Natural Resource Modelling

Abstract.  Ensuring drought resilience for farmers is an important policy concern. Yet, a quantitative treatment of the concept of drought resilience has been lacking in the literature. This paper designs a mathematical model of drought resilience to assess farmers’ survival strategies when faced with the prospect of repeated droughts. A key distinction is being made here between consecutive droughts and one‐off droughts, as it is the former, which is of most concern to farmers as well as policy makers. The mathematical model is generalized to incorporate the possibility of more than one set of a certain number of consecutive droughts occurring in the future. Findings indicate varying implications for groundwater sustainability when resilience outcomes are directly linked to the length of a farmer's drought planning horizon as well as to the planned minimum consumption during drought years.

A model of renewable resource exploitation under event uncertainty is formulated. The model is applied to analyze the situation in which excessive water diversion for human needs can lead to the extinction of an animal population. Special attention is given to uncertainty regarding the conditions that lead to extinction. The manner in which the potential benefit foregone due to the species' extinction (the “extinction penalty”) induces more conservative exploitation policies is studied in detail. When the extinction penalty is ignored, the optimal policy is to drive the resource stock to a particular equilibrium level from any initial state. When the extinction penalty is accounted for and the conditions that lead to extinction are not fully understood (i.e., involve uncertainty), an interval of equilibrium states is identified, which depends on the penalty and on the immediate extinction risk.

It is assumed that the probability of destruction of a biological asset by natural hazards can be reduced through investment in protection. Specifically a model, in which the hazard rate depends on both the age of the asset and the accumulated invested protection capital, is assumed. The protection capital depreciates through time and its effectiveness in reducing the hazard rate is subject to diminishing returns. It is shown how the investment schedule to maximize the expected net present value of the asset can be determined using the methods of deterministic optimal control, with the survival probability regarded as a state variable. The optimal investment pattern involves “bang‐bang‐singular” control. A numerical scheme for determining jointly the optimal investment policy and the optimal harvest (or replacement) age is outlined and a numerical example involving forest fire protection is given.

Bioeconomic analyses of spatial fishery models have established that marine reserves can be economically optimal (i.e., maximize sustainable profit) when there is some type of spatial heterogeneity in the system. Analyses of spatially continuous models and models with more than two discrete patches have also demonstrated that marine reserves can be economically optimal even when the system is spatially homogeneous. In this note we analyze a spatially homogeneous two‐patch model and show that marine reserves can be economically optimal in this case as well. The model we study includes the possibility that fishing can damage habitat. In this model, marine reserves are necessary to maximize sustainable profit when dispersal between the patches is sufficiently high and habitat is especially vulnerable to damage.

ABSTRACT. Illegal game meat hunting in the Serengeti National Park, Tanzania, and adjacent game reserves provides an important source of protein and cash income to local communities. We construct a profitability model that describes the spatial distribution of the economic costs and benefits of illegal hunting in the Serengeti during the late 1980s and early 1990s. Costs included capital investment in hunting weapons, W_R, and the opportunity cost of hunting, W_O, both held to be constants; and two spatially variable components, the logistic effort of traveling to hunting areas, W_L, and the penalties incurred if arrested, W_P. Benefit was the expected income from the sale of meat from resident wildlife species. The model suggests: (1) W_R is the most important cost. (2) W_L is the second most important cost and likely to determine the spatial distribution of hunting activity if hunters seekto minimize costs. (3) W_O and W_P are of minor importance, the former because alternative sources of income provide low pay, the latter because the overall chance of being arrested is low. (4) W_P exceeds W_L only in areas close to the boundary of protected areas. (5) Although resident wildlife contributes only a minor share of illegal offtake compared to the migratory herds, hunting resident wildlife is profitable in 68% of the area. This suggests that hunting of resident and migratory wildlife is highly profitable and may explain why the utilization of the target populations has become increasingly unsustainable.

