Use of simulation-based statistical models to complement bioclimatic models in predicting continental scale invasion risks

Ranjan Muthukrishnan, Nicholas R Jordan, Adam S. Davis, James D Forester

Research output: Contribution to journalArticle

Abstract

Invasive species represent one of the greatest risks to global biodiversity and economic productivity of agroecosystems. The development of certain novel crops—e.g., herbaceous perennial biomass crops—may create a risk of novel invasions by these crops. Therefore, potential benefits and risks need to be weighed in making decisions about their introduction and subsequent management. Ideally, such a weighing will be based on good estimates of invasion risks in realistic scenarios pertaining to actual landscapes of concern. Most previous large-scale analyses of invasion risk have used species distribution models and their established methods. Unfortunately, these approaches are unable to incorporate local scale biotic and spatial factors that influence invasion risk. Here we present a case study for how such factors can be efficiently incorporated in large-scale analyses of invasion risk, by extending simulation models with statistical modeling tools. By these means, we predict invasion risk at the scale of the entire United States for a major biomass crop, Miscanthus × giganteus. We then combine invasion risk predictions for this method with those from bioclimatic methods, producing a map of aggregated invasion risk that can offer more nuanced predictions of invasion risk than either approach alone. Lastly, we evaluate potential risks for invasive crops that differ in invasiveness traits, to examine how geographic patterns of invasion risk vary among invaders as a result of their particular constellation of traits.

Original languageEnglish (US)
Pages (from-to)847-859
Number of pages13
JournalBiological Invasions
Volume21
Issue number3
DOIs
StatePublished - Mar 15 2019

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statistical models
complement
simulation
crop
Miscanthus giganteus
invasiveness
economic productivity
prediction
energy crops
biomass
agricultural ecosystem
crops
agroecosystems
invasive species
decision making
simulation models
biogeography
methodology
biodiversity
case studies

Keywords

  • Biofuel
  • Hybrid model
  • Invasion risk
  • Landscape
  • Spatial structure
  • Species distribution model

Cite this

Use of simulation-based statistical models to complement bioclimatic models in predicting continental scale invasion risks. / Muthukrishnan, Ranjan; Jordan, Nicholas R; Davis, Adam S.; Forester, James D.

In: Biological Invasions, Vol. 21, No. 3, 15.03.2019, p. 847-859.

Research output: Contribution to journalArticle

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