TY - JOUR
T1 - Reframing wildlife disease management problems with decision analysis
AU - McEachran, Margaret C.
AU - Harvey, Johanna A.
AU - Mummah, Riley O.
AU - Bletz, Molly C.
AU - Teitelbaum, Claire S.
AU - Rosenblatt, Elias
AU - Rudolph, F. Javiera
AU - Arce, Fernando
AU - Yin, Shenglai
AU - Prosser, Diann J.
AU - Mosher, Brittany A.
AU - Mullinax, Jennifer M.
AU - DiRenzo, Graziella V.
AU - Couret, Jannelle
AU - Runge, Michael C.
AU - Grant, Evan H.Campbell
AU - Cook, Jonathan D.
N1 - Publisher Copyright:
© ([0-9]+) Society for Conservation Biology.
PY - 2024/8
Y1 - 2024/8
N2 - Contemporary wildlife disease management is complex because managers need to respond to a wide range of stakeholders, multiple uncertainties, and difficult trade-offs that characterize the interconnected challenges of today. Despite general acknowledgment of these complexities, managing wildlife disease tends to be framed as a scientific problem, in which the major challenge is lack of knowledge. The complex and multifactorial process of decision-making is collapsed into a scientific endeavor to reduce uncertainty. As a result, contemporary decision-making may be oversimplified, rely on simple heuristics, and fail to account for the broader legal, social, and economic context in which the decisions are made. Concurrently, scientific research on wildlife disease may be distant from this decision context, resulting in information that may not be directly relevant to the pertinent management questions. We propose reframing wildlife disease management challenges as decision problems and addressing them with decision analytical tools to divide the complex problems into more cognitively manageable elements. In particular, structured decision-making has the potential to improve the quality, rigor, and transparency of decisions about wildlife disease in a variety of systems. Examples of management of severe acute respiratory syndrome coronavirus 2, white-nose syndrome, avian influenza, and chytridiomycosis illustrate the most common impediments to decision-making, including competing objectives, risks, prediction uncertainty, and limited resources.
AB - Contemporary wildlife disease management is complex because managers need to respond to a wide range of stakeholders, multiple uncertainties, and difficult trade-offs that characterize the interconnected challenges of today. Despite general acknowledgment of these complexities, managing wildlife disease tends to be framed as a scientific problem, in which the major challenge is lack of knowledge. The complex and multifactorial process of decision-making is collapsed into a scientific endeavor to reduce uncertainty. As a result, contemporary decision-making may be oversimplified, rely on simple heuristics, and fail to account for the broader legal, social, and economic context in which the decisions are made. Concurrently, scientific research on wildlife disease may be distant from this decision context, resulting in information that may not be directly relevant to the pertinent management questions. We propose reframing wildlife disease management challenges as decision problems and addressing them with decision analytical tools to divide the complex problems into more cognitively manageable elements. In particular, structured decision-making has the potential to improve the quality, rigor, and transparency of decisions about wildlife disease in a variety of systems. Examples of management of severe acute respiratory syndrome coronavirus 2, white-nose syndrome, avian influenza, and chytridiomycosis illustrate the most common impediments to decision-making, including competing objectives, risks, prediction uncertainty, and limited resources.
UR - http://www.scopus.com/inward/record.url?scp=85193913073&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85193913073&partnerID=8YFLogxK
U2 - 10.1111/cobi.14284
DO - 10.1111/cobi.14284
M3 - Article
C2 - 38785034
AN - SCOPUS:85193913073
SN - 0888-8892
VL - 38
JO - Conservation Biology
JF - Conservation Biology
IS - 4
M1 - e14284
ER -