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Controlling range expansion in habitat networks by adaptively targeting source populations

Overview of attention for article published in Conservation Biology, February 2016
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Title
Controlling range expansion in habitat networks by adaptively targeting source populations
Published in
Conservation Biology, February 2016
DOI 10.1111/cobi.12665
Pubmed ID
Authors

Karlo Hock, Nicholas H Wolff, Roger Beeden, Jessica Hoey, Scott A Condie, Kenneth R N Anthony, Hugh P Possingham, Peter J Mumby

Abstract

Controlling the spread of invasive species, pests and pathogens is often logistically limited to interventions that target specific locations at specific points in time. 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 non-deterministic future distributions of species with local populations emerging dynamically and concurrently over a large area. The challenge, therefore, is to choose intervention locations which will maximize the effectiveness of the control efforts. We propose a novel method to manage dynamic species invasions/outbreaks that identifies the intervention locations most likely to curtail population expansion. Critically, at any point during the development of the invasion or outbreak, the method identifies the local intervention that maximises the long-term benefit across the ecosystem. In so doing, the method adaptively selects the intervention targets under dynamically changing circumstances. We illustrate the effectiveness of the method by demonstrating its potential application to controlling the spread of crown-of-thorns starfish outbreaks across Australia's Great Barrier Reef. We find that application of our dynamic method results in an 18-fold improvement of management outcomes compared to a random targeting of reefs in putative crown-of-thorns starfish control scenarios. Although we focus on applying the method to reducing the spread of species, it can also be reversed and used to help facilitate the spread of species through networks. For example, the method could be used to select those fragments of habitat that are most likely to rebuild a population if sufficiently well protected. This article is protected by copyright. All rights reserved.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 1%
Unknown 73 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 22%
Researcher 16 22%
Student > Master 11 15%
Other 4 5%
Student > Bachelor 3 4%
Other 9 12%
Unknown 15 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 34%
Environmental Science 17 23%
Social Sciences 2 3%
Biochemistry, Genetics and Molecular Biology 2 3%
Computer Science 2 3%
Other 8 11%
Unknown 18 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 July 2016.
All research outputs
#15,497,948
of 24,558,777 outputs
Outputs from Conservation Biology
#3,590
of 3,965 outputs
Outputs of similar age
#218,735
of 406,989 outputs
Outputs of similar age from Conservation Biology
#29
of 31 outputs
Altmetric has tracked 24,558,777 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,965 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.0. This one is in the 8th percentile – i.e., 8% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 406,989 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.