Statistics and Environmental Policy: Case Studies from Long-Term Environmental Monitoring Data

  1. Gregory R. Bock Organizer and
  2. Jamie A. Goode
  1. Rob Goudey1 and
  2. Geoff Laslett2

Published Online: 28 SEP 2007

DOI: 10.1002/9780470515600.ch8

Novartis Foundation Symposium 220 - Environmental Statistics: Analysing Data for Environmental Policy

Novartis Foundation Symposium 220 - Environmental Statistics: Analysing Data for Environmental Policy

How to Cite

Goudey, R. and Laslett, G. (2007) Statistics and Environmental Policy: Case Studies from Long-Term Environmental Monitoring Data, in Novartis Foundation Symposium 220 - Environmental Statistics: Analysing Data for Environmental Policy (eds G. R. Bock and J. A. Goode), John Wiley & Sons, Ltd., Chichester, UK. doi: 10.1002/9780470515600.ch8

Author Information

  1. 1

    Freshwater Sciences, Environment Protection Authority, 27 Francis Street, Melbourne, Victoria 3000, Australia

  2. 2

    CSIRO Mathematical and Information Sciences, Private Bag 10, Clayton South MDC, Victoria 3169, Australia

Publication History

  1. Published Online: 28 SEP 2007

ISBN Information

Print ISBN: 9780471985402

Online ISBN: 9780470515600

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Keywords:

  • statistics;
  • environmental policy;
  • environmental monitoring data;
  • victorian epa monitoring programs;
  • bacterial network sites

Summary

Environmental objectives are statements of policy which are intended to be assessed using information from a monitoring program. An environmental monitoring program has to be adequate in its quality and quantity of data so that the environmental objectives can be assessed. Also, the resulting data should be able to contribute information towards decisions to modify policy at a later time if desirable. However, monitoring programs can fail to return satisfactory information for policymakers because future statistical needs have not been anticipated, potential confounding factors were not considered, or sampling protocols did not specify suitable randomization. A key intermediate role exists for the use of statistical inference in providing a logical framework for using monitoring data to test hypotheses about fulfillment of environmental objectives. The undertaking of a statistical inferential approach to monitoring design can result in data which are more general in their interpretation and, thus, more useful as input to policy development and review. Some case studies from the Victorian EPA monitoring programs will be presented to illustrate these points.