AN EMPIRICAL INVESTIGATION OF THE HARVEST OPERATION USING SYSTEMS SIMULATION

A simple model of the cereal harvest operation was constructed for the Wimmera region of Victoria. The model was used to investigate factors influential in determining the harvesting costs of a machinery system over a period of years. An evaluation of alternative machinery systems was also conducted using the model. The superiority of systems simulation over static analysis was demonstrated by using the model to incorporate stochastic variables and to handle the dynamic nature of the harvest operation. In addition, the model output was shown to provide more information for decision makers than had resulted from previous Australian studies. It was concluded that systems simulation is an appropriate technique for investigating farm management machinery selection problems.     

ECONOMIC ANALYSIS OF ON-FARM SOLUTIONS TO DRAINAGE PROBLEMS IN IRRIGATED AGRICULTURE

Agricultural production in many semi-arid areas over the world is affected by poor drainage and saline conditions. Optimal agricultural management can be considerably different under these conditions than in locations where these problems do not occur. A long-run steady-state model is developed to analyse several management strategies for a farm with limited natural drainage and no access to off farm facilities. The model is applied to a representative farm in California. Under optimal management, the results suggest relatively small evaporation ponds, a reduction in water application, and little change in cropping patterns. Some drainage reuse is optimal when only variable reuse costs are considered. Returns to land and management are positive in all cases considered and benefits from a free off-farm facility are approximately $260/ha.     

Adaptive management decision of agroforestry under timber price risk

In an effort to increase wood production and mitigate environmental problems, agro-forestry practices have emerged as a viable strategy in the Northern Plains of China, where one popular form of the agro-forestry system consists of fast-growing and high-yield plantation of poplar (populus) trees and the underwood planting of button mushroom (Agaricus bisporous). This paper examines adaptive management decision-making with stochastic dynamic programming under risk of timber price. Under the assumption of risk neutral preferences of the investors, the results suggest that the reservation price strategy remains optimal for the harvesting decision of agro-forests: when the timber price is higher than the reservation price, poplar trees should be harvested to end agro-forestry; otherwise, the trees should be retained. Numerical results are presented for sample agro-forest stands, which show that, with underwood planting, the reservation price for timber harvesting will be higher than that in pure forest.     

OPTIMAL FEEDING POLICIES FOR BROILER PRODUCTION: AN APPLICATION OF DYNAMIC PROGRAMMING*

The determination of an optimal feeding and selling strategy for broiler production given a space constraint is formulated as a dynamic programming problem. Production equations derived from trial data are used to obtain an optimal sequence of rations in which energy density changes through time. The stability of the plan is explored and the implications of the results for production research and commercial practice are considered.     

Woody biomass potential for energy feedstock in United States

The production reliability and relatively low costs of sustainably harvested woody biomass such as logging residue and low value roundwood could make it a significant component of the Renewable Fuel Standards portfolio. This research explored a set of woody biomass harvesting combinations of different sources and wood types using a cost minimizing linear programming model populated with disaggregated regional inventory, yield, and cost data, and projected future conventional wood demand of the United States. The model pre-satisfied conventional wood demand before harvesting roundwood as woody biomass. Findings suggest that collecting forest residue and non-merchantable (small sized) timber may provide the largest initial contribution in woody biomass supply. Regional estimations imply that not all regions have the capacity to develop bioenergy plants without using merchantable (medium sized) wood. Within a reasonable range of harvesting costs, demand for roundwood is expected to increase with higher energy production targets. Harvesting merchantable natural softwood as woody biomass has a relatively small impact on marginal supply costs. This will result in little or no disturbance to merchantable natural softwood timber management and operations if demand for woody biomass increased.     

The effect of site quality on economically optimal stand management

This paper proposes a discrete-time type timber harvesting model for simultaneously determining (i) the optimal quantity of seedlings to be planted, (ii) the optimal quantities of timber harvested by thinnings, and (iii) the optimal rotation age. With the help of Microsoft Excel Solver, a generalized reduced gradient algorithm, numerical examples are developed to evaluate the impact of the variations in the quality level of a forest site on the optimal harvest strategy. It is shown that the level of optimal rotation age and optimal quantity of seedlings to be planted can individually exhibit non-monotonicity to the increase in site quality.     

Sheep as capital goods and farmers as portfolio managers: a bioeconomic model of Scandinavian sheep farming

A model analyzing the economics of sheep farming is formulated. The basic idea is simple. Sheep are capital and they are held by farmers as long as their capital value exceeds their slaughter, or meat, value. Farmers are therefore portfolio managers aiming to find the optimal combination of different categories of animals. Yields are compared with the yields from other assets. The model is formulated within a Northern Scandinavian economic and biological setting with a crucial distinction between the outdoors grazing season and the indoors season, and with adult sheep and lambs being different categories. In the first step, the management problem is analyzed with only the meat income of the farmers taken into account. In the next step, income from wool production is considered as well. The analysis provides several results that differ from standard harvesting theory.     

