4.7 Article

Integrated assessment of biological invasions

期刊

ECOLOGICAL APPLICATIONS
卷 24, 期 1, 页码 25-37

出版社

WILEY
DOI: 10.1890/13-0776.1

关键词

Celastrus orbiculatus; demographic framework; hierarchical Bayesian models; invasive species management; Mytilus galloprovincialis; Orconectes rusticus; risk assessment; dispersal phase; colonization phase; proliferation phase; multiple scales

资金

  1. Climate and Invasions Working Group-National Center for Ecological Analysis and Synthesis, NSF [EF-0553768]

向作者/读者索取更多资源

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 speciesa vine, a marine mussel, and a freshwater crayfishunder 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.

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