TY - JOUR
T1 - RE-ARMing salt marshes
T2 - a resilience-experimentalist approach to prescribed fire and bird conservation in high marshes of the Gulf of Mexico
AU - Stantial, Michelle L.
AU - Fournier, Auriel M.V.
AU - Lawson, Abigail J.
AU - Marcot, Bruce G.
AU - Woodrey, Mark S.
AU - Lyons, James E.
N1 - Publisher Copyright:
Copyright © 2024 Stantial, Fournier, Lawson, Marcot, Woodrey and Lyons.
PY - 2024
Y1 - 2024
N2 - Uncertainty, complexity, and dynamic changes present challenges for conservation and natural resource management. Evidence-based approaches grounded in reliable information and rigorous analysis can enhance the navigation of the uncertainties and trade-offs inherent in conservation problems. This study highlights the importance of collaborative efforts and evidence-based decision-making, specifically implementing the Resilience-Experimentalist school of adaptive management (RE-ARM), which emphasizes stakeholder involvement, shared understanding, and experimentation. Our goal was to develop an adaptive management framework to reduce the uncertainty around the use of prescribed fire to manage the habitat for eastern black rails (Laterallus jamaicensis jamaicensis) and mottled ducks (Anas fulvigula) in saltmarshes of the Gulf of Mexico. Supported by discussions at a series of workshops, we used a value of information analysis to select a fire management hypothesis to test, developed an influence diagram to represent the system under fire management, used the influence diagram to develop a Bayesian decision network (BDN), and conducted a power analysis to guide management experiments and monitoring. Value of information analysis identified fire return interval as the critical uncertainty. Our BDN provided valuable insight into how managers believe prescribed fire influences vegetation characteristics and how vegetation influences both eastern black rail occupancy and mottled duck abundance. The results of the power analysis indicated that a standard occupancy modeling framework was more useful to compare 2- and 5-year fire return intervals for black rails than two alternative designs (removal and conditional). Our BDN can be used to predict the probability of achieving the desirable vegetative response to increase the occupancy probability of black rails and abundance of mottled ducks, and monitoring data can be used to update the BDN (learn) and improve best management practices for prescribed burns (adapt). Linking the value of information, BDNs, and power analysis enhances our understanding of the system, improves management decision-making, and builds trust among scientists, interested parties, and decision-makers. This approach lays the groundwork for knowledge co-production and adaptive management.
AB - Uncertainty, complexity, and dynamic changes present challenges for conservation and natural resource management. Evidence-based approaches grounded in reliable information and rigorous analysis can enhance the navigation of the uncertainties and trade-offs inherent in conservation problems. This study highlights the importance of collaborative efforts and evidence-based decision-making, specifically implementing the Resilience-Experimentalist school of adaptive management (RE-ARM), which emphasizes stakeholder involvement, shared understanding, and experimentation. Our goal was to develop an adaptive management framework to reduce the uncertainty around the use of prescribed fire to manage the habitat for eastern black rails (Laterallus jamaicensis jamaicensis) and mottled ducks (Anas fulvigula) in saltmarshes of the Gulf of Mexico. Supported by discussions at a series of workshops, we used a value of information analysis to select a fire management hypothesis to test, developed an influence diagram to represent the system under fire management, used the influence diagram to develop a Bayesian decision network (BDN), and conducted a power analysis to guide management experiments and monitoring. Value of information analysis identified fire return interval as the critical uncertainty. Our BDN provided valuable insight into how managers believe prescribed fire influences vegetation characteristics and how vegetation influences both eastern black rail occupancy and mottled duck abundance. The results of the power analysis indicated that a standard occupancy modeling framework was more useful to compare 2- and 5-year fire return intervals for black rails than two alternative designs (removal and conditional). Our BDN can be used to predict the probability of achieving the desirable vegetative response to increase the occupancy probability of black rails and abundance of mottled ducks, and monitoring data can be used to update the BDN (learn) and improve best management practices for prescribed burns (adapt). Linking the value of information, BDNs, and power analysis enhances our understanding of the system, improves management decision-making, and builds trust among scientists, interested parties, and decision-makers. This approach lays the groundwork for knowledge co-production and adaptive management.
KW - adaptive management
KW - Bayesian decision network
KW - co-production
KW - marsh birds
KW - power analysis
KW - structured decision making
KW - value of information
UR - http://www.scopus.com/inward/record.url?scp=85205390511&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85205390511&partnerID=8YFLogxK
U2 - 10.3389/fcosc.2024.1426646
DO - 10.3389/fcosc.2024.1426646
M3 - Article
AN - SCOPUS:85205390511
SN - 2673-611X
VL - 5
JO - Frontiers in Conservation Science
JF - Frontiers in Conservation Science
M1 - 1426646
ER -