Strong Trade-off Research Articles

DA LI UČINAK ROBOVSKOG ODNOSA PREMA DOMU DEPRESIRA MEĐUNARODNA TURISTIČKA PUTOVANJA?

This paper examines the relationship between "the house slave effect" and tourist outmigration in most European countries. The outline of this study is set up on the analysis of annual data on homeownership and tenant participants in plan to measure the relationship between housing wealth endowment and outbound traveling, with a panel framework that spans the period from 2007 to 2019. In the present empirical case, this paper examines whether or not there is a significant relationship in the sample of 32 countries by using a panel quantile regression method, a panel SGMM, and a panel OLS regression. Estimation outputs reveal that there is a strong negative trade-off between homeownership and outbound tourism for all quantile levels. This evidence along with the auxiliary SGMM and pooled panel estimation assessment strongly confirm that “the house slave effect” negatively affects outbound tourism. What is more, the results show that tenant rates help to boost the international tourism departures or expenditures per capita. The novelty of this work lies in the fact that it provides the pioneering study of the impact of home ownership on outbound travel in European area. The results suggest that a panel quantile regression method (due to data constraints arising from the skewness of international tourism outbound or per capita expenditure data) should be considered when examining the relationship between "the "house slave effect" and outbound tourism in country panel analyses.

The Green Climate Fund and private sector climate finance in the Global South

ABSTRACT Governments and international organizations are increasingly using public funds to mobilize and leverage private finance for climate projects in the Global South. An important international organization in the effort to mobilize the private sector for financing climate mitigation and adaptation in the Global South is the Green Climate Fund (GCF). The GCF was established under the UNFCCC in 2010 and is the world’s largest dedicated multilateral climate fund. The GCF differs from other intergovernmental institutions through its fund-wide inclusion of the private sector, ranging from project design and financing to project implementation. In this paper, we investigate private sector involvement in the GCF through a qualitative exploratory research approach. We ask two main questions: Do private sector projects deliver on their ambitious goals? What are the tensions, if any, between private sector engagement and other principles of the GCF (most importantly the principles of country ownership, mitigation/adaptation balance, transparency, and civil society participation)? This paper argues that private sector involvement does not provide an easy way out of the financial constraints of public climate financing. We show that the GCF fails to deliver on its ambitious goals in private sector engagement for a number of reasons. First, private sector interest in GCF projects is thus far underwhelming. Second, there are strong tradeoffs between private sector projects and the Global Partnership for Effective Development Co-operation (GPEDC) principles of country ownership, transparency, and civil society participation. Third, private sector involvement is creating a mitigation bias within the GCF portfolio. Fourth, while the private sector portfolio is good at channeling funds to particularly vulnerable countries, it does so mostly through large multi-country projects with weak country ownership. Fifth, there is a danger that private climate financing based on loans and equity might add to the debt burden of developing countries, destabilize financial markets, and further increase dependency on the Global North.

Cross-feeding affects the target of resistance evolution to an antifungal drug.

Pathogenic fungi are a cause of growing concern. Developing an efficient and safe antifungal is challenging because of the similar biological properties of fungal and host cells. Consequently, there is an urgent need to better understand the mechanisms underlying antifungal resistance to prolong the efficacy of current molecules. A major step in this direction would be to be able to predict or even prevent the acquisition of resistance. We leverage the power of experimental evolution to quantify the diversity of paths to resistance to the antifungal 5-fluorocytosine (5-FC), commercially known as flucytosine. We generated hundreds of independent 5-FC resistant mutants derived from two genetic backgrounds from wild isolates of Saccharomyces cerevisiae. Through automated pin-spotting, whole-genome and amplicon sequencing, we identified the most likely causes of resistance for most strains. Approximately a third of all resistant mutants evolved resistance through a pleiotropic drug response, a potentially novel mechanism in response to 5-FC, marked by cross-resistance to fluconazole. These cross-resistant mutants are characterized by a loss of respiration and a strong tradeoff in drug-free media. For the majority of the remaining two thirds, resistance was acquired through loss-of-function mutations in FUR1, which encodes an important enzyme in the metabolism of 5-FC. We describe conditions in which mutations affecting this particular step of the metabolic pathway are favored over known resistance mutations affecting a step upstream, such as the well-known target cytosine deaminase encoded by FCY1. This observation suggests that ecological interactions may dictate the identity of resistance hotspots.

