of no climate change, predicted increases in BKC were reliable under one intervention scenario: stock enhancement as part of a BKC hatchery program. However, when climate change was accounted for the intervention was not able to counteract its adverse impacts, which had an overall negative effect on BKC. The remaining scenarios related to changes in fishing effort on BKC predators. For those scenarios, BKC outcomes were unreliable but climate change further decreased the probability of observing recovery. We performed sensitivity analyses to identify key sources of prediction uncertainty which can be used to inform research prioritization, guide model refinement, and aid the development of more targeted quantitative models. QNMs are useful options when data are limited, but they remain underutilized in the conservation arena. This article is protected by copyright. All rights reserved.