Optimal management of agricultural systems

To remain competitive, many agricultural systems are now being run along business lines. Systems methodologies are being incorporated, and here evolutionary computation is a valuable tool for identifying more profitable or sustainable solutions. However, agricultural models typically pose some of the more challenging problems for optimisation. This chapter outlines these problems, and then presents a series of three case studies demonstrating how they can be overcome in practice. Firstly, increasingly complex models of Australian livestock enterprises show that evolutionary computation is the only viable optimisation method for these large and difficult problems. On-going research is taking a notably efficient and robust variant, differential evolution, out into real-world systems. Next, models of cropping systems in Australia demonstrate the challenge of dealing with competing objectives, namely maximising farm profit whilst minimising resource degradation. Pareto methods are used to illustrate this trade-off, and these results have proved to be most useful for farm managers in this industry. Finally, land-use planning in the Netherlands demonstrates the size and spatial complexity of real-world problems. Here, GIS-based optimisation techniques are integrated with Pareto methods, producing better solutions which were acceptable to the competing organizations. These three studies all show that evolutionary computation remains the only feasible method for the optimisation of large, complex agricultural problems. An extra benefit is that the resultant population of candidate solutions illustrates trade-offs, and this leads to more informed discussions and better education of the industry decision-makers.

Optimal management of conflicting species: Grey seal (Halichoerus grypus) and Atlantic salmon (Salmo salar) in the Baltic Sea

The objective of this thesis is to examine the economic effects in the conflict between grey seal population and the salmon fishery in the Baltic Sea. We will formulate a bioeconomic model which provides new insights on the optimal management of Atlantic salmon with respect to the effects brought about by the grey seal population. As the catch losses caused by seals have an effect on salmon fishery in Baltic, we will study how seal population affects the present value of the salmon fishery. The study considers the Finnish coastal trap net fishery. The bioeconomic model considers a scenario of sole salmon fishery and a scenario of salmon fishery affected by the grey seal population. On the basis of these scenarios, a seal compensation scheme is introduced. We can observe a significant economic seal-induced effect on the salmon fishery. The results suggest that the present seal compensation scheme emploid by the Finnish government is suboptimal. This thesis is part of the TARMO –project, in which the conflict between grey seal population and salmon fishery is studied using the methods of environmental economics.

Optimal multispecies fishery management in the Baltic Sea: A bioeconomic analysis

The aim of the thesis is to assess the fishery of Baltic cod, herring and sprat by simulation over 50 years time period. We form a bioeconomic multispecies model for the species. We include species interactions into the model because especially cod and sprat stocks have significant effects on each other. We model the development of population dynamics, catches and profits of the fishery with current fishing mortalities, as well as with the optimal profit maximizing fishing mortalities. Thus, we see how the fishery would develop with current mortalities, and how the fishery should be developed in order to yield maximal profits. Especially cod stock has been quite low recently and by optimizing the fishing mortality it could get recovered. In addition, we assess what would happen to the fisheries of the species if more favourable environmental conditions for cod recruitment dominate in the Baltic Sea. The results may yield new information for the fisheries management. According to the results the fishery of Baltic cod, herring and sprat are not at the most profitable level. The fishing mortalities of each species should be lower in order to maximize the profits. By fishing mortality optimizing the net present value would be almost three times higher in the simulation period. The lower fishing mortality of cod would result in a cod stock recovery. If the environmental conditions in the Baltic Sea improved, cod stock would recover even without a decrease in the fishing mortality. Then the increased cod stock would restrict herring and sprat stock remarkably, and harvesting of these species would not be as profitable anymore.

Optimal management of beaver population using a reduced-order distributed parameter model and single network adaptive critics

Beavers are often found to be in conflict with human interests by creating nuisances like building dams on flowing water (leading to flooding), blocking irrigation canals, cutting down timbers, etc. At the same time they contribute to raising water tables, increased vegetation, etc. Consequently, maintaining an optimal beaver population is beneficial. Because of their diffusion externality (due to migratory nature), strategies based on lumped parameter models are often ineffective. Using a distributed parameter model for beaver population that accounts for their spatial and temporal behavior, an optimal control (trapping) strategy is presented in this paper that leads to a desired distribution of the animal density in a region in the long run. The optimal control solution presented, imbeds the solution for a large number of initial conditions (i.e., it has a feedback form), which is otherwise nontrivial to obtain. The solution obtained can be used in real-time by a nonexpert in control theory since it involves only using the neural networks trained offline. Proper orthogonal decomposition-based basis function design followed by their use in a Galerkin projection has been incorporated in the solution process as a model reduction technique. Optimal solutions are obtained through a "single network adaptive critic" (SNAC) neural-network architecture.

Reference Points and Optimal Management in Stochastic Age-Structured Fisheries Models

The purpose of this article is to characterize dynamic optimal harvesting trajectories that maximize discounted utility assuming an age-structured population model, in the same line as Tahvonen (2009). The main novelty of our study is that uses as an age-structured population model the standard stochastic cohort framework applied in Virtual Population Analysis for fish stock assessment. This allows us to compare optimal harvesting in a discounted economic context with standard reference points used by fisheries agencies for long term management plans (e.g. Fmsy). Our main findings are the following. First, optimal steady state is characterized and sufficient conditions that guarantees its existence and uniqueness for the general case of n cohorts are shown. It is also proved that the optimal steady state coincides with the traditional target Fmsy when the utility function to be maximized is the yield and the discount rate is zero. Second, an algorithm to calculate the optimal path that easily drives the resource to the steady state is developed. And third, the algorithm is applied to the Northern Stock of hake. Results show that management plans based exclusively on traditional reference targets as Fmsy may drive fishery economic results far from the optimal.

