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Purdue E-Scholar
Other literature type . 2014
Data sources: Purdue E-Scholar
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Ecological Applications
Article . 2014 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
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Integrated assessment of biological invasions

Authors: Ibanez, Ibnes; Diez, Jeffrey M; Miller, Luke P; Olden, Julian D; Sorte, Cascade J B; Blumenthal, Dana M; Bradley, Bethany A; +5 Authors

Integrated assessment of biological invasions

Abstract

As the main witnesses of the ecological and economic impacts of invasions on ecosystems around the world, ecologists seek to provide the relevant science that informs managers about the potential for invasion of specific organisms in their region(s) of interest. Yet, the assorted literature that could inform such forecasts is rarely integrated to do so, and further, the diverse nature of the data available complicates synthesis and quantitative prediction. Here we present a set of analytical tools for synthesizing different levels of distributional and/or demographic data to produce meaningful assessments of invasion potential that can guide management at multiple phases of ongoing invasions, from dispersal to colonization to proliferation. We illustrate the utility of data‐synthesis and data‐model assimilation approaches with case studies of three well‐known invasive species—a vine, a marine mussel, and a freshwater crayfish—under current and projected future climatic conditions. Results from the integrated assessments reflect the complexity of the invasion process and show that the most relevant climatic variables can have contrasting effects or operate at different intensities across habitat types. As a consequence, for two of the study species climate trends will increase the likelihood of invasion in some habitats and decrease it in others. Our results identified and quantified both bottlenecks and windows of opportunity for invasion, mainly related to the role of human uses of the landscape or to disruption of the flow of resources. The approach we describe has a high potential to enhance model realism, explanatory insight, and predictive capability, generating information that can inform management decisions and optimize phase‐specific prevention and control efforts for a wide range of biological invasions.

Countries
United States, United Kingdom
Keywords

570, hierarchical Bayesian models, invasive species management, Science, Ecology and Evolutionary Biology, Astacoidea, Orconectes rusticus, Models, Biological, 333, demographic framework, Natural Resources and Conservation, Animals, multiple scales, proliferation phase, Biology, Demography, Mytilus, Models, Statistical, Population Biology, Celastrus orbiculatus, dispersal phase, 500, risk assessment, Celastrus, United States, proliferation phase multiple scales, Mytilus galloprovincialis, colonization phase, Introduced Species

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    48
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
48
Top 10%
Top 10%
Top 10%
Green
bronze