(much of this section was based on notes provided by Mike Runge - USGS)

If your goal is to evaluate, regulate, guide, or investigate your land or wildlife management actions then you will want to collect data in a way to both monitor the success of those actions and to help you learn how to improve your management over time. Long-term monitoring programs are usually unsuitable for those specific kinds of objectives. If your primary interest is in tracking the long-term status of a species or a group of species within an area (e.g. long-term trends of birds, frogs, salamanders) rather than directly addressing management concerns or issues regarding the cause of changes then please see our sections on status monitoring.

There are 2 main approaches to addressing how management actions affect wildlife populations:

1. Traditional short-term research project.
2. Adaptive management approach.

There are many ways to use research and adaptive management to investigate management activities. Some of the factors that affect the approach you would take include:

• Your budget
• The number of sites you have available for controls/management/manipulation
• The species being studied
• The questions being addressed
• The weather/climate/personnel conditions that determine what can be accomplished within a year.

Usually either approach requires outside financial input as the costs of such an approach exceed base funds.

While both approaches investigate the same thing, there are differences to consider. Most research projects have a defined set of money available only for a short period of time. Any manipulation of habitats are done once on a discrete set of plots and when the study if competed there is no additional follow-up unless a new study is begun. Adaptive management is usually accomplished over a series of years. The same plots are used over and over with management actions being altered over time as results are analyzed and those findings plugged back into the next round of management and surveys.

Because of the complexity, cost, and individual nature of each question and approach to answering that question we don't go into how to establish a research project. Because adaptive management is a relatively new tool, we do spend some time below explaining the concept.

Adaptive Management

Monitoring integrated with management is often termed adaptive management. Management is adaptive when management actions are measured and evaluated before and after they occur and the resulting information is then used to refine the next round of management questions. Consequently, adaptive management can be thought of as a hybrid between pure research and seat-of-the-pants management. Within this system, monitoring is incorporated to collect data that will gauge the relative success of the management actions.

It is important to note that once management ceases or the need for additional information is complete, then the need for monitoring also ceases. This is in contrast with status monitoring, where the purpose is to obtain a the long-term picture of population changes on a particular piece of land. In status monitoring, the need for monitoring is constant and only disappears when collecting information on the population is no longer conservation interest.

To better illustrate the differences between status monitoring and adaptive management, we have put together a series of examples.

To be most effective, adaptive management should be proactive, not reactive. The ideal is to anticipate the ecological and management questions that are important to the conservation of the animals in your area and structure your management and monitoring actions around those. A manager should ask:

Please note that the goal of adaptive management is not learning for learning's sake. The goal of adaptive management is exactly the same as that of the management action itself (i.e. changing habitat or wildlife populations in some way). The subtlety is that adaptive management actively incorporates feedback and learning into the process so that you learn from your management actions and can better and more quickly adjust those actions over time. Under adaptive management, monitoring is conducted to improve your management, not to simply gather information about the status of your animal populations.

Learn more about why adaptive management and the associated monitoring is useful to a wildlife manager.

In many ways adaptive management formalizes the wisdom of a land manager with clear resource management ideas. Land managers in touch with the wildlife and the land is created not by schooling, but years of direct experience. They have spent time observing animals on the land they are managing, integrating how their populations respond to each year’s changes in farming, impoundment, mowing, and forestry practices as they weigh, adapt and alter what they do to achieve their management goals. For those unfortunate not to have the wise manager, then adaptive management provides a framework for ongoing management that formalizes and transcribes that same wisdom into something that future managers can easily use and carry on.

Adaptive management is not a cure-all, it is a new, much talked-about approach that many speak of, but few have implemented. There are situations where it works well and others where the process gains you little information.

Places where adaptive management works well:

• The targeted species management goals are simple and clear
• The management options are few, likely to remain the same for a long period of time, under your complete control, and likely to produce distinct and clear results.
• The relationship between management option and species population is straightforward.
• There is opportunity for a large number of treatment sites
• Management results are apparent within a year or less
• Management actions can occur on a number of sites at the same time
• There are more than 5 plots for each treatment action available
• Monitoring the results takes little time
• Statisticians are available to design the program and analyze data
• Several groups in a region can collaborate
• Resources for implementing the program are available

Situations where adaptive management works less well.

• Multiple species management goals (>2)
• The differences in management options are small, could change, often not completely under your control, and may not result in large differences
• The number of sites available for management is limited
• The results of treatments may not be apparent for several years (e.g., many forestry practices)
• Monitoring the results with the appropriate precision is time consuming
• Statistical help is not available or too expensive
• Extra money is not available

Unfortunately, because of the variety of species, circumstances, approaches, and situations being managed, we cannot do more than give you a very broad outline of what adaptive management can do as an approach to making your management more effective. If your management problems appear to lend themselves to an adaptive management approach, we highly recommend the following references (it is also advisable to discuss your needs with a population ecologist familiar with adaptive management).

