Application of qualitative value of information to prioritize uncertainties about eastern black rail population recovery. Issue 7 (25th May 2022)

• Record Type: Journal Article
• Authors: Lawson, Abigail J.; Kalasz, Kevin; Runge, Michael C.; Schwarzer, Amy C.; Stantial, Michelle L.; Woodrey, Mark; Lyons, James E.
• Is Part Of: Conservation science and practice. Volume 4:Issue 7(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-05-25
• Subjects: adaptive management -- decision analysis -- endangered species -- marsh birds -- structured decision making -- value of information; Biodiversity conservation -- Periodicals; Biodiversity conservation; Periodicals; 333.951605
• DOI: 10.1111/csp2.12732
• Languages: English
• ISSNs: 2578-4854

Abstract

Abstract: Natural resource management decisions are often made in the face of uncertainty. The question for the decision maker is whether the uncertainty is an impediment to the decision and, if so, whether it is worth reducing uncertainty before or while implementing actions. Value of information (VoI) methods are decision analytical tools to evaluate the benefit to the decision maker of resolving uncertainty. These methods, however, require quantitative predictions of the outcomes as a function of management alternatives and uncertainty, in which predictions which may not be available at early stages of decision prototyping. Here we describe the first participatory application of a new qualitative approach to VoI in an adaptive management workshop for Atlantic Coast eastern black rail populations. The eastern black rail is a small, cryptic marsh bird that was recently listed as federally threatened, with extremely little demographic data available. Workshop participants developed conceptual models and nine hypotheses related to the effects of habitat management alternatives on black rail demography. Here, we describe the qualitative VoI framework, how it was implemented in the workshop, and the analysis outcomes, and describe the benefits of qualitative VoI in the context of adaptive management and co‐production of conservation science.