Abstract Uncertainty occupies a major place in the literature, both when it is being defined and when it is being measured. The mathematical viability theory framework provides useful concepts to go beyond the probabilistic views of uncertainty that are not able to capture all forms of uncertainty, particularly in the absence of statistical regularities. Bounded‐set uncertainty can help to analyze changes in the evolutionary conditions that affect ecological and social systems with probabilistic or nonprobabilistic distributions. This paper introduces uncertainty into a viability model by associating stochastic and bounded‐set uncertainty related to sales price as a driver of economic uncertainty. Based on an illustration of agroecosystems, the model identifies decision rules that guarantee viability. The larger the initial crop portfolio for sequential diversification is, the lower the costs to belong to the viability kernels will be, regardless of economic and environmental constraints. The diversification of farming systems transforms their complexity into an advantage against uncertainty, which opens up numerous viability trajectories.Recommedations for Resource Managers Considering the relevance of a bounded set of economic uncertainty, restoring soil quality and choosing diversification guarantee viability and allow a single generation of farmers to relax both their environmental and economic constraints. When the time available to conform to both their environmental and economic constraints decreases, sequential diversification can be used as a tool to relax the economic constraint of self‐financing soil restoration. Sequential diversification is an asset, especially for low‐quality soil. Even under uncertainty and very low soil quality, diversification drastically reduces the value‐at‐risk for viable farming investment. Eligibility for agricultural subsidies should be conditional on soil quality to motivate practices of soil restoration that provide a sort of insurance against economic uncertainty.

Abstract The destructive impacts of fishing on marine habitats may be mitigated through the allocation of catch shares between different user groups. We assess the optimal allocation of harvest across multiple user groups and how fishery outcomes are affected when catch shares are allocated suboptimally. We incorporate the harvest allocation process into a bioeconomic model in which fishing‐induced habitat damage occurs and a single fish stock is targeted by two user groups characterized by fishing technologies of differing environmental impact. Results show that maximizing the overall profit of the fishery often requires the catch share of one of the groups to be set at zero. The effects on biological and economic outcomes of deviating from this allocation to ensure positive catch shares for all groups depend on the strength of habitat–fishery interactions, difference in fishing costs, and whether the suboptimal allocation is made to the high or low impact group.Recommedations for Resource Managers Ignoring the impacts of fishing on marine environments can undermine attempts to sustainably manage fish stocks and to generate economic benefits that fisheries are capable of. Allocation of harvest across different fishery user groups is one means of managing habitat impacts of fishing. Economically optimal harvest allocation often requires the exclusion of either high impact user groups in a fishery where stocks are reliant on vulnerable habitats or low impact but less efficient user groups where habitat is fast to recover from damage. Suboptimal allocations of harvest need careful consideration as they may require trading‐off improved biological outcomes against lower fishery‐wide profit. Suboptimal allocations made in favor of a group causing higher habitat damage may result in collapse of fish stocks in environments where stocks are reliant on vulnerable environments and the damage rate of fishing is high.

Abstract This study aims to better understand why farmers do not convert to organic farming by studying decision trajectories in a dynamic agent‐based model. In this model, an agent's decision on transitioning to organic is based on the comparison between satisfaction with its current situation and potential satisfaction with an alternative farming strategy. A farmer's satisfaction was modeled by borrowing from the Theory of Reasoned Action and computed by comparing the farmer's performance over time against the farming practices of other farmers to which he/she lends great credibility (“important others”). Analysis identified five different reasons why a farmer does not change strategy. Three are due to satisfaction or recovered satisfaction with the current situation. The conversion to organic farming is effectively a major change and cannot be envisaged if the farmer is currently satisfied. Satisfaction can be recovered when evaluation by the farmer or “important others” finds an improvement of the current situation. A farmer's decision to not convert can also be due to negative evaluations of organic farming by “important others,” or to dissatisfaction with the current situation being too transient to prompt the effort to convert.Summary for ManagersA farmer's decision on whether or not to convert to organic farming is deeply influenced by his/her satisfaction with the current strategy and potential satisfaction under an alternative farming strategy.A farmer's satisfaction is computed by comparing the farmer's performance over time against the farming practices of other farmers to which he/she lends great credibility.The conversion to organic farming is effectively a major change, and a farmer will not envisage a change of strategy if he/she is satisfied with their current situation.A farmer's satisfaction can be recovered when evaluation by the farmer or social peers finds an improvement of the current situation.If a farmer's credible peers have a negative assessment of organic farming or if his/her own dissatisfaction with the current situation is too short‐lived, then farmer will not convert to organic farming.

