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Assessing recreational benefits as an economic indicator for an industrial harbour report card
- Windle, Jill, Rolfe, John, Pascoe, Sean
- Ecological indicators 2017 v.80 pp. 224-231
- aquatic ecosystems, economic indicators, economic valuation, employment, environmental factors, monitoring, recreation, Queensland
- Industrial harbours are a complex interface between environmental, economic and social systems. Trying to manage the social and economic needs of the community while maintaining the integrity of environmental ecosystems is complicated, as is the identification and evaluation of the various factors that underpin the drivers of economic, community and resource condition. An increasingly popular strategy to deal with the identification and evaluation challenges in complex human-environmental systems is to use a report card system which can be used as a summary assessment tool to monitor the health of aquatic ecosystems. To date though these have largely focused on environmental factors, and it is only very recently that attempts are being made to include social, cultural and economic indicators. There has been limited consensus in the selection of social and economic indicators applied in different aquatic report cards but as recreation is such an important activity, typically some measure of recreation benefit is included. However, there has been no commonality in the measures applied to assess its performance as an economic indicator.This paper is focused on the assessment of recreational benefits as an indicator of economic value in the report card for Gladstone Harbour in Queensland, Australia. It is the first aquatic health report card to include an assessment of the nonmarket value of recreation which makes it a more comprehensive indicator of economic value compared to other report cards based on measures of employment, participation or expenditure. There have now been three consecutive years of reporting (2014–2016) of the Gladstone Harbour report card, and the results indicate that the recreation index appears to be effective in monitoring changes over time.