Biodiversity Conservation and Ecotourism: an investigation of linkages, mutual benefits and future opportunities
Biodiversity Series, Paper No. 5
Noel Preece and Penny van Oosterzee, Ecoz-Ecology Australia and David James, Ecoservices Pty Ltd
Department of the Environment, Sport and Territories, 1995
5. Strategic planning for NBE development
The ESD Working Group on Tourism observed that 'if tourism is to develop in an ecologically sustainable way, the current political and institutional fragmentation existing in landuse planning will need to be overcome'.
The authors of the present study concur with this observation. The review of strategic plans in Section 6 of this report reveals that the whole approach to tourism and nature based and ecotourism planning is fragmented, based on sometimes very different premises, reflecting a limited understanding of ecological sustainability, and led by misguided notions of the potentials and realities of NBE.
The Working Group recommended that regional planning should focus on integrated landuse plans based on ecological systems or biophysical regions. In the context of regional plans, strategic tourism plans should be developed by State and Territory Governments in collaboration with local governments and tourism industry bodies which would, amongst other things, identify ecologically appropriate areas for tourism use and development.
Approaches are discussed in sections 3.2, 3.5, and 7.3, using, in particular, bioregional planning, biogeographic regionalisation, and the James Cook regional planning approaches.
There are well established methods for assessing the economic implications of NBE tourism development and for conducting development planning. The usual framework is an input-output or multi-sectoral economic model, designed to be applied at regional, state or national level.
Multi-sectoral models vary in sophistication from fairly simple representations of the economic structure to large-scale simulation models with many policy and other variables and complex mathematical functions connecting them. It is important to note that the economic variables incorporated in the models are based only on market transactions and do not include broader community economic values such as existence, bequest, option and quasi-option values.
Tourism is not an identifiable sector in the standard classification of industries. Rather, it places demands on a wide range of industries which include food, beverages, accommodation, retail trade, transport, entertainment and personal services. Part of tourism expenditure consists of taxes and charges paid to governments such as airport taxes, park use fees for national parks, bed taxes and user charges paid to local councils for local services such as roads, waste disposal, water and sewerage.
Nature-based and ecotourism requires quite detailed expenditure data, as they comprise a special major component of the total tourism market. At present, no data set representing specific patterns of nature-based and ecotourism expenditure has been compiled. It should be a high priority in strategic planning for ecotourism development.
It is recommended that data on specific patterns of nature-based and ecotourism expenditure be compiled for Australia, based on the bioregional or regional planning models discussed in sections 3.2 and elsewhere.
One of the important applications of multi-sectoral models in evaluating the role of ecotourism is to make a baseline assessment of the current dependence of the economy – regional, state or national – on the ecotourism trade and of specific industries within the economy in terms of their total turnover, income and employment.
A second application is to predict the impacts of changes in the level and structure of the tourism trade, based on scenarios or forecasts of future trends in tourism markets.
A third application is to use the results of model simulations to formulate regional development strategies, with a focus on, among other things:
- Opportunities – both direct and indirect – for industry to benefit from a future expansion of tourism;
- Requirements for public and private investments in infrastructure;
- Demands for and availability of labour in specific skill categories;
- Fiscal implications for local and state government;
- Facilitation and coordination of industrial development associated with the tourism trade.
Extensive work has been undertaken on conventional regional economic models, but new directions are needed in integrating this kind of planning with bioregional planning.
To apply multi-sectoral modelling in strategic planning for ecotourism development the spatial location and boundaries of key bioregions must be matched with corresponding regional economic data. Market studies can be applied to determine likely growth rates for tourism in each region and the demands for specific kinds of goods, services and infrastructure associated with the tourist trade. Impacts on regional economies can then be predicted using standard modelling techniques. The results of model simulations can be used to assess the feasibility of development plans and environmental protection programs for each key bioregion and linked regional economy. An example of this methodology is the input-output analysis of public lands in the Upper North-East region of NSW recently conducted for the NSW Natural Resource Audit Council (results yet to be released).
