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Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020.

While the imminent extinction of many species is predicted, prevention is expensive, and decision-makers often have to prioritise funding. In democracies, it can be argued that conservation using public funds should be influenced by the values placed on threatened species by the public, and that community views should also affect the conservation management approaches adopted. We conducted on online survey with 2400 respondents from the general Australian public to determine 1) the relative values placed on a diverse set of 12 threatened Australian animal species and 2) whether those values changed with the approach proposed to conserve them. The survey included a contingent valuation and a choice experiment. Three notable findings emerged: 1) respondents were willing to pay $60/year on average for a species (95% confidence interval: $23 to $105) to avoid extinction in the next 20 years based on the contingent valuation, and $29 to $100 based on the choice experiment, 2) respondents were willing to pay to reduce the impact of feral animals on almost all presented threatened species, 3) for few species and respondents, WTP was lower when genetic modification to reduce inbreeding in the remaining population was proposed.

Climate change is forcing cities to reassess their water management practices, particularly for water-intensive applications like park irrigation. If water scarcity requires governments to deviate from current park management norms and allocate less water towards parks, it is essential that park managers design spaces that maintain community wellbeing. We apply the hedonic pricing method and use detailed park management information to assess the value of parks in a region where local climatic conditions require extensive irrigation to keep turf green, and where climate change is further constraining water supplies. Here we show that the impacts of irrigation on the value of parks differ depending on the dwelling types of the nearby housing populations that they serve. In most cases, the convention that parks have to be irrigated to deliver ecosystem services to the public is supported. However, we find that non-irrigated park areas are also valued positively by nearby apartment dwellers. Accelerating rates of urbanization and shifts towards high-density living may support the development of more diverse park options that are less water-intensive. Increased visibility of these alternative park forms, which could include more areas of native vegetation that do not require irrigation, may subsequently influence public expectations for landscape design.

Marine fish stocks are in many cases extracted above sustainable levels, but they may be protected through restricted-use zoning systems. The effectiveness of these systems typically depends on support from coastal fishing communities. High management costs including those of enforcement may, however, deter fishers from supporting marine management. We incorporated enforcement costs into a spatial optimization model that identified how conservation targets can be met while maximizing fishers' revenue. Our model identified the optimal allocation of the study area among different zones: no-take, territorial user rights for fisheries (TURFs), or open access. The analysis demonstrated that enforcing no-take and TURF zones incurs a cost, but results in higher species abundance by preventing poaching and overfishing. We analyzed how different enforcement scenarios affected fishers' revenue. Fisher revenue was approximately 50% higher when territorial user rights were enforced than when they were not. The model preferentially allocated area to the enforced-TURF zone over other zones, demonstrating that the financial benefits of enforcement (derived from higher species abundance) exceeded the costs. These findings were robust to increases in enforcement costs but sensitive to changes in species' market price. We also found that revenue under the existing zoning regime in the study area was 13-30% lower than under an optimal solution. Our results highlight the importance of accounting for both the benefits and costs of enforcement in marine conservation, particularly when incurred by fishers.