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Conserving biodiversity and combating ecological hazards require cost‐effective allocation of limited resources among potential management projects. Project priorities, however, can change over time as underlying social‐ecological systems progress, novel priorities emerge, and management capabilities evolve. Thus, reallocation of ongoing investments in response to shifting priorities could improve management outcomes and address urgent demands, especially when additional funding is not available immediately. Resource reallocation, however, could incur transaction costs, require additional monitoring and reassessment, and be constrained by ongoing project commitments. Such complexities may prevent managers from considering potentially beneficial reallocation strategies, reducing long‐term effectiveness. We propose an iterative project prioritization approach, based on marginal return‐on‐investment estimation and portfolio optimization, that guides resource reallocation among ongoing and new projects. Using simulation experiments in 2 case studies, we explored how this approach can improve efficacy under varying reallocation constraints, frequencies, costs, and rates of project portfolio change. Periodic budget reallocation could enhance the management of stochastically emerging invasive weeds in Australia and thus reduce the overall risk by up to 50% compared with a static budget. Reallocation frequency and the rate of new weed incursion synergistically increased the conservation gains achieved by allowing unconstrained reallocation. Conversely, budget reallocation would not improve the International Union for Conservation of Nature conservation status of threatened Australian birds due to slow rates of transition among conservation states; extinction risk could increase if portfolio reassessment is costly. Although other project prioritization studies may recommend periodic reassessment and reallocation, our findings revealed conditions when reallocation is valuable and demonstrated a structured approach that can help conservation agencies schedule and implement iterative budget‐allocation decisions cost‐effectively. Article impact statement: Reallocating funding among conservation projects in response to shifting or emerging priorities may improve outcomes. [ABSTRACT FROM AUTHOR]

Allocating money for species conservation on the basis of threatened species listings is not the most cost-effective way of promoting recovery or minimizing extinction rates. Using ecological and social factors in addition to threat categories, we designed a decision-support process to assist policy makers in their allocation of resources for the management of native wildlife and to clarify the considerations leading to a priority listing. Each species is scored on three criteria at the scale of the relevant jurisdiction: (1) threat category, (2) consequences of extinction, and (3) potential for successful recovery. This approach provides opportunity for independent input by policy makers and other stakeholders (who weight the relative importance of the criteria) and scientists (who score the species against the criteria). Thus the process explicitly separates societal values from the technical aspects of the decision-making process while acknowledging the legitimacy of both inputs. We applied our technique to two Australian case studies at different spatial scales: the frogs of Queensland (1,728,000 km2; 116 species) and the mammals of the Wet Tropics bioregion (18,500 km2; 96 species). We identified 7 frog and 10 mammal species as priorities for conservation. The frogs included 1 of the 9 species classified as endangered under Queensland legislation, 3 of the 10 species classified as vulnerable, 2 of the 22 species classified as rare, and 1 of the 75 species classified as least concern. The mammals identified included 3 of the 6 species classified as endangered, 1 of the 4 species classified as vulnerable, 5 of the 11 species classified as rare, and 1 of the 75 species classified as least concern. The methods we used to identify species were robust to comparisons across the two taxonomic groups. We concluded that (1) our process facilitates comparisons of data required to make transparent, cost-effective, and strategic management decisions across taxonomic groups and (2) the process should be used to short-list species for further discussion rather than for allocating resources per se. [ABSTRACT FROM AUTHOR]