Northwest Fisheries Science Center

Display All Information

Document Type: Journal Article
Center: NWFSC
Document ID: 8319
Title: Integrating expert perceptions into food web conservation and management"
Author: A. C. Stier, J. F. Samhouri, Steven Gray, Rebecca G. Martone, Megan Mach, B. S. Halpern, Carrie Kappel, C. Scarborough, P. S. Levin
Publication Year: 2016
Journal: Conservation Letters
DOI: 10.1111/conl.12245
Keywords: mental model,herring,Haida Gwaii
Abstract:

 Decision makers often rely on expert knowledge to guide management and policy decisions, especially in complex, dynamic, and data-poor social-ecological systems. However, the knowledge held by experts can vary- often significantly- by background, training, and experience. When differences exist they can lead to conflict due to variable perspectives on how the system works and is expected to respond to management actions. Understanding when expert perceptions vary and how these different perceptions might contribute to environmental conflict is therefore critical to building knowledge and developing shared understanding of sustainability solutions. Here we demonstrate variability in expert perceptions of food webs centered on Pacific herring—a valuable ecological, economic, and cultural resource. We use simulations to demonstrate how each expert’s perceived food web exhibits divergent perceptions about the future state of the ecosystem under future management scenarios impacting herring. Expert’s food web responses varied markedly when we simulated an increase in herring. Our findings demonstrate that expert knowledge is not as discrete or homogenous as typical expert categories suggest. Given the high variation we observed in predicted ecosystem impacts of herring, our results suggest that variation in experts’ perceptions of the ecosystem may contribute to future conflict over herring management decisions. Our study also provides a preemptive approach for managers to predict and reduce conflict as a partial function of structural disagreement and uncertainty. We suggest that by measuring how different experts anticipate ecosystems will respond to future perturbation or management action, experts can explicitly work toward consensus and building knowledge capital.