State‐space modeling to support management of brucellosis in the Yellowstone bison population. Issue 4 (1st November 2015)
- Record Type:
- Journal Article
- Title:
- State‐space modeling to support management of brucellosis in the Yellowstone bison population. Issue 4 (1st November 2015)
- Main Title:
- State‐space modeling to support management of brucellosis in the Yellowstone bison population
- Authors:
- Hobbs, N. Thompson
Geremia, Chris
Treanor, John
Wallen, Rick
White, P. J.
Hooten, Mevin B.
Rhyan, Jack C. - Abstract:
- Abstract : The bison ( Bison bison ) of the Yellowstone ecosystem, USA, exemplify the difficulty of conserving large mammals that migrate across the boundaries of conservation areas. Bison are infected with brucellosis ( Brucella abortus ) and their seasonal movements can expose livestock to infection. Yellowstone National Park has embarked on a program of adaptive management of bison, which requires a model that assimilates data to support management decisions. We constructed a Bayesian state‐space model to reveal the influence of brucellosis on the Yellowstone bison population. A frequency‐dependent model of brucellosis transmission was superior to a density‐dependent model in predicting out‐of‐sample observations of horizontal transmission probability. A mixture model including both transmission mechanisms converged on frequency dependence. Conditional on the frequency‐dependent model, brucellosis median transmission rate was 1.87 yr −1 . The median of the posterior distribution of the basic reproductive ratio ( R 0 ) was 1.75. Seroprevalence of adult females varied around 60% over two decades, but only 9.6 of 100 adult females were infectious. Brucellosis depressed recruitment; estimated population growth rate λ averaged 1.07 for an infected population and 1.11 for a healthy population. We used five‐year forecasting to evaluate the ability of different actions to meet management goals relative to no action. Annually removing 200 seropositive female bison increased byAbstract : The bison ( Bison bison ) of the Yellowstone ecosystem, USA, exemplify the difficulty of conserving large mammals that migrate across the boundaries of conservation areas. Bison are infected with brucellosis ( Brucella abortus ) and their seasonal movements can expose livestock to infection. Yellowstone National Park has embarked on a program of adaptive management of bison, which requires a model that assimilates data to support management decisions. We constructed a Bayesian state‐space model to reveal the influence of brucellosis on the Yellowstone bison population. A frequency‐dependent model of brucellosis transmission was superior to a density‐dependent model in predicting out‐of‐sample observations of horizontal transmission probability. A mixture model including both transmission mechanisms converged on frequency dependence. Conditional on the frequency‐dependent model, brucellosis median transmission rate was 1.87 yr −1 . The median of the posterior distribution of the basic reproductive ratio ( R 0 ) was 1.75. Seroprevalence of adult females varied around 60% over two decades, but only 9.6 of 100 adult females were infectious. Brucellosis depressed recruitment; estimated population growth rate λ averaged 1.07 for an infected population and 1.11 for a healthy population. We used five‐year forecasting to evaluate the ability of different actions to meet management goals relative to no action. Annually removing 200 seropositive female bison increased by 30‐fold the probability of reducing seroprevalence below 40% and increased by a factor of 120 the probability of achieving a 50% reduction in transmission probability relative to no action. Annually vaccinating 200 seronegative animals increased the likelihood of a 50% reduction in transmission probability by fivefold over no action. However, including uncertainty in the ability to implement management by representing stochastic variation in the number of accessible bison dramatically reduced the probability of achieving goals using interventions relative to no action. Because the width of the posterior predictive distributions of future population states expands rapidly with increases in the forecast horizon, managers must accept high levels of uncertainty. These findings emphasize the necessity of iterative, adaptive management with relatively short‐term commitment to action and frequent reevaluation in response to new data and model forecasts. We believe our approach has broad applications. … (more)
- Is Part Of:
- Ecological monographs. Volume 85:Issue 4(2015)
- Journal:
- Ecological monographs
- Issue:
- Volume 85:Issue 4(2015)
- Issue Display:
- Volume 85, Issue 4 (2015)
- Year:
- 2015
- Volume:
- 85
- Issue:
- 4
- Issue Sort Value:
- 2015-0085-0004-0000
- Page Start:
- 525
- Page End:
- 556
- Publication Date:
- 2015-11-01
- Subjects:
- adaptive management -- basic reproductive ratio -- Bayesian state-space models -- Bison bison -- Brucella abortus -- brucellosis -- disease transmission -- ecological forecasting -- Greater Yellowstone Ecosystem, USA -- host–parasite dynamics -- serology -- uncertainty
Ecology -- Periodicals
Ecology
Écologie
Electronic journals
Periodicals
Ressource Internet (Descripteur de forme)
Périodique électronique (Descripteur de forme)
577 - Journal URLs:
- http://www.esajournals.org/esaonline/?request=get-archive&issn=0012-9615 ↗
http://www.jstor.org/journals/00129615.html ↗
http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1557-7015 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1890/14-1413.1 ↗
- Languages:
- English
- ISSNs:
- 0012-9615
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3649.000000
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