Enhancing multifunctionality in European boreal forests: The potential role of Triad landscape functional zoning

Land-use policies aim at enhancing the sustainable use of natural resources. The Triad approach has been suggested to balance the social, ecological, and economic demands of forested landscapes. The core idea is to enhance multifunctionality at the landscape level by allocating landscape zones with specific management priorities, i.e., production (intensive management), multiple use (extensive management), and conservation (forest reserves). We tested the efficiency of the Triad approach and identified the respective proportion of above-mentioned zones needed to enhance multifunctionality in Finnish forest landscapes. Through a simulation and optimization framework, we explored a range of scenarios of the three zones and evaluated how changing their relative proportion (each ranging from 0 to 100%) impacted landscape multifunctionality, measured by various biodiversity and ecosystem service indicators. The results show that maximizing multifunctionality required around 20% forest area managed intensively, 50% extensively, and 30% allocated to forest reserves. In our case studies, such landscape zoning represented a good compromise between the studied multifunctionality components and maintained 61% of the maximum achievable net present value (i.e., total timber economic value). Allocating specific proportion of the landscape to a management zone had distinctive effects on the optimized economic or multifunctionality values. Net present value was only moderately impacted by shifting from intensive to extensive management, while multifunctionality benefited from less intensive and more diverse management regimes. This is the first study to apply Triad in a European boreal forest landscape, highlighting the usefulness of this approach. Our results show the potential of the Triad approach in promoting forest multifunctionality, as well as a strong trade-off between net present value and multifunctionality. We conclude that simply applying the Triad approach does not implicitly contribute to an overall increase in forest multifunctionality, as careful forest management planning still requires clear landscape objectives.

Optimizing cropping systems to close the gap between economic profitability and environmental health.

Supporting food security while maintaining ecosystem sustainability is one of the most important global challenges for humanity. Optimization of cropping systems is expected to promote the ecosystem services of agroecosystems. Yet, how and why cropping system influences the trade-offs between economic profitability and multiple ecosystem services remain poorly understood. We investigate the influence of six cropping systems on trade-offs between economic profitability and multiple ecosystem services after considering 36 agricultural ecosystem properties using field experiment data from 2020 to 2022. We show that designing cropping system is a critical tool to closing the gap between ecosystem sustainability and commercial profitability. Cropping system with three harvests within 2 yr had higher performance in overall ecosystem multiple services through enhancement of supporting, regulating, and economic performance without compromising provisioning compared with four other systems. These systems diminished the trade-off among multiple services, resulting in a 'win-win' situation for economics and multiple services. By contrast, the monoculture and double cropping systems lead to a strong trade-off between pairwise services including ecosystem health and profitability. Our work illustrates the substantial potential of rotation systems with three harvests within 2 yr in enforcing ecosystem services and closing the trade-offs among multiple agricultural ecosystem services.

Synergistic effects of grain sizes on the corrosion behavior and mechanical properties in a metastable high-entropy alloy

Synergistic effects of grain sizes on corrosion behavior and mechanical properties of metastable high-entropy alloys (HEAs) were studied. The results exhibit that the corrosion resistance of metastable HEA increases first and then decreases with grain size increases. This difference in corrosion behavior is manifested in different degrees of passive film dissolution and pitting corrosion, and ascribed to characteristics of passive film induced by different grain boundary densities. Moreover, increasing the grain size decreases mechanical strength, suggesting a strong trade-off in matching corrosion resistance and mechanical properties. The potential corrosion mechanism and trade-off between corrosion resistance and mechanical properties were discussed.

Fertilization using manure minimizes the trade-offs between biodiversity and forage production in agri-environment scheme grasslands.

