A Model to Support Resource Allocation Decisions

A network of national parks can be viewed as a management portfolio of natural assets that have a ‘business goal’ of maximising the flow of benefits from national parks to society (Stephens, 1999). However, inadequate funding is a significant factor in the failure of national parks to meet their objectives, and the problem is exacerbated by the ad hoc decision-making processes used by national park management agencies to allocate these limited funds among their conservation responsibilities (Bell & Martin, 1987). These decision-making processes need to be improved.

When examining environmental decision-making, concepts like efficiency, equity, effectiveness, and legitimacy are raised (Adger, Brown, Fairbrass, Jordan, Paavola et al., 2003; Fisher, 1998). In economics, efficiency relates to the maximisation of human welfare; effectiveness refers to the capacity of a decision to achieve its objectives; equity is a matter of distributive justice or the distributional consequences of a decision; and legitimacy relates to the acceptability of the decision process to participants on the basis of who makes and implements the decisions (Adger et al., 2003). These concepts may have multiple meanings depending on who is defining them, and it is unlikely that all four concepts will be maximised in a decision (Fisher, 1998). A new approach is needed for resource allocation decision-making; one that transcends concepts of effectiveness, efficiency, equity, and legitimacy. Decisions must be transparent, repeatable, and based on current best practice. Decision-makers need practical and robust models to help them better understand their asset portfolio so they can make better annual resource allocation decisions in both the short-term and the long-term.

The focus of the research is to develop a decision-making model to assist decision-makers with the allocation of resources among national parks. To do this, parameters for the proposed model must be identified. Following from the above discussion, the model will take a rational decision approach. This approach is the most appropriate because the proposed model is intended to facilitate better decisions, not explain or predict behaviour. The parameters for the proposed model are outlined below. The sub-headings refer to the aspects of the rational

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decision-making approach outlined in Figure 2.7. These are: (1) define objectives; (2) identify constraints; (3) identify alternative means of achieving the objective; (4) define criteria for comparing and evaluating options; and, (5) evaluate each option against each criterion using a numerical scoring system and sum numerical scores for each option (Fisher, 1998).

(1) Objectives

The objective of the proposed model to aid decision-making is to allocate resources among a set of national parks; the purpose of the national parks must be agreed upon so that the characteristics or benefits they deliver can be compared. Biological considerations alone are an inadequate guide to conservation priority because environmental decisions typically draw on multidisciplinary knowledge bases (Clarke & Bell, 1986; Kiker et al., 2005). The Convention on Biological Diversity (CBD), which most nations are party to, is concerned with the conservation of biological diversity; the sustained use of biological resources; and the equitable sharing of benefits arising from biological diversity including genetic resources (Convention on Biological Diversity, 1993; Siebenhuner & Suplie, 2005). This corresponds with the principles of ‘sustainable development’, which is the dominant rhetorical device of environmental governance. Sustainable development incorporates environmental, economic, and social dimensions. Relevant national policies and legislation, and other environmental agreements as they relate to national parks must also be accommodated.

The IUCN’s Southern African Sustainable Use Specialist Group (SASUSG) made suggestions for improving protected area outcomes by clarifying the principles underlying park management (Child, 2004a). The group suggests that:

Parks are areas set aside for the purpose of serving a local or national constituency;

Parks should meet the dual objectives of ecological conservation and the provision of socio-economic value by aiming to maximise socio-economic value within constraints imposed by ecosystems;

The ecological conservation objective for parks should be to ensure that ecosystem health and diversity thresholds remain intact and that these are measured systematically, accepting that in some cases other factors (e.g., single species) may take specific and overriding priority;

The socio-economic objective for parks should be to actively encourage the maximisation of benefits to society, and that any socially acceptable or humane use is acceptable provided that ecosystem health and diversity thresholds remain intact. This means that jobs, economic growth, and rural development are social goals every bit as legitimate to societies where rural poverty is common as are wilderness and science to North Americans; and,

That there are complex trade-offs between producing social value and distributional issues relating to who benefits from that value. All these must be addressed, in order to maximise the benefits provided by national parks. The purpose of the proposed model is to help decision-makers to better view the nation’s national park system as an asset portfolio and as a result improve the transparency and robustness of resource allocation decisions. Thus, the model’s objective is to rank national parks in terms of conservation importance, where conservation importance is determined by a combination of the biological, economic, and social net benefits associated with each national park.