The economic model is constructed from base year data indicating the flows of expenditure between sectors of the economy; sales to consumers, government and export markets; and expenditures on primary inputs to production such as labour and capital. The data must support the mathematical form of the model.
The simpler models are based on the assumption that consumer or other demands are pre-determined, that all inputs to each sector are required simultaneously in fixed proportions and that substitution of inputs does not occur. Such models predict the pattern of industrial activity that is required to meet the prescribed set of final demands.
The more complicated models allow for input substitution, changes in the pattern of demand and other more complex economic effects. The best-known example in Australia is the ORANI model which enables the analyst to predict the percentage changes that would occur in the economic system as a result of assumed changes in policy or market variables.
The next step is to assess the economic implications of nature-based and ecotourism. It is necessary to identify the pattern of expenditure for this segment of the tourism market. Data are required for key components of expenditure such as guided tours, transport, food, accommodation, photographic supplies, equipment and personal services, each associated with a particular economic sector.
Once these data have been collected it is possible to assess the dependence of the economy (as defined), specific industries, and the work force on the ecotourism market.
Although the methodology is straightforward, there are currently severe limitations on the availability of data, particularly on expenditure patterns associated with nature-based and ecotourism. Indeed, data on expenditure patterns for tourism in general are currently extremely limited. The expenditure components are usually limited to commercial accommodation and daily expenditure. More is known about the expenditure patterns of international visitors. Very little information is available on domestic visitors.
To conduct reliable assessments of the economic importance of nature-based and ecotourism, extensive primary data collection on expenditure patterns is needed. Such data should cover not only actual expenditure currently made by ecotourists, but also the kinds of natural areas, services or activities tourists would like to spend their money on in the future.
The discussion paper by the Victorian Department of Conservation and Environment (1992, p10) has noted that:
The infrastructure needs of the ecotourist differ from the mass market tourist primarily in requirements for the locality and style of accommodation, transport services, and access to sites. Ecotourists seek local vernacular accommodation that allows them to be close to the natural environment rather than removed from it. They seek designs and styles which expose them to the local culture, not cosmopolitan internationalised architecture.
The Victorian paper recognises that infrastructure needs include booking systems and infrastructure outside National Parks. Even where infrastructure developments are undertaken largely by the private sector, Governments can assist by identifying suitable sites, assisting developers with concept development, entering joint ventures such as information centres, and assisting with funding where public land is controlled by a local committee of management.
While the assessment by the Victorian Dept of Conservation and Environment may apply to a proportion of "ecotourists", it does not, in our opinion, apply to the much broader travelling public who seek nature-based experiences. People have broad tastes and preferences in accommodation and other infrastructure, and will avail themselves of their preferred style if it is available. In planning for infrastructure support, planners must consider the place where the developments are proposed, the range of infrastructure currently available, the ecological/environmental constraints and opportunities, the purpose and goals of the development, and the potential market and proposed activities for the area. The infrastructure must be appropriate to the area.
In formulating strategic development plans, it is important to distinguish the economic effects of expenditure directly attributable to tourism, which will tend to be ongoing, from effects that result from capital expenditure in supporting infrastructure, which may be only of a transitory nature. The various spheres of infrastructure investment should be identified, such as local, state and federal government and the private sector.
Care should be taken to avoid the 'boomtown' effect whereby regional production, income and employment increase rapidly during the capital construction phase, but decline when required facilities and infrastructure have been provided.
The provision of information on predicted patterns of development should assist industry to plan new development projects and help government agencies to plan for public investments in supporting infrastructure.
Multi-sectoral modelling has been applied at the national level by Adams and Parmenter (1993) using the ORANI model to assess the economic impacts of tourism on the national economy and State economies. ORANI-F is based on the original ORANI model developed by Dixon et al. (1983). It identifies 112 industries and 114 commodities.
