Rapid Prototyping for Quantifying Belief Weights of Competing Hypotheses About Emergent Diseases

Authors

Ellen P. Robertson, US Geological Survey, Wetland and Aquatic Research Center
Daniel P. Walsh, The University of Montana
Julien Martin, U.S. Geological Survey, Eastern Ecological Science Center
Thierry M. Work, U.S. Geological Survey, National Wildlife Health Center
Christina A. Kellogg, U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center
James S. Evans, U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center
Victoria Barker, Florida Sea Grant
Aine Hawthorn, U.S. Geological Survey National Wildlife Health Center
Greta Aeby, Smithsonian Marine Station
Valerie J. Paul, Smithsonian Marine Station
Brian K. Walker, Nova Southeastern UniversityFollow
Yasunari Kiryu, Fish and Wildlife Research Institute, Florida Fish and Wildlife Conservation Commission
Cheryl M. Woodley, National Oceanic and Atmospheric Administration's National Ocean Service
Julie L. Meyer, University of Florida
Stephanie M. Rosales, Cooperative Institute for Marine and Atmospheric Studies, University of Miami,
Michael Studivan, Cooperative Institute for Marine and Atmospheric Studies, University of Miami
Jennifer F. Moore, Moore Ecological Analysis and Management
Marilyn E. Brandt, Center for Marine and Environmental Studies, University of the Virgin Islands
Andrew Bruckner, Florida Keys National Marine Sanctuary

Document Type

Article

Publication Date

7-1-2023

Publication Title

Journal of Environmental Management

Keywords

Stony coral tissue loss diseaseEtiologyCoral reefsDisease ecologyWildlife diseaseHypothesis testing

ISSN

1095-8630

Volume

337

First Page

117668

Abstract

Emerging diseases can have devastating consequences for wildlife and require a rapid response. A critical first step towards developing appropriate management is identifying the etiology of the disease, which can be difficult to determine, particularly early in emergence. Gathering and synthesizing existing information about potential disease causes, by leveraging expert knowledge or relevant existing studies, provides a principled approach to quickly inform decision-making and management efforts. Additionally, updating the current state of knowledge as more information becomes available over time can reduce scientific uncertainty and lead to substantial improvement in the decision-making process and the application of management actions that incorporate and adapt to newly acquired scientific understanding. Here we present a rapid prototyping method for quantifying belief weights for competing hypotheses about the etiology of disease using a combination of formal expert elicitation and Bayesian hierarchical modeling. We illustrate the application of this approach for investigating the etiology of stony coral tissue loss disease (SCTLD) and discuss the opportunities and challenges of this approach for addressing emergent diseases. Lastly, we detail how our work may apply to other pressing management or conservation problems that require quick responses. We found the rapid prototyping methods to be an efficient and rapid means to narrow down the number of potential hypotheses, synthesize current understanding, and help prioritize future studies and experiments. This approach is rapid by providing a snapshot assessment of the current state of knowledge. It can also be updated periodically (e.g., annually) to assess changes in belief weights over time as scientific understanding increases. Synthesis and applications: The rapid prototyping approaches demonstrated here can be used to combine knowledge from multiple experts and/or studies to help with fast decision-making needed for urgent conservation issues including emerging diseases and other management problems that require rapid responses. These approaches can also be used to adjust belief weights over time as studies and expert knowledge accumulate and can be a helpful tool for adapting management decisions.

Comments

© 2023 Elsevier Ltd. All rights reserved.

NSUWorks Citation

Ellen P. Robertson, Daniel P. Walsh, Julien Martin, Thierry M. Work, Christina A. Kellogg, James S. Evans, Victoria Barker, Aine Hawthorn, Greta Aeby, Valerie J. Paul, Brian K. Walker, Yasunari Kiryu, Cheryl M. Woodley, Julie L. Meyer, Stephanie M. Rosales, Michael Studivan, Jennifer F. Moore, Marilyn E. Brandt, and Andrew Bruckner. 2023. Rapid Prototyping for Quantifying Belief Weights of Competing Hypotheses About Emergent Diseases .Journal of Environmental Management : 117668 . https://nsuworks.nova.edu/occ_facarticles/1334.

ORCID ID

https://orcid.org/0000-0001-8385-7066

DOI

https://doi.org/10.1016/j.jenvman.2023.117668