Taking advantage of the electrification strategy, Northwest China has made full use of its natural resources endowment, to develop renewable energy as the substitution of thermal power. To evaluate carbon dioxide (CO₂) emissions from electric power sector, an extended Kaya identity equation and the Logarithmic mean Divisia index decomposition method are applied to Northwest China from 1998 to 2017. Six explaining factors are analyzed, including carbon intensity, energy mixes, generating efficiency, electrification, economy and population. The results show that driving forces of CO₂ emissions from electricity system varied greatly among provinces. Generally, economic growth has mainly contributed to increase CO₂ emission, while the improvement in the power‐generating efficiency has crucially decreased CO₂ emission. In 2017, Promoting electrification directly increased CO₂ emissions from electric system, but indirectly reduced CO₂ emissions from the whole region by 5.10% through the estimation of a clean development mechanism method. Therefore, local governments are suggested continuing to promote electrification to guide future emission reduction, while enterprises and individuals need to make their own contributions to low‐carbon development.

Recommendations for Resource Managers:

Variations of carbon dioxide (CO₂) emissions of all five provinces in Northwest China are analyzed.

After 20 years of effort, technical approaches to natural resource management have not been effective in preventing overuse and destruction of resources. The resource modeling community can help to change our present course toward destruction by (1) recognizing and publicizing the ineffectiveness of scientific, technical and magical approaches to resource management, (2) pointing out that the resolution of environmental problems is impossible unless the social problems of excessive human population sizes and excessive consumption are effectively addressed, (3) making clear the irrationality and imprudence of current environmental decisionmaking under uncertainty, and (4) pointing out the impossibility of achieving conservation goals by management that attempts to achieve economic optima.

ABSTRACT. The use of marine protected areas (MPAs) as a basic management tool to limit exploitation rates in marine fisheries has been widely suggested. Models are important in predicting the consequences of management decisions and the design of monitoring programs in terms of policy goals. However, few tools are available that consider both multiple fleets and ecosystem scale dynamics. We use a new applied game theory tool, Ecoseed, that operates within a temporally and spatially explicit biomass dynamics model, Ecopath with Ecosim, to evaluate the efficacy of marine protected areas in the North Sea in both ecological and economic terms. The Ecoseed model builds MPAs based on the change in values of predicted economic rents of fisheries and the existence value of biomass pools in the ecosystem. We consider the market values of four fisheries operating in the North Sea: a trawl fishery, a gill net fishery, a seine fishery, and an industrial (reduction) fishery. We apply existence values, scaled such that their aggregate is similar to the total fishery value, to six biomass pools of concern: juvenile cod, haddock, whiting, saithe, seals, and the collective pool ‘Other predators’ that include marine mammals. Four policy options were considered: to maximize the rent only; to maximize the existence values only; to maximize the sum of the rent and existence values; and, finally, to maximize the sum of the rent and the existence values, but excluding only the trawl fleet from the MPA. The Ecoseed model suggests that policy goals that do not include ecological considerations can negatively impact the rents obtained by the different fishing sectors. The existence values will also be negatively impacted unless the MPA is very large. The Ecoseed model also suggests that policy goals based solely on existence values will negatively impact most fisheries. Under policy options that included ecological considerations, maximum benefits were derived from an MPA that covered 25–40% of the North Sea, placed along the southern and eastern coasts. Finally, the Ecoseed model suggests that an exclusion of the trawl fishery only from the MPA can provide small‐to‐substantial positive impacts to most species and fleets; this relative impact depends on level of interaction between the trawl fleet and the other fleets target species (e.g., through bycatch).

ABSTRACT. In this paper we present a bioeconomic model of a harvesting industry operating over a heterogeneous environment comprised of discrete biological populations interconnected by dispersal processes. The model generalizes the Gordon [1954]/Smith [1968] model of open‐access rent dissipation by accounting for intertemporal and spatial “Ricardian” patterns of exploitation. This model yields a simple, but insightful, framework from which one can investigate factors that contribute to the evolution of resource exploitation patterns over space and time. For example, we find that exploitation patterns are driven by biological and fleet dispersal and biological and economic heterogeneity. We conclude that one cannot really understand the biological processes operating in an exploited system without knowing as much about the harvesting system as about the biological system.