AN OPTIMAL CONTROL MODEL FOR INTEGRATED WEED MANAGEMENT UNDER HERBICIDE RESISTANCE*

The presence of weeds which have developed resistance to chemical herbicides is a problem of rapidly growing importance in Australian agriculture. We present an optimal control model of herbicide resistance development in ryegrass, the weed for which resistance is most commonly reported. The model is used to select the optimal combination of chemical and non-chemical control measures taking account of the trade off between short term profits and the long term level of herbicide resistance. Results indicate that given the threat of resistance there are benefits from integrating a combination of chemical and non-chemical control measures. The optimal strategy is found to include a declining herbicide dosage as resistance develops, with compensatory increases in the level of non-chemical control.     

A DYNAMIC ANALYSIS OF US EXPORT WHEAT PRICING AND MARKET SHARES

The economics of a higher loan rate to support US wheat prices is analysed. Utilising optimal control theory, a dynamic wheat trade model is developed. The basic premise underlying the model is that the United States finds itself having transient monopoly power in the wheat market. An expression for the optimal pricing policy which maximises the present value of expected profits over the indefinite future is derived. Results from both the theoretical and empirical models demonstrate that the US wheat pricing strategy depends on its costs relative to competitors' costs, the discount rate and the competitors' response function. The main policy implication of the analysis is for the dominant wheat exporting country constantly to seek to lower costs relative to competitors and to maintain a price exceeding unit cost without encouraging competitors' expansion.     

Size matters: Optimal management of dynamic systems with varying size

Many natural and economic systems are managed to deliver the highest benefits to society but are subject to regime shifts. We specifically consider the variability of the size of the system itself as a key driver of a regime shift. We address the question of how the optimal management of these systems should vary with its size. Put simply, certain management options might work when the system is of a given size, while others might be preferred when the system has grown or shrunk. In this paper, we develop a model that allows us to analyse the effect of the size of the system on its optimal management. We apply this model to a case of water pollution in a reservoir/lake that varies in size over time: sometimes the lake is deep and sometimes it is shallow. Numerical simulations were conducted to compare optimal management of the reservoir with and without explicitly modelling its size variation. The findings show that the overall social costs of optimally managing pollution are significantly smaller when the variability in size is taken into account. This is due to differences in the timing and magnitude of the optimal control. The key implication is that the variability of the size of a system should be explicitly considered in this type of management problems.     

Aggregating forest harvesting activities in forest plantations through Integer Linear Programming and Goal Programming

The inclusion of criteria related to the spatial patterns resulting from forest harvesting activities is an important component of forest planning. Harvesting operations are more efficient when the harvesting areas are clustered. Therewith, it is possible to reduce the displacement of machinery and costs related to construction and maintenance of the road network. In this context, the objective of this study was to evaluate different strategies for aggregating harvesting stands in a forest plantation. We applied two Goal Programming approaches aiming at aggregating harvesting stands and an Integer Linear Programming model for including road investments into strategic forest planning.     

发展赴俄森林采伐产业的思考

内蒙古大兴安岭森林采伐量锐减,为了有效地解决问题,林区应该根据自身发展的需要,把赴俄采伐作为森工企业的发展项目,坚持"走出去"的发展战略,整合现有对俄采伐加工项目,建立统一管理的赴俄采伐机构,实行股份合作制经营,走规模化经营发展之路,扩大赴俄合作采伐的生产规模,真正促进赴俄采伐产业的健康有序发展。针对内蒙古大兴安岭林区发展赴俄采伐产业实际进行分析,提出了相应的意见和建议。     

A Spatial-Based Decision Support System for wood harvesting management in mountain areas

In this paper, a spatial-based economic model is proposed with the aim of estimating the most likely harvest cost of a forest block in relation to its particular morphological and operating features. This work, which is based on the classical stumpage price assessment method, presents an economic balance of a forest cut, attained by conducting a cost analysis of each logging phase of the different standard harvesting strategies. The study area is in the North-West of Italy, in the Mount Cotolivier forest compartment, in Oulx, Piedmont. The map of the stand structure, which is included in the Oulx Forest Management Plan, was used to locate blocks (areas considered homogeneous according to the stand structure and forest typology) where silvicultural cuts could be scheduled. The feasibility of the selected logging strategies was mapped considering six conditioning factors, of both a topological and a topographic nature. Their influence was weighted by means of a score assignation and integrated in a Multi-Criteria Decision Making procedure. The scores were mathematically combined to calculate a spatial dependent cost-function (Block Exploitation Aptitude, BEA) in which the suitability of each block to be harvested was mapped through a specific strategy. The obtained BEA was then used to estimate the most suitable productivity rate of the harvests of each block. The unitary costs of the strategies were estimated and then compared to find the most profitable one for each block.This model has proved to be effective in generating objective economic results concerning harvest cuts in productive stands in mountainous areas. The proposed methodology simultaneously takes into account different factors and generates feasibility scenarios, in the space domain, for the considered harvesting strategies. The proposed model represents a prototype on which an operational Decision Support System could be based to assist forest managers over the short-medium term.     

