Download and view a document containing a list of publications in the National Academy Press that include references to adaptive management.
- Why Assessments?
- Benefits of Multi-Scale
- Assessment/Planning Links (Step-Down Concept)
- Assessment Process Similarities
- Mid- and Fine-scale Assessment Tools
Bridging individuals and organizations with diverse interests, ways of communicating, missions and objectives is a challenging endeavor under any circumstances. EM is complicated by the fact that the collaborative dimension is not one in which resource professionals have been schooled, experienced or encouraged by agency procedures and professional norms. One of the priorities of EMI is to help build the capacity of different organizations to collaborate in an EM context.
The Puget Sound Nearshore Ecosystem Restoration Program (PSNERP) proposes to restore degraded shoreline ecosystems of Puget Sound. In the process of providing scientific direction for PSNERP, the Nearshore Science Team (NST) sought to more clearly define the role and position of scientific input into large restoration programs such as PSNERP. As part of the planning phase of this program, the NST conducted a "lessons learned" exercise to characterize the role of science in five other large-scale programs around the country. These programs including the Chesapeake Bay Program, the Comprehensive Everglades Restoration Plan, the California Bay-Delta Authority, the Glen Canyon Adaptive Management Program, and the Louisiana Coastal Areas Ecosystem Restoration Program. The NST’s goal was to better understand how science is incorporated into program management and organizational structure, such that the "best available science" is realized. This document summarizes lessons learned by the NST about maximizing the best available science in conceptualizing, designing and implementing large-scale restoration.
Introduction to the Special Feature: Adaptive Management - Scientifically Sound, Socially Challenged?
Management of natural resources is often conducted under great uncertainty regarding future conditions, relationships among components, user response to management, management objectives, and even abundance of the resource itself. However, we know that human use of resources and the need for management will continue in spite of this uncertainty. If we hope to improve management, we must learn as we go.
This informational slide show, presented by Nick Aumen of the National Park Service and Everglades RECOVER team, includes a study of the Central and South Florida Flood Control Project, offers a comparison of adaptive assessment and adaptive management, and reviews conceptual ecological models and performance meaures.
In July 2001, EMI faculty member Steven Yaffee and EMI senior associate Sarah McKearnan facilitated a one-day adaptive management workshop in Sacramento, California. Workshop participants included staff from the CALFED Bay-Delta Program and members of the Adaptive Management Practitioners Network (AMPN).
This chapter of the land management handbook provides an overview of principles and methods for approaches to experimentation and data analysis for adaptive management studies, including: design of experiments, non-experimental studies, retrospective studies, measurement and estimates, errors of inference, Bayesian statistics, and decision analysis.
Along with John Calhoun, ONRC has engaged Dr. Robert Lee from the University of Washington and Robert Alverts from the Bureau of Land Management as the key organizers of this conference. The Bellevue, WA conference occurred in December 2001.
Many adaptive management projects have been carried out in Australia in recent years. This paper evaluates three recent projects carried out by a group in New South Wales (NSW) (http://www.gse.mq.edu.au), with a view to improving our understanding of the adaptive management approach. These projects are presented briefly in the context of the original premises of Adaptive Environmental Assessment and Management (AEAM). In the discussion, they examine the issues raised by the case studies and make suggestions to improve the likelihood of a wider adoption of the adaptive management approach.