The various steps undertaken in an ORANI analysis are shown in Figure 5.1. A baseline scenario is first specified, with appropriate assumptions about macro-economic variables, policy variables, international variables and variables affecting production and supply.
These projections are then translated into projections for State economies using the ORANI Regional Equation System (ORES). Details are then determined for economic variables at the State level such as Gross State Product, industry outputs, employment and income.
The system is then 'shocked' and the model is re-run to determine changes in the economic system, identified as percentage rates of change in average annual growth rates for the economic variables under consideration.
Adams and Parmenter took tourism expenditure as one kind of 'shock' and used the method outlined to assess the economic implications of international tourism for the national and State economies of Australia.
Source: Adams and Pamenter (1993)
Expenditure patterns by international tourists at the national level were derived from various data sources, using 1987-88 as a base year. The forecast period was assumed to be 1988-89 to 1994-95. Additional tourism attributable to international tourists was assumed to generate, in that period, 10 per cent a year more expenditure by tourists in each State on domestically produced goods and services. The composition of tourism expenditure within each State was assumed to remain the same as in 1987-88. Excess capacity was assumed in the accommodation and entertainment industries.
The results for the national economy indicated that tourism-dependent industries such as air transport, communications, entertainment and leisure would enjoy higher than average growth prospects. Good prospects were also predicted for suppliers of investment goods such as aircraft, cement, ready mixed concrete, structural metal products and other construction.
After applying ORES the economic effects of additional tourism growth were determined for the State economies. Some local industries within each State – those catering directly for tourists – benefit directly from the increased tourist trade, whereas others benefit through multiplier effects and linkages with the national economy. The effects of additional tourism growth on local industries are shown in Table 5.1.
According to the model simulations, Victoria would gain most from an increase in international tourism, followed by New South Wales, South Australia, Tasmania, Queensland and Western Australia. Queensland has the greatest gains in terms of direct effects of increased tourism but gains little, relative to the other States in terms of multiplier effects, because of its lack of national industries, particularly air transport.
The results of these ORANI simulations must be considered in the context of the assumptions made, especially in relation to the industrial structure of the economy and the tourism expenditure patterns in 1987-88. Simulations conducted with more recent data would undoubtedly yield a different set of results reflecting the efforts made by individual States since 1987-88 to change their industrial structure, capture a greater proportion of the tourism trade and develop supporting industries.
Multi-sectoral modelling can be applied at a more detailed level to assess the economic impacts of tourism at the regional scale. An excellent example is the study by Driml (1987) on economic impacts of activities on the Great Barrier Reef.
Driml used simple input-output modelling to assess the economic impacts of island resorts, charter boats, commercial fishing, recreational fishing, island camping and research on the regional economies of Cairns, Townsville, McKay and Rockhampton. The regional input-output models were constructed by Morison et al. (1982) for the base year of 1978-79.
Estimated total outputs of by each sector in 1981-82 are reproduced in Table 5.2. Total output, income and employment multipliers for each sector and region are shown in graphical form in Figure 5.2. The multipliers are Type II and incorporate induced consumption effects as well as indirect production effects. The initial and flow-on effects of these activities on the regional economies are shown in Tables 5.3, 5.4 and 5.5. The results provide valuable insights into the dependence of each region on the activities and the ways in which changes in these activities can be expected to affect the structure of the regional economy.
A similar study is currently being conducted for the NSW Natural Resources Audit Council for the North-East Region of the State, assessing the structural significance of activities in the region associated with public lands, including recreation and tourism.