Short List

Kendall, WL. 2001. Using models to facilitate complex decisions. Pages 147-170 in TM Shenk and AB Franklin, eds. Modeling in Natural Resource Management, Island Press, Washington, DC, USA.

Lancia, RA, et al. 1996. ARM! For the future: adaptive resource management in the wildlife profession. Wildlife Society Bulletin 24(3):436-442.

Lee, KN. 1993. Compass and Gyroscope. Island Press, Washington, D.C., USA.

Walters, CJ, and CS Holling. 1990. Large-scale management experiments and learning by doing. Ecology 71:2060-68.

Williams, BK. 1997. Approaches to the management of waterfowl under uncertainty. Wildlife Society Bulletin 25(3):714-720.

Longer List

Bellman, R. 1957. Dynamic Programming. Princeton University Press, Princeton, N.J., USA.

Chamberlin, TC. 1890. The method of multiple working hypotheses. Science (old series) 15:92. Reprinted in 1965 in Science 148:754-759.

Drechsler, M. 2000. A model-based decision aid for species protection under uncertainty. Biological Conservation 94:23-30.

Gunderson, LH, CS Holling, and SS Light, eds. 1995. Barriers and Bridges to the Renewal of Ecosystems and Institutions. Columbia University Press, New York, NY, USA.

Harwood, J. 2000. Risk assessment and decision analysis in conservation. Biological Conservation 95:219-226.

Hilborn, R. 1987. Living with uncertainty in resource management. N. Amer. Journal of Fisheries Management 7:1-5.

Hilborn, R, and CJ Walters. 1992. Quantitative Fisheries Stock Assessment: Choice, Dynamics, and Uncertainty. Chapman and Hall, New York, NY.

Holling, CS. 1978. Adaptive Environmental Assessment and Management. John Wiley & Sons, Chichester, UK.

Johnson, FA, CT Moore, WL Kendall, JA Dubovsky, DF Caithamer, JR Kelley, Jr., and BK Williams. 1997. Uncertainty and the management of mallard harvests. Journal of Wildlife Management 61(1):202-216.

Lee, KN. 1999. Appraising adaptive management. Conservation Ecology 3(2):3. http://www.consecol.org/Journal/vol3/iss2/art3/index.html

Lubow, BC. 1996. Optimal translocation strategies for enhancing stochastic metapopulation viability. Ecological Applications 6(4):1268-1280.

Ludwig, D, R Hilborn, and CJ Walters. 1993. Uncertainty, resource exploitation, and conservation: lessons from history. Science 260:17, 36.

Milner-Gulland, EJ. 1997. A stochastic dynamic programming model for the management of the saiga antelope. Ecological Applications 7(1):130–142.

Nichols, JD. 2001. Using models in the conduct of science and management of natural resources. Pages 11-34 in TM Shenk and AB Franklin, eds. Modeling in Natural Resource Management, Island Press, Washington, DC.

Nichols, JD, FA Johnson, and BK Williams. 1995. Managing North American waterfowl in the face of uncertainty. Annual Review of Ecology and Systematics 26:177-199.

Parma, AM, and NCEAS Working Group on Population Management. 1998. What can adaptive management do for our fish, forests, food, and biodiversity? Integrative Biology 1(1):16-26.

Platt, JR. 1964. Strong inference. Science 146:347-353.

Richards, SA, HP Possingham, and J Tizard. 1999. Optimal fire management for maintaining community diversity. Ecological Applications 9(3):880-892.

Shea, K. 1998. Management of populations in conservation, harvesting and control. Trends in Ecology & Evolution 13(9):371-375.

Shea, K. and HP Possingham. 2000. Optimal release strategies for biological control agents: an application of stochastic dynamic programming to population management. Journal of Applied Ecology 37:77-86.

Walters, CJ, and R Hilborn. 1978. Ecological optimization and adaptive management. Annual Review of Ecology and Systematics 9:157-88.

Walters, CJ. 1986. Adaptive Management of Renewable Resources. MacMillian, New York, NY.

Watt, KEF. 1988. A revolutionary approach to resource management. Ecology 69: 878-879.

Williams, BK. 1982. Optimal stochastic control in natural resource management: framework and examples. Ecological Modelling 16:275-297.

Williams, BK, and FA Johnson. 1995. Adaptive management and the regulation of waterfowl harvests. Wildlife Society Bulletin 23(3):430-436.