Controlling range expansion in habitat networks by adaptively targeting source populations

Hock, Karlo, Wolff, Nicholas H., Beeden, Roger, Hoey, Jessica, Condie, Scott A., Anthony, Kenneth R. N., Possingham, Hugh P. and Mumby, Peter J. (2016) Controlling range expansion in habitat networks by adaptively targeting source populations. Conservation Biology, 30 4: 856-866. doi:10.1111/cobi.12665


Author Hock, Karlo
Wolff, Nicholas H.
Beeden, Roger
Hoey, Jessica
Condie, Scott A.
Anthony, Kenneth R. N.
Possingham, Hugh P.
Mumby, Peter J.
Title Controlling range expansion in habitat networks by adaptively targeting source populations
Journal name Conservation Biology   Check publisher's open access policy
ISSN 1523-1739
0888-8892
Publication date 2016-01-01
Year available 2016
Sub-type Article (original research)
DOI 10.1111/cobi.12665
Open Access Status DOI
Volume 30
Issue 4
Start page 856
End page 866
Total pages 11
Place of publication Malden, MA, United States
Publisher Blackwell Publishing
Language eng
Subject 1105 Ecology, Evolution, Behavior and Systematics
2303 Ecology
2309 Nature and Landscape Conservation
Abstract Controlling the spread of invasive species, pests, and pathogens is often logistically limited to interventions that target specific locations at specific periods. However, in complex, highly connected systems, such as marine environments connected by ocean currents, populations spread dynamically in both space and time via transient connectivity links. This results in nondeterministic future distributions of species in which local populations emerge dynamically and concurrently over a large area. The challenge, therefore, is to choose intervention locations that will maximize the effectiveness of the control efforts. We propose a novel method to manage dynamic species invasions and outbreaks that identifies the intervention locations most likely to curtail population expansion by selectively targeting local populations most likely to expand their future range. Critically, at any point during the development of the invasion or outbreak, the method identifies the local intervention that maximizes the long-term benefit across the ecosystem by restricting species' potential to spread. In so doing, the method adaptively selects the intervention targets under dynamically changing circumstances. To illustrate the effectiveness of the method we applied it to controlling the spread of crown-of-thorns starfish (Acanthaster sp.) outbreaks across Australia's Great Barrier Reef. Application of our method resulted in an 18-fold relative improvement in management outcomes compared with a random targeting of reefs in putative starfish control scenarios. Although we focused on applying the method to reducing the spread of an unwanted species, it can also be used to facilitate the spread of desirable species through connectivity networks. For example, the method could be used to select those fragments of habitat most likely to rebuild a population if they were sufficiently well protected.
Formatted abstract
Controlling the spread of invasive species, pests, and pathogens is often logistically limited to interventions that target specific locations at specific periods. However, in complex, highly connected systems, such as marine environments connected by ocean currents, populations spread dynamically in both space and time via transient connectivity links. This results in nondeterministic future distributions of species in which local populations emerge dynamically and concurrently over a large area. The challenge, therefore, is to choose intervention locations that will maximize the effectiveness of the control efforts. We propose a novel method to manage dynamic species invasions and outbreaks that identifies the intervention locations most likely to curtail population expansion by selectively targeting local populations most likely to expand their future range. Critically, at any point during the development of the invasion or outbreak, the method identifies the local intervention that maximizes the long-term benefit across the ecosystem by restricting species’ potential to spread. In so doing, the method adaptively selects the intervention targets under dynamically changing circumstances. To illustrate the effectiveness of the method we applied it to controlling the spread of crown-of-thorns starfish (Acanthaster sp.) outbreaks across Australia's Great Barrier Reef. Application of our method resulted in an 18-fold relative improvement in management outcomes compared with a random targeting of reefs in putative starfish control scenarios. Although we focused on applying the method to reducing the spread of an unwanted species, it can also be used to facilitate the spread of desirable species through connectivity networks. For example, the method could be used to select those fragments of habitat most likely to rebuild a population if they were sufficiently well protected.
Keyword Acanthaster
Adaptive management
Connectivity
Decision theory
Dynamic digraph
Invasives
Spatial network
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mathematics and Physics
HERDC Pre-Audit
School of Biological Sciences Publications
 
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Citation counts: TR Web of Science Citation Count  Cited 4 times in Thomson Reuters Web of Science Article | Citations
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