(2) Constraints

The constraints confronting decision-makers who try to rank order national parks are largely related to reliable data, and the degree of subjectivity inherent in making environmental decisions.

The people charged with making annual resource allocation decisions amongst national parks are often not expert natural scientists, economists, or social scientists. They need a practical model that is easy to use and understand and is not excessively time-consuming to regularly update; furthermore, it should reduce complexity into a simple procedure. Once resources have been allocated to a national park, it is the responsibility of the park manager to distribute the money to different management activities. Guidance for doing this should be taken from the Management Plan for each park (and associated operational, corporate, and

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business plans). A park Management Plan that follows best practice identifies, describes, and prioritises the management actions required to achieve the management objectives (de la Harpe et al., 2004; Thomas & Middleton, 2003). Because many national park management agencies are also responsible for other types of protected area, it is important that the proposed model can be modified to accommodate these areas. Rather than attempting to rank the full range of a nation’s different protected areas types, the focus of this research will be to develop a model to rank a set of national parks only. National parks are the obvious and best choice because they are the most assimilated and accepted type of protected area worldwide11 (Ahmend et al., 2003), and have the clearest property rights (aside from Strict Nature Reserves, IUCN protected area category I, which have no direct human use element beyond a research capacity). In the future, the model could be tailored to include other types of protected area. This means that the ‘conservation importance’ criteria chosen will be in the context of areas managed as national parks, according to the IUCN definition, for ecosystem protection and recreation.

Sound management decisions should be based on quality data and information. It is impossible to predict the consequences of every decision, but use of the most relevant and recent information is a good start (De Lacy, Chapman, Whitmore, & Worboys, 2006). For the proposed model to be robust, the specific attributes selected must have associated data that are both meaningful and available. Some data are difficult and expensive to acquire. The availability of data also differs between nations (Table 2.10) with developed countries often having greater access to data. Signatories to the CBD are required to assess and monitor biological diversity. However, the CBD text provides no guidance for undertaking biodiversity assessments or monitoring; standards do not exist (Sheil, 2001). Fine-scale data (if collected over a large extent) can always be amalgamated to provide coarse-scale data, but not the reverse (Hartley & Kunin, 2003). The literature concerned with selecting areas for conservation assumes complete

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This is true for many developed countries, but one notable exception is Scotland where the national park movement failed to gain legislation due to factors including the strength of the landowning interest, rural depopulation, and concern for jobs in a depressed economy.

information about the incidence and survival of species. In practice, species incidence and survival at a locale is uncertain (Camm, Norman, Polasky, & Solow, 2002). Not all benefits and costs associated with conservation can be expressed in currency or other, non-monetary units (Hughey et al., 2003), so the particular rational decision framework constituting the model must deal competently with incommensurate data.

Table 2.10

Characteristics of Economic Values Associated with Protected Areas in Developed and Developing Countries

Type of Economic Value

Use Value Non-use Value

Direct1 Indirect2 Option3 Bequest4 Existence4

Developed Country

Ease of measurement

Easy Moderately easy Difficult Difficult Difficult

Available data Many Some Some Some Some

Realisable as income

Easy Moderately difficult

Difficult Difficult Difficult

Developing Country

Ease of measurement

Easy Difficult Difficult Very difficult Very difficult

Available data Some Few Very few None None

Realisable as income

Easy Moderately difficult

Difficult Difficult Difficult

1 _{Direct use values include those benefits derived from consumptive use of a protected area for activities such}

as harvesting, recreation, tourism, hunting, education, and research.

