Quantifying spatio-temporal variation of invasion spread

Joshua Goldstein, Jaewoo Park, Murali Haran, Andrew Liebhold, Ottar N. Bjornstad

Research output: Contribution to journalArticle

Abstract

The spread of invasive species can have far-reaching environmental and ecological consequences. Understanding invasion spread patterns and the underlying process driving invasions are key to predicting and managing invasions. - We combine a set of statistical methods in a novel way to characterize local spread properties and demonstrate their application using simulated and historical data on invasive insects. Our method uses a Gaussian process fit to the surface of waiting times to invasion in order to characterize the vector field of spread. - Using this method, we estimate with statistical uncertainties the speed and direction of spread at each location. Simulations from a stratified diffusion model verify the accuracy of our method. - We show how we may link local rates of spread to environmental covariates for two case studies: the spread of the gypsy moth (Lymantria dispar), and hemlock woolly adelgid (Adelges tsugae) in North America. We provide an R-package that automates the calculations for any spatially referenced waiting time data.

Original languageEnglish (US)
Article number2294
JournalProceedings of the Royal Society B: Biological Sciences
Volume286
Issue number1894
DOIs
StatePublished - Jan 16 2019

Fingerprint

Adelges tsugae
temporal variation
Statistical methods
Lymantria dispar
Tsuga
Hemlock
Introduced Species
invasive species
Moths
environmental impact
statistical analysis
uncertainty
North America
methodology
moth
case studies
Uncertainty
Insects
insects
insect

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Environmental Science(all)
  • Agricultural and Biological Sciences(all)

Cite this

@article{0780fb226fef4be6bbed47e9f3d848d2,
title = "Quantifying spatio-temporal variation of invasion spread",
abstract = "The spread of invasive species can have far-reaching environmental and ecological consequences. Understanding invasion spread patterns and the underlying process driving invasions are key to predicting and managing invasions. - We combine a set of statistical methods in a novel way to characterize local spread properties and demonstrate their application using simulated and historical data on invasive insects. Our method uses a Gaussian process fit to the surface of waiting times to invasion in order to characterize the vector field of spread. - Using this method, we estimate with statistical uncertainties the speed and direction of spread at each location. Simulations from a stratified diffusion model verify the accuracy of our method. - We show how we may link local rates of spread to environmental covariates for two case studies: the spread of the gypsy moth (Lymantria dispar), and hemlock woolly adelgid (Adelges tsugae) in North America. We provide an R-package that automates the calculations for any spatially referenced waiting time data.",
author = "Joshua Goldstein and Jaewoo Park and Murali Haran and Andrew Liebhold and Bjornstad, {Ottar N.}",
year = "2019",
month = "1",
day = "16",
doi = "10.1098/rspb.2018.2294",
language = "English (US)",
volume = "286",
journal = "Proceedings of the Royal Society B: Biological Sciences",
issn = "0962-8452",
publisher = "Royal Society of London",
number = "1894",

}

Quantifying spatio-temporal variation of invasion spread. / Goldstein, Joshua; Park, Jaewoo; Haran, Murali; Liebhold, Andrew; Bjornstad, Ottar N.

In: Proceedings of the Royal Society B: Biological Sciences, Vol. 286, No. 1894, 2294, 16.01.2019.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Quantifying spatio-temporal variation of invasion spread

AU - Goldstein, Joshua

AU - Park, Jaewoo

AU - Haran, Murali

AU - Liebhold, Andrew

AU - Bjornstad, Ottar N.

PY - 2019/1/16

Y1 - 2019/1/16

N2 - The spread of invasive species can have far-reaching environmental and ecological consequences. Understanding invasion spread patterns and the underlying process driving invasions are key to predicting and managing invasions. - We combine a set of statistical methods in a novel way to characterize local spread properties and demonstrate their application using simulated and historical data on invasive insects. Our method uses a Gaussian process fit to the surface of waiting times to invasion in order to characterize the vector field of spread. - Using this method, we estimate with statistical uncertainties the speed and direction of spread at each location. Simulations from a stratified diffusion model verify the accuracy of our method. - We show how we may link local rates of spread to environmental covariates for two case studies: the spread of the gypsy moth (Lymantria dispar), and hemlock woolly adelgid (Adelges tsugae) in North America. We provide an R-package that automates the calculations for any spatially referenced waiting time data.

AB - The spread of invasive species can have far-reaching environmental and ecological consequences. Understanding invasion spread patterns and the underlying process driving invasions are key to predicting and managing invasions. - We combine a set of statistical methods in a novel way to characterize local spread properties and demonstrate their application using simulated and historical data on invasive insects. Our method uses a Gaussian process fit to the surface of waiting times to invasion in order to characterize the vector field of spread. - Using this method, we estimate with statistical uncertainties the speed and direction of spread at each location. Simulations from a stratified diffusion model verify the accuracy of our method. - We show how we may link local rates of spread to environmental covariates for two case studies: the spread of the gypsy moth (Lymantria dispar), and hemlock woolly adelgid (Adelges tsugae) in North America. We provide an R-package that automates the calculations for any spatially referenced waiting time data.

UR - http://www.scopus.com/inward/record.url?scp=85061309624&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85061309624&partnerID=8YFLogxK

U2 - 10.1098/rspb.2018.2294

DO - 10.1098/rspb.2018.2294

M3 - Article

C2 - 30963867

AN - SCOPUS:85061309624

VL - 286

JO - Proceedings of the Royal Society B: Biological Sciences

JF - Proceedings of the Royal Society B: Biological Sciences

SN - 0962-8452

IS - 1894

M1 - 2294

ER -