A common practice used to restore and maintain biodiversity in grasslands is to stop or decrease the use of fertilizers as they are a major cause of biodiversity loss. This practice is problematic for farmers who need fertilizers to increase forage and meet the nutritional needs of livestock. Evidence is needed that helps identify optimal fertilizer regimes that could benefit biodiversity and livestock production simultaneously over the long-term. Here, we evaluated the impact of different fertilizer regimes on indicators related to both biodiversity (plant, pollinator, leaf miners and parasitoid Shannon-Weiner diversity, bumblebee abundance, nectar productivity and forb species richness), and forage production (ash, crude protein, ruminant metabolizable energy and dry matter). To this end, we used data from a grassland restoration experiment managed under four nutrient inputs schemes for 27 years: farmyard manure (FYM; 72 kg N ha-1 yr-1), artificial nitrogen-phosphorus and potassium (NPK; 25 kg N ha-1 yr-1), FYM + NPK (97 kg N ha-1 yr-1) and no-fertilizer. Results showed strong trade-offs between biodiversity and forage production under all treatments even in applications lower than the critical load in the EU. Overall, farmyard manure was the fertilizer that optimized production and biodiversity while 97 kg N ha-1 yr-1 of fertilizer addition (FYM+NPK) had the most negative impact on biodiversity. Finally, forage from places where no fertilizer has been added for 27 years did not meet the nutritional requirements of cattle, but it did for sheep. Rethinking typical approaches of nutrient addition could lead to land management solutions suitable for biological conservation and agriculture.

Nutrition regulates sex expression in a gender diphasy plant, Lilium concolor var. megalanthum.

The evolution and maintenance of plant polymorphism have always received much attention. Gender diphasy is a rare sexual system. Plant individuals with gender diphasy can adjust the resource allocation of different functional organs according to the changes of environmental conditions to regulate the sex expression of individuals, and the sex expression can be converted between years. However, our understanding of sex expression in plants is still very insufficient. In this study, we explored whether the perennial plant Lilium concolor var. megalanthum has a gender diphasy system and whether environmental resource availability affects its resource allocation and sex expression. By collecting the bulbs of two sexual phenotypes (male and hermaphrodite) in the field and simulating the application of different levels of nutrients under the same habitat conditions, the growth and reproduction indexes and sex expression of plants in two years (2021 and 2022) were measured to evaluate the resource allocation strategy and sex expression pattern of Lilium concolor var. megalanthum. We found that the sex expression of Lilium concolor var. megalanthum was variable in continuous years. Under limited resources, Lilium concolor var. megalanthum increases the biomass resources of the leaves and has a longer flowering period. Resource availability regulates the growth, reproduction and sex expression of Lilium concolor var. megalanthum. Bulb size is the main factor affecting its growth, reproduction and sex expression after accumulating sufficient resources. This study confirms that Lilium concolor var. megalanthum has gender diphasy system. There is a strong trade-off between growth and reproduction under limited resources. Nutrient levels can regulate the reproduction and sex expression process of Lilium concolor var. megalanthum. With the growth of Lilium concolor var. megalanthum in consecutive years, the size dependence of bulbs may be the decisive factor in its sex expression.

Periodic patterns for resolution limit characterization of correlation plenoptic imaging

The measurement of the spatio-temporal correlations of light provides an interesting tool to overcome the traditional limitations of standard imaging, such as the strong trade-off between spatial resolution and depth of field. In particular, using correlation plenoptic imaging, one can detect both the spatial distribution and the direction of light in a scene, pushing both resolution and depth of field to the fundamental limit imposed by wave optics. This allows one to perform refocusing of different axial planes and three-dimensional reconstruction without any spatial scanning. In the present work, we investigate the resolution limit in a particular correlation plenoptic imaging scheme, by considering periodic test patterns, which provide, through analytical results, a deeper insight in the resolution properties of this second-order imaging technique, also in comparison with standard imaging.

Accounting for behaviour in fine-scale habitat selection: A case study highlighting methodological intricacies.