2 _{Indirect use values are benefits derived from the protected area, but not necessarily experienced on-site, for}

example, ecosystem services such as carbon sequestration, watershed protection, breeding habitat for migratory species, and climatic stabilisation.

3 _{Option values are derived from the option of using the protected area, either directly or indirectly, at some}

future time.

4 _{Bequest and existence values include spiritual, cultural, aesthetic, educational, scientific, peace, and}

therapeutic values.

Source: Adapted from Barnes (2003)

The data employed in a ranking model will be unavoidably biased. For example, biological databases are heavily biased by road-access research facilities and site- choice by researchers. It is easier for researchers to access survey areas by road, so areas that are relatively inaccessible are surveyed less often. However, it is now possible to analyse vegetation assemblages using recent satellite imagery in a Geographic Information System, which removes most of the bias associated with survey-based data (Vreugdenhil, Terborgh, Cleef, Sinitsyn, Boere et al., 2003).

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The ideal allocation of conservation funds is not simply a matter of giving the park with the most pristine contents the most money. Decision-makers must decide whether funds should be prioritised for areas with the worst environmental problems, or areas that have made some environmental improvements (Wu & Boggess, 1999). This means that some form of weighting procedure needs to be incorporated into the proposed model.

However, while any prioritising exercise involves a degree of subjectivity, value judgements are not necessarily bad (Bell & Martin, 1987; Hambler, 2004). Components of the natural environment merge in space and time, but humans divide nature into subjective sets of objects (Bell & Martin, 1987), so people with different perceptions of conservation importance will assign values in different ways (Hambler, 2004). Weights are inherent in conservation legislation and funding, but the weighting processes are usually subconscious. Biological components tend to be subjectively sorted into grades of importance; for example, threatened species are generally considered more important than unthreatened species, large species more important than small species, and vertebrates more important than invertebrates (Bell & Martin, 1987). Therefore, to be transparent, the proposed model must incorporate weighting processes that are explicit.

To accommodate the constraints outlined above, the rational decision-making framework on which the proposed model is built must meet the following parameters:

1. The biological, economic, and social attributes used to compare the national parks in a country’s national park network should be based on conservation best practice;

2. To be practical for PAMAs to apply, the attributes chosen depend on existing data sets that the agency can access;

3. To ensure fair comparisons, data must be available for all national parks in the country’s network. However, in some instances surrogate data could be used for some national parks if data about a specific attribute is available for the rest. Consequently, the decision-making framework must allow the use of surrogate data;

4. The decision-making framework chosen for the model must accommodate a large range of incommensurate data; and,

5. Because not all attributes will have the same importance in the allocation decision, the framework must allow attributes to be weighted.

(3) Alternatives

Alternatives are the different options for achieving the decision objective. In this research, the alternatives are the different national parks in the country’s national park network.

(4) Criteria

Suitable criteria against which to compare national parks in terms of conservation importance are discussed in Chapter Three, using the Convention on Biological Diversity’s biological, economic, and social attribute categories. The criteria employed in the proposed model are essentially indicators of the significance of different attributes of a national park. According to Margoluis and Salafsky (1998), a good indicator is:

Measurable – in either quantitative or qualitative terms;

Precisely defined – to ensure that the same data is collected over different geographic locations and by different people over time; and,

Consistent and sensitive – to accurately reflect changes in a condition over time.

Possible indicators for progress towards meeting the objectives for national park management as stipulated in the IUCN guidelines are outlined in Table 2.11. Some of these indicators will be suitable criteria for inclusion in the decision- making model.

(5) Evaluation

An evaluation can only occur once a formal rational decision framework has been selected in which to ‘build’ the proposed model, in accordance with the parameters outlined above. Existing frameworks are reviewed in Chapter Four, culminating in

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the selection of a Multiple Criteria Analysis method. The remainder of the thesis is concerned with the development, application, and suitability of the model.