Identifying optimal feeding habitat and proposed Marine Protected Areas (pMPAs) for the black-legged kittiwake (Rissa tridactyla) suggests a need for complementary management approaches

Marine Protected Areas (MPAs) are an important conservation tool. For marine predators, recent research has focused on the use of Species Distribution Models (SDMs) to identify proposed sites. We used a maximum entropy modelling approach based on static and dynamic oceanographic parameters to determine optimal feeding habitat for black-legged kittiwakes (Rissa tridactyla) at two colonies during two consecutive breeding seasons (2009 and 2010). A combination of Geographic Positioning System (GPS) loggers and Time-Depth Recorders (TDRs) attributed feeding activity to specific locations. Feeding areas were <30 km from the colony, <40 km from land, in productive waters, 25–175m deep. The predicted extent of optimal habitat declined at both colonies between 2009 and 2010 coincident with declines in reproductive success. Whilst the area of predicted optimal habitat changed, its location was spatially stable between years. There was a close match between observed feeding locations and habitat predicted as optimal at one colony (Lambay Island, Republic of Ireland), but a notable mismatch at the other (Rathlin Island, Northern Ireland). Designation of an MPA at Rathlin may, therefore, be less effective than a similar designation at Lambay perhaps due to the inherent variability in currents and sea state in the North Channel compared to the comparatively stable conditions in the central Irish Sea. Current strategies for designating MPAs do not accommodate likely future redistribution of resources due to climate change. We advocate the development of new approaches including dynamic MPAs that track changes in optimal habitat and non-colony specific ecosystem management.

Optimal management of natural resources. Accounting for heterogeneity

Dynamic optimization methods have become increasingly important over the last years in economics. Within the dynamic optimization techniques employed, optimal control has emerged as the most powerful tool for the theoretical economic analysis. However, there is the need to advance further and take account that many dynamic economic processes are, in addition, dependent on some other parameter different than time. One can think of relaxing the assumption of a representative (homogeneous) agent in macro- and micro-economic applications allowing for heterogeneity among the agents. For instance, the optimal adaptation and diffusion of a new technology over time, may depend on the age of the person that adopted the new technology. Therefore, the economic models must take account of heterogeneity conditions within the dynamic framework. This thesis intends to accomplish two goals. The first goal is to analyze and revise existing environmental policies that focus on defining the optimal management of natural resources over time, by taking account of the heterogeneity of environmental conditions. Thus, the thesis makes a policy orientated contribution in the field of environmental policy by defining the necessary changes to transform an environmental policy based on the assumption of homogeneity into an environmental policy which takes account of heterogeneity. As a result the newly defined environmental policy will be more efficient and likely also politically more acceptable since it is tailored more specifically to the heterogeneous environmental conditions. Additionally to its policy orientated contribution, this thesis aims making a methodological contribution by applying a new optimization technique for solving problems where the control variables depend on two or more arguments --- the so-called two-stage solution approach ---, and by applying a numerical method --- the Escalator Boxcar Train Method --- for solving distributed optimal control problems, i.e., problems where the state variables, in addition to the control variables, depend on two or more arguments. Chapter 2 presents a theoretical framework to determine optimal resource allocation over time for the production of a good by heterogeneous producers, who generate a stock externalit and derives government policies to modify the behavior of competitive producers in order to achieve optimality. Chapter 3 illustrates the method in a more specific context, and integrates the aspects of quality and time, presenting a theoretical model that allows to determine the socially optimal outcome over time and space for the problem of waterlogging in irrigated agricultural production. Chapter 4 of this thesis concentrates on forestry resources and analyses the optimal selective-logging regime of a size-distributed forest.

Optimal performance fee and flow of funds in asset management contracts

This paper investigates the importance of ow of funds as an implicit incentive in the asset management industry. We build a two-period bi- nomial moral hazard model to explain the trade-o¤s between ow, per- formance and fees where e¤ort depends on the combination of implicit ( ow of funds) and explicit (performance fee) incentives. Two cases are considered. With full commitment, the investor s relevant trade-o¤ is to give up expected return in the second period vis-à-vis to induce e¤ort in the rst period. The more concerned the investor is with today s pay- o¤, the more willing he will be to give up expected return in the second period by penalizing negative excess return in the rst period. Without full commitment, the investor learns some symmetric and imperfect infor- mation about the ability of the manager to obtain positive excess return. In this case, observed returns reveal ability as well as e¤ort choices. We show that powerful implicit incentives may explain the ow-performance relationship with a numerical solution. Besides, risk aversion explains the complementarity between performance fee and ow of funds.

Private or public? a taxonomy of optimal ownership and management regimes

We develop a theory of public versus private ownership based on value diversion by managers. Government is assumed to face stronger institutional constraints than has been assumed in previous literature. The model which emerges from these assumptions is fexible and has wide application. We provide amapping between the qualitative characteristics of an asset, its main use - including public goods characteristics, and spillovers toother assets values - and the optimal ownership and management regime. The model is applied to single and multiple related assets. We address questions such as; when is it optimal to have one of a pair ofr elated assets public and the other private; when is joint management desirable; and when should a public asset be managed by the owner of a related private asset? We show that while private ownership can be judged optimal in some cases solely on the basis of qualitative information, the optimality of any other ownership and management regimes relies on quantitative analysis. Our results reveal the situations in which policy makers will have difficulty in determining the opimal regime.