Animal habitat selection-central in both theoretical and applied ecology-may depend on behavioural motivations such as foraging, predator avoidance, and thermoregulation. Step-selection functions (SSFs) enable assessment of fine-scale habitat selection as a function of an animal's movement capacities and spatiotemporal variation in extrinsic conditions. If animal location data can be associated with behaviour, SSFs are an intuitive approach to quantify behaviour-specific habitat selection. Fitting SSFs separately for distinct behavioural states helped to uncover state-specific selection patterns. However, while the definition of the availability domain has been highlighted as the most critical aspect of SSFs, the influence of accounting for behaviour in the use-availability design has not been quantified yet. Using a predator-free population of high-arctic muskoxen Ovibos moschatus as a case study, we aimed to evaluate how (1) defining behaviour-specific availability domains, and/or (2) fitting separate behaviour-specific models impacts (a) model structure, (b) estimated selection coefficients and (c) model predictive performance as opposed to behaviour-unspecific approaches. To do so, we first applied hidden Markov models to infer different behavioural modes (resting, foraging, relocating) from hourly GPS positions (19 individuals, 153-1062 observation days/animal). Using SSFs, we then compared behaviour-specific versus behaviour-unspecific habitat selection in relation to terrain features, vegetation and snow conditions. Our results show that incorporating behaviour into the definition of the availability domain primarily impacts model structure (i.e. variable selection), whereas fitting separate behaviour-specific models mainly influences selection strength. Behaviour-specific availability domains improved predictive performance for foraging and relocating models (i.e. behaviours with medium to large spatial displacement), but decreased performance for resting models. Thus, even for a predator-free population subject to only negligible interspecific competition and human disturbance we found that accounting for behaviour in SSFs impacted model structure, selection coefficients and predictive performance. Our results indicate that for robust inference, both a behaviour-specific availability domain and behaviour-specific model fitting should be explored, especially for populations where strong spatiotemporal selection trade-offs are expected. This is particularly critical if wildlife habitat preferences are estimated to inform management and conservation initiatives.

Mixed strain pathogen populations accelerate the evolution of antibiotic resistance in patients

Antibiotic resistance poses a global health threat, but the within-host drivers of resistance remain poorly understood. Pathogen populations are often assumed to be clonal within hosts, and resistance is thought to emerge due to selection for de novo variants. Here we show that mixed strain populations are common in the opportunistic pathogen P. aeruginosa. Crucially, resistance evolves rapidly in patients colonized by multiple strains through selection for pre-existing resistant strains. In contrast, resistance evolves sporadically in patients colonized by single strains due to selection for novel resistance mutations. However, strong trade-offs between resistance and growth rate occur in mixed strain populations, suggesting that within-host diversity can also drive the loss of resistance in the absence of antibiotic treatment. In summary, we show that the within-host diversity of pathogen populations plays a key role in shaping the emergence of resistance in response to treatment.

Diverging trends and drivers of Arctic flower production in Greenland over space and time

The Arctic is warming at an alarming rate. While changes in plant community composition and phenology have been extensively reported, the effects of climate change on reproduction remain poorly understood. We quantified multidecadal changes in flower density for nine tundra plant species at a low- and a high-Arctic site in Greenland. We found substantial changes in flower density over time, but the temporal trends and drivers of flower density differed both between species and sites. Total flower density increased over time at the low-Arctic site, whereas the high-Arctic site showed no directional change. Within and between sites, the direction and rate of change differed among species, with varying effects of summer temperature, the temperature of the previous autumn and the timing of snowmelt. Finally, all species showed a strong trade-off in flower densities between successive years, suggesting an effective cost of reproduction. Overall, our results reveal region- and taxon-specific variation in the sensitivity and responses of co-occurring species to shared climatic drivers, and a clear cost of reproductive investment among Arctic plants. The ultimate effects of further changes in climate may thus be decoupled between species and across space, with critical knock-on effects on plant species dynamics, food web structure and overall ecosystem functioning.

An integrated multi-objective mathematical model for sugarcane harvesting considering cumulative degree-days

Sugarcane is one of the main commodities in the world economy. An important step in the sugarcane supply chain is the harvest stage, requiring the support of mathematical modeling and optimization tools. Integrating the process of choosing the areas for harvesting according to the sugarcane maturation with the formation of the harvesting fronts and associating them with machine relocation costs is challenging. This paper contributes with a novel integer mathematical model that considers these concerns using three conflicting objectives. The first is that the sugarcane should be harvested as close as possible to its maturity, considering the sugarcane should be harvested as close as possible to its maturity by considering a combined measure of temperature and time since planting. The second aims to minimize the number of harvest fronts. The third objective is to minimize the costs involved with the relocation of the harvesters that cut the cane. Different strategies for obtaining Pareto-optimal solutions were proposed using exact methods, including MIP start and a decomposition technique. In the worst case, solutions with tolerable integrality gaps were obtained (inferior to 3%) in less than 1.5 h. Computational tests in real case studies were conducted in the sugarcane industry in two countries, indicating strong trade-offs in the determined solutions. In the Brazilian case, harvesting as close to maturation as possible, for example, causes an increase of 158% in the number of harvest fronts and 47% in the transportation costs, considering the minimum values for these objectives. Other trade-offs were seen and discussed when one of the other objectives was prioritized. These different compromise solutions help the decision-makers choose the most appropriate harvesting schedule according to their preferences.