Abstract West Nile virus (WNV) is a vector‐borne disease spread primarily between birds and mosquitoes. In the United States, the main methods used to control WNV are aimed at lowering the vector population through reducing births (larvicide) or increasing the mortality of adults (adulticide). We investigate the potential of a novel control, vaccination of newborn birds (nestlings). We first apply standard optimal control (OC) methodology to a nonautonomous differential equation model for WNV transmission incorporating avian stage structure and allowing larvicide, adulticide, and nestling vaccination. We convert the continuous OC results to practical advice that accounts for restrictions on the frequency of control application in the field. We then develop an alternative optimization algorithm using genetic algorithms and compare control advice for various budget constraints. We find that vaccination is recommended, provided budgets are sufficiently high, and explore how differences in control efficacy and vector biting rates on host stages affect our results. Recommendations for Resource Managers: Genetic algorithms are able to incorporate practical restrictions on control application as well as budget constraints. Advice depends on the efficacies of controls as well as model parameters. At high‐efficacy estimates, adulticide is recommended for low budgets. Vaccination is recommended when budgets are sufficiently high, and sooner for scenarios where nestling hosts have increased vector exposure. If vector control has low efficacy and nestlings have increased vector exposure relative to older hosts, including vaccination may reduce levels of infectious mosquitoes below those resulting from high‐efficacy vector control alone.

Abstract The study investigates the sustainability of an urban system in the presence of haphazard urban development taking place in cities, through the use of nonlinear model system of differential equations. Here, the urban system comprises of urban forests and population, along with different development activities and associated pollution. In addition to equilibrium points and their stabilities, the qualitative behavior of the model system is also being established by determining the uniform persistence. However, quantitative behavior is being predicted through numerical solutions of the model system. The obtained behaviors demonstrate that unplanned development and its associated excessive pollution can disturb the stability of the urban system. It is also being revealed that overexploitation of forest resources by population and devastation of forest resources, as well as of population, through pollutants concentration may also pose a serious threat for a sustainable urban system in the long time.Recommendations for Resource Managers The sustainability of an urban system in the presence of haphazard development activities and excessive pollution is a matter of great concern as it may lead to extinction of urban forests as well as of urban population. The admissible amount of control over urban development through government intervention is necessary for the orderly development of urban areas in harmony with natural environment. This would also help in protecting forest resources and, therefore, on the survival of its dependent population. Urban forestry should be practiced, where emphasis should be on plantation of such vegetation, trees, and shrubs, etc., which have the pollution tolerating and mitigating abilities. In order to establish sustainable urban system, urban development activities should harmonize the people and the environment, while taking proper advantage of abundant natural resources.

