Ensemble ecosystem modeling for predicting ecosystem response to predator reintroduction

Baker, Christopher M., Gordon, Ascelin and Bode, Michael (2017) Ensemble ecosystem modeling for predicting ecosystem response to predator reintroduction. Conservation Biology, 31 2: 376-384. doi:10.1111/cobi.12798


Author Baker, Christopher M.
Gordon, Ascelin
Bode, Michael
Title Ensemble ecosystem modeling for predicting ecosystem response to predator reintroduction
Journal name Conservation Biology   Check publisher's open access policy
ISSN 1523-1739
0888-8892
Publication date 2017-04-01
Sub-type Article (original research)
DOI 10.1111/cobi.12798
Open Access Status Not yet assessed
Volume 31
Issue 2
Start page 376
End page 384
Total pages 9
Place of publication Malden, MA, United States
Publisher Wiley-Blackwell Publishing
Language eng
Subject 1105 Ecology, Evolution, Behavior and Systematics
2303 Ecology
2309 Nature and Landscape Conservation
Abstract Introducing a new or extirpated species to an ecosystem is risky, and managers need quantitative methods that can predict the consequences for the recipient ecosystem. Proponents of keystone predator reintroductions commonly argue that the presence of the predator will restore ecosystem function, but this has not always been the case, and mathematical modeling has an important role to play in predicting how reintroductions will likely play out. We devised an ensemble modeling method that integrates species interaction networks and dynamic community simulations and used it to describe the range of plausible consequences of 2 keystone-predator reintroductions: wolves (Canis lupus) to Yellowstone National Park and dingoes (Canis dingo) to a national park in Australia. Although previous methods for predicting ecosystem responses to such interventions focused on predicting changes around a given equilibrium, we used Lotka–Volterra equations to predict changing abundances through time. We applied our method to interaction networks for wolves in Yellowstone National Park and for dingoes in Australia. Our model replicated the observed dynamics in Yellowstone National Park and produced a larger range of potential outcomes for the dingo network. However, we also found that changes in small vertebrates or invertebrates gave a good indication about the potential future state of the system. Our method allowed us to predict when the systems were far from equilibrium. Our results showed that the method can also be used to predict which species may increase or decrease following a reintroduction and can identify species that are important to monitor (i.e., species whose changes in abundance give extra insight into broad changes in the system). Ensemble ecosystem modeling can also be applied to assess the ecosystem-wide implications of other types of interventions including assisted migration, biocontrol, and invasive species eradication.
Keyword Cascada trófica
Dingo
Dingo
Lobo
Lotka–Volterra
Q-Index Code C1
Q-Index Status Provisional Code
Grant ID DE130100572
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
School of Biological Sciences Publications
 
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Created: Fri, 24 Mar 2017, 12:01:22 EST by Christopher Baker on behalf of Learning and Research Services (UQ Library)