Broadband picometer-scale resolution on-chip spectrometer with reconfigurable photonics

Miniaturization of optical spectrometers is important to enable spectroscopic analysis to play a role in in situ, or even in vitro and in vivo characterization systems. However, scaled-down spectrometers generally exhibit a strong trade-off between spectral resolution and operating bandwidth, and are often engineered to identify signature spectral peaks only for specific applications. In this paper, we propose and demonstrate a novel global sampling strategy with distributed filters for generating ultra-broadband pseudo-random spectral responses. The geometry of all-pass ring filters is tailored to ensure small self- and cross-correlation for effective information acquisition across the whole spectrum, which dramatically reduces the requirement on sampling channels. We employ the power of reconfigurable photonics in spectrum shaping by embedding the engineered distributed filters. Using a moderate mesh of MZIs, we create 256 diverse spectral responses on a single chip and demonstrate a resolution of 20 pm for single spectral lines and 30 pm for dual spectral lines over a broad bandwidth of 115 nm, to the best of our knowledge achieving a new record of bandwidth-to-resolution ratio. Rigorous simulations reveal that this design will readily be able to achieve single-picometer-scale resolution. We further show that the reconfigurable photonics provides an extra degree of programmability, enabling user-defined features on resolution, computation complexity, and relative error. The use of SiN integration platform enables the spectrometer to exhibit excellent thermal stability of ±2.0 °C, effectively tackling the challenge of temperature variations at picometer-scale resolutions.

Multi-objective optimization of chemical process plant layout considering economy and inherent safety

Economy and safety are important factors for the layout design of chemical process plants. However, safety factors are often translated into economic indicators as a part of the objective function for layout optimization in previous studies. This may result in safety performance of chemical process plants does not meet the actual production requirements. In this paper, a multi-objective optimization method for chemical process plant layout is proposed to obtain series of solutions that can achieve the trade-off between economy and safety. The economic objective function is characterized by the total capital cost, including land cost, pipe cost, protection device cost and expected property loss from accidents. The safety objective function involves inherent safety which is evaluated by the Comprehensive Inherent Safety Index (CISI). The proposed multi-objective optimization model solved by non-dominated sorting genetic algorithm II (NSGA-II) is applied for layout optimization of an acrylic acid production plant. The results show a strong trade-off between competing economic and safety objectives according to the Pareto curve. The optimal solution ranges from 236,099 $ to 379,622 $ for total cost, corresponding to 87.7–132 for CISI. Safety will be improved significantly in the low-safety layout scheme when the capital investment increases slightly.

In highly-biodiverse tropical landscapes, multiple-objective optimization reveals opportunities for increasing both conservation and agricultural production

In humid tropics, small and medium farming systems are important for producing food but also because they retain rainforest patches with high conservation value. Forest conservation and agricultural production strongly compete for land in Tropical Farming Systems (TFS). Finding solutions that synergize increasing conservation areas and agricultural production is an issue that has yet to be resolved in human-modified tropical landscapes. Achieving this objective requires analyzing how farms could be reorganized to relieve the pressure for production on the land. Pareto-based genetic algorithms that produce a set of solutions that satisfy apparently opposed objectives may tackle multi-objective problems. We explored trade-offs and synergies to increase the profits by sustainable intensification and maintain or increase rainforest areas in five TFS. There was a strong trade-off between conservation and economic profits in all TFS. However, depending on the total farming area, initial configurations and the amount of external inputs used, TFS showed low (two out of five) or high (three out of five) potential to increase forest conservation and profits. In low potential areas, the expansion of conservation areas and profits was only possible by increasing external inputs, primarily due to the limiting farming area and intensification status in those areas. In contrast, in high potential areas it was possible to increase conservation areas and profits through sustainable intensification practices, such as increasing maize silage, changing high for low use-pesticides crops but also reducing variable costs by minimizing cost-supply uses or external feeds. Alternative management and resource allocation options were specific for each TFS. The multi-objective simulation yielded novel results showing that it is possible to overcome the conservation-production antagonism (a regional-global scale issue) by adjusting management at farm (local) scale.