More sophisticated models can also be applied at a local or regional scale to assess the economic impacts of tourism development. The ORANI model, for example, has been applied by Knapman et al. (1991) to assess the effects of tourism in Kakadu National Park on the Northern Territory economy. The particular version of the ORANI used was ORANI-NT.
|Local industry||NSW||VIC||QLD||SA||WA||TAS||All states|
|9||Services to agriculture||-0.0860||-0.0799||-0.1664||-0.0885||-0.1095||-0.0821||-0.1611|
|23||T||Bread, cakes and biscuits||0.2647||0.2350||0.3414||0.3032||0.3070||0.2522||0.1540|
|26||T||Soft drinks, cordials||0.2581||0.2347||0.3124||0.2857||0.2808||0.2250||0.1515|
|27||T||Beer and malt||0.1160||0.1225||0.0865||0.1097||0.0560||0.0566||0.0573|
|60||Ready mixed concrete||0.0440||0.0904||-0.0849||-0.0067||-0.1280||-0.0882||0.0822|
|86||Water, sewage, drainage||0.0526||0.0836||-0.0655||0.0104||-0.0970||-0.0548||-0.0006|
|100||T||Investment and services||0.0505||0.0780||-0.0551||0.0049||-0.1000||-0.0471||0.0083|
|102||T||Other business services||0.0724||0.0904||-0.0238||0.0233||-0.0823||-0.0335||0.0373|
|103||Ownership of dwellings||0.0669||0.1163||-0.1001||0.0066||-0.1431||-0.0930||0.0064|
Note: Industries marked with a T produce goods and services directly purchased by overseas tourists in each State
Source: Adams and Parmenters (1993).
|Cairns region||Townsville region||Mackay region||Rockhampton region||Total output|
All values are A$ millions
na Not applicable/available
Source: Driml (1987).
Note: rounding errors occur
Source: Driml (1987).
Note: rounding errors occur
Source: Driml (1987).
Note: rounding errors occur
Source: Driml (1987).
The way the ORANI-NT model works is explained by Knapman et al. as follows:
It constructs the economy as a system of interrelated industries or sectors; incorporates orthodox microeconomic theory in order to explain the behaviour of economic entities, including their responses to random or policy shocks to the economy; and computes equilibrium solutions for different economic environments and shocks chosen by the analyst. Solutions show how, in the new equilibria, macroeconomic aggregates and market-clearing prices and quantities for all product and input markets differ from what they otherwise would have been. ORANI-NT is thus a comparative statics model. It is also usually short run in the sense that investment does not augment capital stocks during the (approximately) two year adjustment to the new equilibrium. (p 2)
The study noted that the tourism sector in the Northern Territory, defined to include tourist and recreational facilities, accommodation, hotels, clubs and restaurants, employed 7 per cent of the Northern Territory work force in the late 1980s with an additional 6.5 per cent in other sectors servicing tourists.
During the 1980s the number of visitor nights in hotels and motels grew at an annual average rate of 12.3 per cent, and in caravan parks 22.7 per cent.
Kakadu National Park was estimated to attract 230,000 visitors by 1988-89 or 27 per cent of all visitors to the Northern Territory. Total investment in hotel/motel accommodation in the Park was estimated to be $45 million.
The allocation of expenditure by tourists within the Park on different expenditure categories was identified from a survey undertaken by Knapman in 1990 involving 647 domestic visitor groups (1662people) and 187 international visitor groups (383people) (Knapman 1990). The results are reproduced in Table 5.6.
Knapman et al. obtained estimates of total expenditure within the Park from all sources for 1990-91 (see Table 5.7)
|Accommodation/camping fees||44 010||11 724|
|Meals||24 831||8 027|
|Other food/beverages||17 529||2 629|
|Gifts||17 185||2 557|
|Petrol/vehicle costs||35 836||10 099|
|Scenic flights||19 598||2 480|
|Bus & 4WD trips||6 525||1 555|
|Water cruises||25 343||4 859|
|Only total given||5 020||588|
|Total||199 723||45 080|
Sources: Knapman (1990, p15)
|ANPWS (1989-90) budget allocation)|
|Work in progress Kakadu highway||4.95|
|Work in progress Arnhem highway||0.33|
|New works Kakadu highway||2.58*|
|New works Jabiru aerodrome||0.20|
* This figure is 50 per cent of the 1990-91 allocation.
