Any scheme that aims to save nature by paying for its ecosystem services has to begin by measuring and monitorin those services. Not all such methods, however, are created equal, say David Lindenmayer and Gene Likens in “Effective Ecological Monitoring." Through case studies and analyses, they illustrate the keys for successful ecosystem monitoring that forms the foundation for effective mitigation.
Any scheme that aims to save nature by paying for its ecosystem services has to begin by measuring and monitorin those services. Not all such methods, however, are created equal, say David Lindenmayer and Gene Likens in “Effective Ecological Monitoring.” Through case studies and analyses, they illustrate the keys for successful ecosystem monitoring that forms the foundation for effective mitigation.
11 November 2010 | David B. Lindenmayer, a Research Professor at The Australian National University in Canberra and Gene E. Likens, an ecologist best known for discovering acid rain in North America, provide a pungent perspective on the state of long-term monitoring programs designed to identify significant changes in the natural environment.
In their book, Effective Ecological Monitoring, case studies spotlight why some monitoring programs fail while others succeed . The book, just released in soft cover, provides an essential tool for understanding, protecting and preserving the earth’s ecosystems.
Good intentions are not enough
For a first-hand look at an environmental monitoring program that falls short, Lindenmayer and Likens point to the Program for Planned Biodiversity and Ecosystem Research. This Australia-based ecological initiative is designed to provide long-term monitoring of biodiversity indicators including those related to climate change. To assess changes over time. The monitoring program breaks a network of land and sea plots throughout major ecoregions into equally-spaced grids. The authors acknowledge the program’s good intentions and attributes. These include well-developed partnerships and limited bureaucracy. The cost of monitoring is also relatively inexpensive.
But the program’s flaws likely outweigh its positive aspects, the authors write, and will probably decrease its effectiveness and relevance. The monitoring program’s mission contains few well-defined questions. It lacks a conceptual model. This could prevent information gathered from explaining underlying mechanisms. There may be flaws in the program’s experimental design. And the program’s standardized format puts results in a “one size fits all” format that could limit the relevance of measurements.
46 years and going strong
The Hubbard Brook Ecosystem Study, in contrast, is a case study for success, say Lindenmayor and Likens. Researchers at Dartmouth College and the US Forest Service initiated this long-term monitoring program in 1963 in the Hubbard Brook Experimental Forest of New Hampshire, USA. They use it to study the ecological, hydrological and biogeochemical processes of forest and aquatic ecosystems. Many attributes contribute to the study’s success, the authors say. For example, since inception the program has included specific objectives to evaluate critical relationships between mineral cycles and hydrology. It outlined basic approaches including the need to relate scientific research to land and water-management issues. It formed strong partnerships whose focus included an on-the-ground field presence and careful calibration of field equipment for monitoring.
Lindenmayor and Likens say that although the study is beginning to suffer from increasing levels of bureaucracy it has overcame many challenges in its 46 years, including loss of key leaders and remains effective today.
Checklist for Winners
Case studies such as these provide a checklist for success – and for failure.
Good monitoring programs such as the Hubbard Brook Ecosystem Study share certain key characteristics, the authors write. They establish good and evolving questions, use a conceptual model, select appropriate entities to measure, and provide a good design, well-developed partnerships, strong and dedicated leadership, ongoing funding, frequent use of data, scientific productivity, maintenance of data integrity and calibration of field techniques.
Several small factors also contribute greatly to project success, they say. These include reliable field transport availability, motivated field staff, access to remote field sites and significant time dedicated in the field.
Recipe for failure
Failure, the authors write, can often be prevented. But at times it is out of the program designers’ control.
Programs, such as the Australian study, failed because of insufficient questions and poor experimental design that resulted, Lindenmayer and Likens write, from poor planning and a lack of focus. This often results in disagreements over what to monitor, overemphasis on infrastructure, disengagement of the scientific community, poor data management and breaches of long-term data integrity.
Even well-designed and implemented programs also fail at times because of factors outside the designers’ control. These include lack of funding, loss of a key person, unexpected problems and excess bureaucracy.
Adaptability breeds success
One of the book’s strongest assets is the authors’ Adaptive Monitoring framework. This framework starts with well-developed questions concerning what should be monitored and how it should be done. It is furthered by experimental design, data collection, data analysis and ongoing interpretation. It is adapted to individual needs And it views monitoring programs philosophically. Overall, Adaptive Monitoring aims to guide programs away from common deficiencies and toward success.
The Challenge of Integration
The authors offer powerful insights into future challenges for ecological monitoring while identifying conditions necessary for significant improvements to occur.
They claim, paradoxically, that the western cultures that often undertake long-term ecological monitoring efforts often prove ill suited for carrying them out. This, they say, is because of the cultures’ often short-term focus. Another difficulty is the challenge of integrating different monitoring approaches across different levels of implementation, such as state and national governments, academic bodies and organizational flows. Lindenmayer and Likens admit they are unsure how to rectify such deep-rooted cultural and integrational issues.
Of Books and Bias
Effective Ecological Monitoring does not touch on the particular importance of or difficulty in carrying out monitoring programs in developing countries; it includes surprisingly few examples and case studies from outside the developed world. The authors admit their bias upfront in the book’s prelude. Accordingly, the case studies focus solely on Australia, North America and the United Kingdom. The authors would have done well, however, to note their reasons for this omission.
A Call to Action
Lindenmayer and Likens’ adaptive monitoring tool will become increasingly important as we fully grasp the importance of ecological monitoring. It provides essential analyses required to understand environmental changes caused by human interactions with nature. And it provides the basis for determining how to mitigate these results. Adaptive monitoring becomes particularly relevant when assessing the long-term effects of climate change, acid rain, increased ozone levels and natural disasters. And the success, in turn, of schemes involving payments for ecosystem services including carbon sequestration and wetland preservation depend heavily on effective monitoring. They could greatly benefit from such a framework.
Effective Ecological Monitoring offers a well-written analysis of issues facing ecological monitoring programs. Its call to action for improving monitoring programs clearly outlines key issues yet to be resolved and can clearly serve as the foundation for future exploration. It is sure to resonate not only with scientists but also with policymakers, academics and ecosystem service professionals who can use its suggestions to improve existing monitoring programs and implement new ones.
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