Evaluating potential changes to the US Chukchi Sea bottom trawl survey design via simulation testing

The US Chukchi Sea consists of the waters off the northwest of Alaska and is a naturally dynamic ice-driven ecosystem. The impacts from climate change are affecting the Arctic marine ecosystem as well as the coastal communities that rely on healthy marine ecosystems. In anticipation of increased ecosystem monitoring in the area, there is an opportunity to evaluate improved sampling designs for future ecological monitoring of the Chukchi Sea, an area that is sampled less comprehensively compared to other regions in Alaska. This analysis focused on standardized NOAA-NMFS-AFSC bottom trawl surveys (otter and beam trawls) and three types of survey designs: simple random, stratified random, and systematic. First, spatiotemporal distributions for 18 representative demersal fish and invertebrate taxa were fitted using standardized catch and effort data. We then simulated spatiotemporal taxon densities to replicate the three survey design types to evaluate design-based estimates of abundance and precision across a range of sampling effort. Modest increases in precision were gained from stratifying the design when compared to a simple random design with either similar or lower uncertainty and bias of the precision estimates. There were often strong tradeoffs between the precision and bias of the systematic estimates of abundance (and associated variance) across species and gear type. The stratified random design provided the most consistent, reliable, and precise estimates of abundance indices and is likely to be the most robust to changes in the survey design. This analysis provides a template for changing bottom trawl survey designs in the Chukchi Sea and potentially other survey regions in Alaska going forward and will be important when integrating new survey objectives that are more ecosystem-focused.

Space characterizations of complexity measures and size-space trade-offs in propositional proof systems

We identify two new clusters of proof complexity measures equal up to polynomial and log⁡n factors. The first cluster contains the logarithm of tree-like resolution size, regularized clause and monomial space, and clause space, ordinary and regularized, in regular and tree-like resolution. Consequently, separating clause or monomial space from the logarithm of tree-like resolution size is equivalent to showing strong trade-offs between clause space and length, and equivalent to showing super-critical trade-offs between clause space and depth. The second cluster contains width, Σ2 space (a generalization of clause space to depth 2 Frege systems), ordinary and regularized, and the logarithm of tree-like R(log⁡) size. As an application, we improve a known size-space trade-off for polynomial calculus with resolution. We further show a quadratic lower bound on tree-like resolution size for formulas refutable in clause space 4, and introduce a measure intermediate between depth and the logarithm of tree-like resolution size.

Anisotropic tomography of the East Japan subduction zone: influence of inversion algorithms

SUMMARY An important element of seismic tomography is the inversion process. In this work, we use P-wave arrival times of local earthquakes recorded at onshore and offshore seismic stations in East Japan to investigate the influence of two well-known inversion algorithms (LSQR and L-BFGS-B) on anisotropic tomography. Our synthetic tests show that a large damping parameter in the LSQR algorithm can lead to a stable and fast convergence, but it can result in many small value disturbances. The L-BFGS-B algorithm, which has second-order convergence, could converge fast to the optimal solution without damping regularization, but an inappropriate bound on the unknown parameters makes them hard to be recovered fully and causes strong trade-off between isotropic velocity and azimuthal anisotropy. If appropriate control parameters are adopted, the two inversion algorithms lead to almost the same results, though the L-BFGS-B provides a more efficient convergence and leads to a slightly better fit to the data than LSQR does. The two algorithms are applied to investigate the 3-D P-wave velocity (Vp) structure and azimuthal anisotropy of the East Japan subduction zone. Our results show that high-Vp anomalies and trench-normal fast-velocity directions (FVDs) exist in the forearc crust beneath the Pacific Ocean off South Hokkaido, which may reflect a cold and hydrated forearc crust with aligned microcracks or fractures. Significant low-Vp anomalies and trench-parallel FVDs exist at 40–80 km depths beneath Hokkaido, reflecting a water-rich mantle wedge with aligned B-type olivine. In the subducting Pacific slab, strong anisotropy with trench-parallel FVDs is revealed, reflecting localized horizontal bending of the slab.

Multiple models for outbreak decision support in the face of uncertainty

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.