Sources: Knapman 1990; ANPWS; NTG 1990, Budget Paper No. 5
Knapman et al. obtained estimates of total expenditure within the Park from all sources for 1990-91 (see Table 5.7).
Tourism expenditure within the Park was estimated at $30 per person per day for domestic visitors and $39 for international visitors. A ratio of 80:20 was assumed for domestic and international visitors, with an average stay of four days for domestic and three for international. Applying these assumptions to the 250,000 visitors in 1990-91 gave an estimate of $30 million for total visitor expenditure.
Other expenditure in the Park included $10.5 million by the Australian National Parks and Wildlife Service and $8 million in capital expenditure by the Northern Territory Government. Total expenditure within the Park in 1990-91 was thus $48 million.
Expenditures associated with Kakadu were translated into changes in output by seven industries: No 89 (Residential Construction), No 90 (Other Construction), No 92 (Retail Trade), No 95 (Road Transport), No 106 (Public Administration), No 111 (Entertainment and Leisure) and No 112 (Restaurants and Hotels).
Several simulations were undertaken with the ORANI-NT model. Simulation A was designed to determine the importance of tourism in Kakadu to the Northern Territory economy. Simulations B and C assessed the impacts of a 10 per cent decrease and 10 per cent increase respectively in tourists visiting Kakadu. Simulation D assessed the impacts of new capital works associated with Kakadu, equivalent to a 10 per cent increase in the total for the Northern Territory. Increased output of hotel construction and workers accommodation was simulated in terms of industry No 89 and roadworks etc. in terms of industry No 90.
The results of the simulations indicated that real gross product for the Northern Territory was 2.5 per cent higher and employment 3.64 per cent higher because of Kakadu. A 10 per cent change in visitors to Kakadu would change gross product and employment by less than half a per cent. Increased capital construction by industries No 89 and 90 would boost real gross product by 1.15 and 1.18 per cent respectively, and employment by 0.84 and 1.42 per cent.
The model indicates that Kakadu is responsible for approximately 0.5 per cent of revenue raised locally by the Northern Territory Government.
The significance of Kakadu for individual sectors of the Northern Territory economy, demonstrated by Simulation A, are shown in Table 5.8.
|ORANI No.||Industry||% change in output|
|38||Other textile products||5.79|
|45||Furniture and mattresses||3.03|
|49||Publishing and printing||2.47|
|50||Paper stationery etc||3.75|
|60||Clay products and refractories||3.20|
|62||Ready mixed concrete||2.15|
|67||Structural metal products||2.01|
|69||Other metal products||3.88|
|70||Motor vehicles & parts and transport equipment n.e.c.||3.01|
|74||Photographic,professional and scientific equipment||3.49|
|76||Refrigerators, h/hold appl. and water heaters||5.70|
|84||Signs and advertising||6.37|
|88||Water, sewerage, drainage||3.16|
|102||Investment & services to investment & finance||4.22|
|104||Other business services||5.20|
|111||Entertainment and recreation services||31.69|
|112||Restaurants, hotels and clubs||30.03|
|15||Nonferrous metal ores||-0.37|
|19||Services to mining||-0.99|
|66||Basic nonferrous metals and products||-1.06|
Source: Knapman et al. (1991)
The ORANI model has recently undergone further development and is now known as the MONASH model. As part of this development it is being extended to major economic regions in Australia. Regional economic impact analysis and regional planning associated with ecotourism could clearly be facilitated by applying the MONASH model.
These examples demonstrate that the analytical tools are available to conduct detailed economic planning studies of regional development programs based on the tourist trade. Innovative approaches are required to apply these methods in the context of major bioregions and natural areas acting as attractors of tourists and domestic visitors.
It is recommended that primary research be undertaken by governments and the tourism industry to develop regional multi-sectoral models matched to key bioregions throughout Australia. By combining such models with detailed market research of ecotourism profiles and expenditure patterns, a sound basis for regional development planning will be established.