Abstract We investigate the stability of International Environmental Agreements. The analysis of Chwe is extended by investigating the question how to find farsightedly stable coalitions. The myopic stability concept of d'Aspremont, Jacquemin, Gabszeweiz, and Weymark and the farsighted stability concept of Chwe are compared. Farsighted stability, direct and indirect domination are discussed. Considering of the direct domination, we check for the single‐step stability by comparing the profits of every coalition member after one‐step deviation has occurred, while considering the indirect domination (farsightedness) we check for the multistep stability by comparing the profits of every coalition member after a series of deviations have come to an end. On the contrary, myopic stability assumes that players look only one step ahead. The improvement of farsightedly and myopically stable coalitions to the environment quality and welfare are compared. Only the farsightedly stable coalition improves the welfare and abatement by 20% and 79% in comparison to all three myopically stable coalitions together. Algorithms are developed, which can find all farsightedly stable coalitions structures.Considerations for ManagementTaking into account findings, management considerations may include: Myopically stable coalitions are typically subsets of farsightedly stable coalitions. Farsightedly stable coalitions are the largest stable coalitions without side payments, and bring the biggest improvement in environmental quality and welfare. We predict the formation of coalitions that are bigger than myopically stable but smaller than farsightedly stable coalitions. This conclusion is valid under the assumption that transfers are not allowed.

Abstract Quarry operators and government officials often forecast the long‐run demand for construction aggregate by multiplying the projected population each year by a per capita consumption number, and adding up these annual demand forecasts. This approach is theoretically unjustified and empirically inaccurate. An alternative approach is to estimate the demand for aggregate from the bottom up, based on forecasts of the construction and maintenance of homes, schools, highways, and other projects that use aggregate.Summary for Managers The long‐run demand for construction aggregate is often forecast using a constant per capita consumption model. However, this model is fatally flawed, both theoretically and empirically, and should not be used for permitting, planning, or land‐use zoning.

Abstract The aim of this paper is to analyze the optimal management of two ecologically interdependent, competing species, roe deer (Capreolus capreolus) and fallow deer (Dama dama). To this end, we develop a numerical stage‐structured model, accounting for species‐specific life history characteristics, gender, and stage‐specific hunting values. Two contrasting management regimes are considered: optimal joint management of the two species and management where the decision maker is ignorant about interspecific competition. Results from our case study show that the presence of interspecific competition reduces roe deer population size and harvest by 30% and 47%, respectively, and reduces the net present value by 9%. High interspecific competition could lead to the exclusion of the roe deer from the area. In contrast, ignorance about the level and consequences of interspecific competition has no impact on harvest decisions and revenues. The explanation is the higher hunting benefits for fallow deer.Summary for Managers Wildlife managers need bioeconomic models for decisions on ecologically interdependent species. This study investigates optimal joint management of roe and fallow deer when the fallow deer exerts a negative impact on roe deer due to interspecific competition. Results show that interspecific competition reduces the net present value of hunting at the study site by 9%. Regulations will not increase the net present value of hunting in a situation where the manager is ignorant of interspecific competition.

Abstract Data collected over the past 25 years reveal that Northern Spotted Owls (Strix occidentalis caurina) of the Oregon Coast region are being displaced by invasive Barred Owls (Strix varia). A component of the U.S. Fish and Wildlife Service recovery plan is studying the culling of Barred Owls from Spotted Owl habitat. Using information theory to perform a model selection, we fit the most parsimonious ordinary differential equation competition model to the data. We then augment the model to incorporate Barred Owl culling and determine the minimum culling rate required to completely eliminate the Barred Owl population and the amount of time required to achieve such an elimination for various culling rates. Our analysis shows that even with culling Barred Owls, there exists no coexistence equilibrium given the current growth and competition parameters.

Abstract During the several last decades, environmental scientists use numerical modeling as a tool in their studies and investigations of aquatic systems. Ecological and hydrodynamic models are developed in parallel regarding their complexity, uncertainty, and computational power. Ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, evaluate remedial practices in response to eutrophication etc. This review paper deals with the progress in ecological modeling related to eutrophication processes, specifically in models that describe the trophic state dynamics of hypoxic/anoxic aquatic ecosystems. Nine dynamic ecological models coupled or noncoupled with hydrodynamic models have been discussed based upon their history, complexity, limitations, recent detailed modeling applications, and their important results. The advantages and disadvantages of these models are presented along with their application areas.