Adaptive management

Adaptive management (AM), also known as adaptive resource management (ARM), is a structured, iterative process of optimal decision making in the face of uncertainty, with an aim to reducing uncertainty over time via system monitoring. In this way, decision making simultaneously maximizes one or more resource objectives and, either passively or actively, accrues information needed to improve future management. AM is often characterized as "learning by doing."

History

'Adaptive environmental assessment and management' was the original name given to this approach which was developed by the ecologists C.S. Holling and Carl J. Walters at the University of British Columbia, Canada in the 1970s. The approach was further developed at the [http://www.iiasa.ac.at/ International Institute for Applied Systems Analysis (IIASA)] in Vienna, Austria, while C.S. Holling was director of the Institute. Adaptive management has probably been most frequently applied in Australia and North America, initially applied in fishery management, but received more broad application in the 1990s and 2000s. One of the most successful applications of adaptive management has been in the area of waterfowl harvest management in North America, most notably for the mallard (Johnson et al., 1993; Nichols et al., 2007).

Explanation

Adaptive management can be considered either passive or active. Passive adaptive management begins by using predictive modeling based on present knowledge to inform management decisions. As new knowledge is gained, the models are updated and management decisions adapted accordingly.

Active adaptive management, on the other hand, involves changing management strategies altogether in order to test completely new hypotheses. So while the goal of passive adaptive management is to improve existing management approaches, the goal of active adaptive management is to learn by experimentation in order to determine the best management strategy.

Key features of both passive and active adaptive management are:
*Iterative decision-making (evaluating results and adjusting actions on the basis of what has been learned)
*Feedback between monitoring and decisions (learning)
*Explicit characterization of system uncertainty through multi-model inference
*Bayesian inference
*Embracing risk and uncertainty as a way of building understanding

Adaptive management is particularly applicable for systems in which learning via experimentation is impractical. However, any one of five process failures can seriously compromise effective adaptive management decision making (Elzinga et al. 1998):
*The monitoring is never completed.
*The monitoring data are not analyzed.
*The analyzed results are not conclusive.
*The analyzed results are interesting but never reach decision makers.
*The decision makers do not use the results because of internal or external factors.

Because adaptive management is used to make decisions regarding the management of valuable natural resources, it directly affects (and is affected by) public policy and politics.

Key books

*cite book | author = Williams, Byron K.; Robert C. Szaro; Carl D. Shapiro | year = 2007 | title = Adaptive Management: The U.S. Department of the Interior Technical Guide | publisher = US Department of the Interior | id = ISBN 1-411-31760-2
*cite book | last = Holling | first = C. S. (ed.) | authorlink = C. S. Holling | year = 1978 | title = Adaptive Environmental Assessment and Management | publisher = Wiley | location = Chichester | id = ISBN 0-471-99632-7
*cite book | last = Lee | first = Kai N. | year = 1993 | title = Compass and Gyroscope: Integrating Science and Politics for the Environment | publisher = Island Press | location = Washington, D.C. | id = ISBN 1-55963-197-X
*cite book | last = Walters | first = Carl | year = 1986 | title = Adaptive Management of Renewable Resources | publisher = Macmillan | location = New York | id = ISBN 0-02-947970-3

Other references

*cite journal | author =Johnson, F.A.; Williams, B.K.; Nichols, J.D.; Hines, J.El; Kendall, W.L.; Smith, G.W.; and Caithamer, D.F. | year = 1993 | title = "Developing an adaptive management strategy for harvesting waterfowl in North America" | journal =Trans N Am Wildl Nat Resour Conf | issue = 58 | pages = 565–583

*cite journal | author = Nichols, J.D.; Runge, M.C.; Johnson, F.A.; and Williams, B.K. | year = 2007 | title = "Adaptive harvest management of North American waterfowl populations: a brief history and future prospects" | journal = Journal of Ornithology | issue = 148 | url = http://www.springerlink.com/content/0505n125n8g223u6/ | doi = 10.1007/s10336-007-0256-8 | volume = 148 | pages = 343

*cite journal | author = Nichols, J.D.; and Johnson, F.A.; and Williams, B.K. | year = 1995 | title = Managing North American waterfowl in the face of uncertainty | journal = Annu. Rev. Ecol. Syst. | volume = 26 | pages = 177–199 | doi = 10.1146/annurev.es.26.110195.001141

*cite journal | author = Johnson, F.A.; and Williams, B.K. | year = 1999 | title = "Protocol and practice in the adaptive management of waterfowl harvests." | journal = Conservation Ecology | volume = 3 | issue = 8 | url = http://www.consecol.org/vol3/iss1/art8/

*cite book | last = Marmorek | first = D.R. | coauthors = D.C.E. Robinson, C. Murray and L. Grieg | year = 2006 | title = Enabling Adaptive Forest Management | publisher = National Commission on Science for Sustainable Forestry | pages = 94 pp | url = http://ncseonline.org/CMS400Example/uploadedFiles/NCSSF/NCSSF%20Project%20D1_Adaptive%20Forest%20Mgmt%20Final%2018%20May%2006.pdf

*cite book | last = Murray | first = Carol | coauthors = and David Marmorek | editor = in Peter Friederici (ed.), | title = Ecological Restoration of Southwestern Ponderosa Pine Forests | year = 2003 | publisher = Island Press | location = Washington, D.C. | id = ISBN 1-55963-652-1 | pages = 417-428 | chapter = Adaptive management and ecological restoration | chapterurl = http://www.essa.com/downloads/Murray_&_Marmorek_Ponderosa_Pine_2003.pdf

*cite book | last = Peterman | first = Randall M. | coauthors = and Calvin N. Peters | editor = in Vera Sit and Brenda Taylor (eds)., | title = Statistical Methods for Adaptive Management Studies | url = http://www.for.gov.bc.ca/hfd/pubs/Docs/Lmh/Lmh42.htm | year = 1998 | publisher = B.C. Ministry of Forests | location = Victoria, B.C. | id = ISBN 0-7726-3512-9 | pages = 105-127 | chapter = Decision analysis: taking uncertainties into account in forest resource management

*cite book | last = Stankey | first = George H | coauthors = Roger N. Clark and Bernard T. Bormann | Year = 2005 | title = Adaptive management of natural resources: theory, concepts, and management institutions | url = http://www.treesearch.fs.fed.us/pubs/20657 | publisher = Gen. Tech. Rep. PNW-GTR-654. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station | pages = 73 p

*cite book | last = Virine | first = Lev | coauthors = and Michael Trumper | title = " [http://www.projectdecisions.org Project Decisions: The Art and Science] " | location = Vienna, VA | publisher = Management Concepts | year = 2008 | id = ISBN 978-1567262179

*cite book | author =Elzinga, C.L., D. W. Salzer, J. W. Willoughby | year = 1998 | title = Measuring and Monitoring Plant Populations | publisher = Bureau of Land Management | location = Denver, CO | id = BLM Technical Reference 1730-1

ee also

*Conservation ecology
*Decision Theory
*Ecology
*Fisheries
*Forestry
*Optimization (mathematics)
*Operations research
*Uncertainty