Spatial Education: Improving Conservation Delivery Through Space-Structured Decision Making

2013 ◽  
Vol 4 (1) ◽  
pp. 199-210 ◽  
Author(s):  
Clinton T. Moore ◽  
Terry L. Shaffer ◽  
Jill J. Gannon
Keyword(s):  
Decision Making ◽  
Adaptive Management ◽  
Land Management ◽  
Natural Resource ◽  
Spatial Context ◽  
Biological Processes ◽  
Landscape Conservation ◽  
Structured Decision Making ◽  
Landscape Conservation Cooperatives ◽  
The U.S

Abstract Adaptive management is a form of structured decision making designed to guide management of natural resource systems when their behaviors are uncertain. Where decision making can be replicated across units of a landscape, learning can be accelerated, and biological processes can be understood in a larger spatial context. Broad-based partnerships among land management agencies, exemplified by Landscape Conservation Cooperatives (conservation partnerships created through the U.S. Department of the Interior), are potentially ideal environments for implementing spatially structured adaptive management programs.

scholarly journals Structured Decision-Making and Rapid Prototyping to Plan a Management Response to an Invasive Species

2010 ◽  
Vol 1 (1) ◽  
pp. 19-32 ◽  
Author(s):  
Sean M. Blomquist ◽  
Trisha D. Johnson ◽  
David R. Smith ◽  
Geoff P. Call ◽  
Brant N. Miller ◽  
...  
Keyword(s):  
Decision Making ◽  
Adaptive Management ◽  
Predictive Models ◽  
Early Treatment ◽  
Hemlock Woolly Adelgid ◽  
Decision Making Process ◽  
Management Problem ◽  
Structured Decision Making ◽  
Management Framework ◽  
Mature Forest

Abstract We developed components of a decision structure that could be used in an adaptive management framework for responding to invasion of hemlock woolly adelgid Adeleges tsugae on the Cumberland Plateau of northern Tennessee. Hemlock woolly adelgid, an invasive forest pest, was first detected in this area in 2007. We used a structured decision-making process to identify and refine the management problem, objectives, and alternative management actions, and to assess consequences and tradeoffs among selected management alternatives. We identified four fundamental objectives: 1) conserve the aquatic and terrestrial riparian conservation targets, 2) protect and preserve hemlock, 3) develop and maintain adequate budget, and 4) address public concerns. We designed two prototype responses using an iterative process. By rapidly prototyping a first solution, insights were gained and shortcomings were identified, and some of these shortcomings were incorporated and corrected in the second prototype. We found that objectives were best met when management focused on early treatment of lightly to moderately infested but relatively healthy hemlock stands with biological control agent predator beetles and insect-killing fungi. Also, depending on the cost constraint, early treatment should be coupled with silvicultural management of moderately to severely infested and declining hemlock stands to accelerate conversion to nonhemlock mature forest cover. The two most valuable contributions of the structured decision-making process were 1) clarification and expansion of our objectives, and 2) application of tools to assess tradeoffs and predict consequences of alternative actions. Predicting consequences allowed us to evaluate the influence of uncertainty on the decision. For example, we found that the expected number of mature forest stands over 30 y would be increased by 4% by resolving the uncertainty regarding predator beetle effectiveness. The adaptive management framework requires further development including identifying and evaluating uncertainty, formalizing other competing predictive models, designing a monitoring program to update the predictive models, developing a process for re-evaluating the predictive models and incorporating new management technologies, and generating support for planning and implementation.

scholarly journals Consideration of reference points for the management of renewable resources under an adaptive management paradigm

2013 ◽  
Vol 40 (4) ◽  
pp. 302-309 ◽  
Author(s):  
BRIAN J. IRWIN ◽  
MICHAEL J. CONROY
Keyword(s):  
Decision Making ◽  
Resource Management ◽  
Natural Resource ◽  
Decision Rules ◽  
Reference Points ◽  
Natural Resource Policy ◽  
Adaptive Resource Management ◽  
Structured Decision Making ◽  
Resource Policy ◽  
Adaptive Resource

SUMMARYThe success of natural resource management depends on monitoring, assessment and enforcement. In support of these efforts, reference points (RPs) are often viewed as critical values of management-relevant indicators. This paper considers RPs from the standpoint of objective-driven decision making in dynamic resource systems, guided by principles of structured decision making (SDM) and adaptive resource management (AM). During the development of natural resource policy, RPs have been variously treated as either ‘targets’ or ‘triggers’. Under a SDM/AM paradigm, target RPs correspond approximately to value-based objectives, which may in turn be either of fundamental interest to stakeholders or intermediaries to other central objectives. By contrast, trigger RPs correspond to decision rules that are presumed to lead to desirable outcomes (such as the programme targets). Casting RPs as triggers or targets within a SDM framework is helpful towards clarifying why (or whether) a particular metric is appropriate. Further, the benefits of a SDM/AM process include elucidation of underlying untested assumptions that may reveal alternative metrics for use as RPs. Likewise, a structured decision-analytic framework may also reveal that failure to achieve management goals is not because the metrics are wrong, but because the decision-making process in which they are embedded is insufficiently robust to uncertainty, is not efficiently directed at producing a resource objective, or is incapable of adaptation to new knowledge.

Monitoring in the Context of Structured Decision-Making and Adaptive Management

2008 ◽  
Vol 72 (8) ◽  
pp. 1683-1692 ◽  
Author(s):  
James E. Lyons ◽  
Michael C. Runge ◽  
Harold P. Laskowski ◽  
William L. Kendall
Keyword(s):  
Decision Making ◽  
Adaptive Management ◽  
Structured Decision Making
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