Adapting the optimal selective-logging of Scots pine (Pinus sylvestris L.) stands in NE Spain to increasing CO2 concentrations

Predicted increases in CO₂ concentrations will affect forest ecosystems. In particular, they will impact tree growth, which in turn affects reproduction and mortality and consequently, forest planning. This study integrates different climate change scenarios of future biogeochemical processes and an economic model into a forest management model to determine the optimal selective-logging regime of Scots pine stands. It analyzes the economic implications of the management changes in comparison with the business as usual strategy. Adaption to new climatic conditions shows that it is optimal to increase the number of standing trees and to reduce the age of the logged trees. The results suggest that the failure to adapt the management regime has clear implications on the profitability of forests. Moreover, they show that higher mortality is likely to have a significant impact on the optimal forest management regime.     

FISHERY BUY-BACK PROGRAMMES AND ECONOMIC WELFARE

Fishery buy-back programmes reduce the availability to the industry of certain inputs used in the harvesting process, thereby increasing fishing costs and reducing the amount of effort applied to the fishery. The reduction in effort generates an economic benefit which must be weighed against the increased costs. The paper develops an economic model of a buy-back programme which can be used to estimate the effect of the programme on economic welfare. The model is applied to the Tasmanian rock lobster fishery.     

Investment in site-specific crop management under uncertainty: implications for nitrogen pollution control and environmental policy

This paper applies an option‐pricing model to analyze the impact of uncertainty about output prices and expectations of declining fixed costs on the optimal timing of investment in site‐specific crop management (SSCM). It also analyzes the extent to which the level of spatial variability in soil conditions can mitigate the value of waiting to invest in SSCM and influence the optimal timing of adoption and create a preference for custom hiring rather than owner purchase of equipment. Numerical simulations show that while the net present value (NPV) rule predicts that immediate adoption is profitable under most of the soil conditions considered here, recognition of the option value of investment indicates that it is preferable to delay investment in SSCM for at least 3 years unless average soil quality is high and the variability in soil quality and fertility is high. The use of the option value approach reveals that the value of waiting to invest in SSCM raises the cost‐share subsidy rates required to induce immediate adoption above the levels indicated by the NPV rule.     

Costs and Risks of Testing and Segregating Genetically Modified Wheat

Development of genetically modified (GM) crops is challenging the functions of the grain marketing system. A stochastic optimization model was developed in this study to determine optimal testing strategies. The model chooses the optimal testing strategy that maximizes utility (minimizes disutility) of additional system costs due to testing and rejection, and allows the estimation of the risk premium required for sellers to undertake the dual marketing of GM and non-GM segregations over a non-GM system. Costs are estimated for a vertically integrated grain export chain including testing, rejection, and a risk premium. The model includes elements of costs and risks of adventitious commingling at all stages of the marketing chain, variety declaration, grower truth-telling, and accuracy of testing technologies. Sensitivities were evaluated for the effects of GM adoption, risk parameters, variety declaration, and tolerance levels.     

AN ANALYSIS OF MULTIOBJECTIVE DECISION-MAKING FOR THE SCOTTISH INSHORE FISHERY

The Scottish inshore fishery is used to illustrate the application of a multiobjective analytical model to decision-making for fisheries management. Although the quantitative analysis is necessarily fishery-specific, much of the discussion is of more general applicability. A hybrid modelling approach is used to analyse fisheries management objectives for this fishery: regression-based models of the fishing process are used to provide input into linear and goal programming models, the linear programme also providing input into the goal programme. Optimisation of the goal programming model results in an ‘optimal’ pattern of resource allocation for the Scottish inshore fishery.     

Optimal strategies for regional cultivar testing

In undertaking cultivar trials, the variability of the response of the cultivars to the different environments in which they are grown introduces the possibility of release errors and non-release errors in the decisions made on the basis of the trial results. In this article a model is developed that accounts for the economic costs of those errors as well as the costs of operating the trials, and enables the features of the optimal cultivar testing program to be identified. The model is illustrated by application to wheat cultivar trials in central and southern NSW.