Regional forestry sector modelling of options for industrial forest plantations in Indonesia
Degree GrantorUniversity of Canterbury
Degree NameDoctor of Philosophy
Regional resource planning and decision-making for industrial forest plantation development increasingly involves participation by members of the public. Motivation to maximise or minimise the degree to which groups with various interests can satisfy their individual objectives should recognise outcomes arrived at in a consensus decision-making environment. In this study, a planning framework is devised and adopted, which describes a regional planning system prepared in order to assist in the design and evaluation of strategic industrial forest plantation development in Indonesia. The central component of this planning system is interactive Multi-Objective Decision Making (MODM) modelling with linkages between optimisation and simulation models. The framework of the whole planning system demonstrates the capability and feasibility of resolving important and conflicting objectives through discussion and communicative decision processes that can be reinforced with modelling sensitivity outputs. In other words, a methodology is developed that allows strategic options for plantation planning to be analysed interactively. The MODM models here are MINMAX and MINSUM goal programming formulations. This model has various features that characterise industrial forest plantation development planning, including physical production, social, economic, environmental, and location aspects. This formulation, moreover, has several advantages such as capturing the essence of the multi-objective decision making problem, encompassing the entire range of feasible tradeoffs among all objectives through parametric programming in order to derive forestland allocations optimally, as well as serving important implementable and practical interests. A minimum economic size (MES) spreadsheet-based model is run to determine profitable plantation sizes by using financial criteria such as IRR and NPV. The MES model outputs are then incorporated within MODM models. A major part of the research reported here was to develop a way of transferring data between simulation and LP models directly through file transfers, and transferring LP derived solutions directly back to the simulation model. This linkage has several advantages: for example, theoretically optimal LP solutions are usually unrealistic in practical or implementational terms because of administrative, social, environmental and other similar problems facing forest management; whereas simulation allows one to explore the effects of deviations from "optimal" LP solutions, and to simulate both in more detail and in broader aggregations of things such as age classes, log types and locations. If measures, e.g. wood and financial flows, are unsatisfactory, some constraints are modified and formed for the relevant LP model utilising, for example, the future log assortment flow consequences and the tradeoffs among them. The automated linkage between optimisation and simulation models provides easy data and solution transfers so that decision makers and stakeholders may gain detailed insights before any consensus decisions need to be made. A geographic information system (GIS) is utilised to enhance pictorially the preferred solutions, information, and appearance. The whole planning system is demonstrated and tested in an indicative case study. The results display the major advantages of consistency, clarity and simplicity of the approach to regional forestland allocation. The framework and results at this stage are only preliminary, because some data are still incomplete and unrefined. This study is, therefore, an initial description and explanation of methodology and an indication of the nature of desirable results rather than a firm policy recommendation pertaining to the case study area. In principle, the framework could also become multi-temporal by creating each variable in a time-dependent fashion. The planning system developed has the ability to incorporate social, financial, environmental, and technical variables in a comprehensive participatory development process. The ultimate value of the quantitative information represented in this framework (or methodology) through a background case study analysis is its ability to facilitate policy formulation to satisfy decision-makers and stakeholders when making informed choices in fundamental management decisions.