Effective Ecological Monitoring

by Lindenmayer, David B.; Likens, Gene E.

• ISBN13: 9781849711449
• ISBN10: 1849711445
• Format: Hardcover
• Copyright: 2010-10-30
• Publisher: Routledge

Summary

Ecologists and managers of natural resources readily acknowledge the importance of long-term studies and monitoring for improved understanding and management of complex environmental systems. Long-term data are crucially important for providing baselines for evaluating environmental change. They are also fundamental for detecting and evaluating changes in ecosystem structure and function, and for evaluating response to disturbances such as climate change or pollution. Countless scientific articles, books, management plans and other documents have been written about the need to conduct long-term studies and monitoring. However, although there have undoubtedly been some highly successful long-term ecological studies and monitoring programs, there is a history of poorly planned and unfocused efforts that are either ineffective or fail completely. In this book, the authors outline some of the key pitfalls and deficiencies in ecological monitoring programs and long-term studies. They then describe some the features of monitoring programs and long-term studies that are essential to make them viable, using case studies such as those of Rothamsted (UK) and the Hubbard Brook Ecosystem Study (USA). Based upon their collective experience spanning 70 years in establishing long-term studies and natural resource monitoring programs, the authors propose a new approach, which they call Adaptive Monitoring, to resolve some of these problems underlying poorly planned and unfocused monitoring programs.

Author Biography

Professor David B. Lindenmayer is a Research Professor at The Australian National University. He has worked on biodiversity conservation issues for over 25 years and maintains large-scale, long-term projects throughout south-eastern Australia. He is a member of the Australian Academy of Science and has won numerous awards for his work, including the Eureka Prize for Environmental Research, the Whitley Award (three times), the Ecological Society Research Award, the DaimlerChrysler Award and the Australian Natural History Medal. He has published 25 books and over 550 scientific articles as part of his long-term research. Professor Gene E. Likens is Founding Director and President Emeritus of the Institute of Ecosystem Studies in Millbrook, New York, and now Distinguished Senior Scientist at the Cary Institute of Ecosystem Studies. His research focuses on the ecology and biogeochemistry of forest and aquatic ecosystems, primarily through long-term studies at the Hubbard Brook Experimental Forest. He is a member of the U.S. National Academy of Sciences, the American Philosophical Society, and is recipient of numerous awards, including the National Medal of Science, America's highest science honour. He has published 19 books and more than 500 scientific articles.

Table of Contents

Acknowledgments	p. vii
Preface	p. ix
Introduction	p. 1
Some of the ecological values and uses of long-term datasets	p. 3
Time until expression	p. 4
Use in simulation modelling	p. 6
Tests of ecological theory	p. 8
Surprises	p. 8
Poor record of long-term ecological monitoring	p. 8
Why we wrote this book	p. 11
References	p. 13
Why Monitoring Fails	p. 17
Characteristics of ineffective monitoring programs	p. 18
Passive, mindless and lacking questions	p. 18
Poor experimental design	p. 19
Snowed by a blizzard of ecological details	p. 20
Squabbles about what to monitor - 'It's not monitoring without the mayflies'	p. 21
Assumption that 'one-size-fits-all'	p. 26
Big machines that go 'bing'	p. 27
Disengagement	p. 28
Poor data management	p. 29
Breaches of data integrity	p. 30
Other factors contributing to ineffective monitoring programs	p. 32
Lack of funding - grant myopia	p. 32
The loss of a champion	p. 33
Out of nowhere	p. 34
Excessive bureaucracy	p. 34
Summary	p. 36
References	p. 37
What Makes Effective Long-Term Monitoring?	p. 53
Characteristics of effective monitoring programs	p. 53
Good questions and evolving questions	p. 54
The use of a conceptual model	p. 55
Selection of appropriate entities to measure	p. 57
Good design	p. 57
Well-developed partnerships	p. 59
Strong and dedicated leadership	p. 63
Ongoing funding	p. 67
Frequent use of data	p. 68
Scientific productivity	p. 69
Maintenance of data integrity and calibration of field techniques	p. 70
Little things matter a lot! Some 'tricks of the trade'	p. 70
Field transport	p. 70
Field staff	p. 71
Access to field sites	p. 71
Time in the field	p. 71
The Adaptive Monitoring framework	p. 72
A hypothetical example of how the Adaptive Monitoring framework works	p. 73
Adaptive Monitoring is a general and not a prescriptive framework	p. 74
Increased future role for Adaptive Monitoring	p. 75
Summary	p. 77
References	p. 79
The Problematic, the Effective and the Ugly - Some Case Studies	p. 87
The problematic	p. 89
PPBio Australasia	p. 89
The Alberta Biodiversity Monitoring Program (ABMP)	p. 92
EMAP	p. 99
NEON/TERN	p. 103
The effective	p. 108
Rothamsted	p. 108
Moreton Bay Waterways and Catchment Partnership	p. 111
The Hubbard Brook Ecosystem Study	p. 116
The Central Highlands of Victoria, south-eastern Australia	p. 124
The ugly	p. 137
Summary	p. 137
References	p. 138
The Upshot-Our General Conclusions	p. 147
Changes in culture needed to facilitate monitoring	p. 148
The academic culture and rewards systems	p. 148
Structure of organisations	p. 151
Intellectual property issues	p. 152
Funding	p. 152
Societal culture	p. 153
Good things that can come from non-question-based monitoring	p. 154
The next big challenge - integrating different kinds of monitoring	p. 155
Approaches to integrate data from question-driven monitoring and mandated monitoring	p. 161
References	p. 163
Index	p. 166
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