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invasion sequence, Biological invasions, spread, Cercopagis pengoi, stochasticity, gravity model

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Subject-Keyword: invasion sequence Biological invasions spread Cercopagis pengoi stochasticity gravity model

Type of item: Journal Article Published

Language: English

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Description: Aim  Predictions of spread of non-indigenous species allow for greater efficiency in managing invasions by targeting areas for preventative measures. The invasion sequence is a useful concept in predictions of spread, as it allows us to test hypotheses about the transport and establishment of propagules in novel habitats. Our aims are twofold: 1 to develop and validate multi-stage invasion models for the introduced fishhook waterflea, Cercopagis pengoi, and 2 to assess how variability in the transport patterns of the propagules influences the accuracy and spatial extent for predictions of spread. Location  New York State, USA. Methods  We developed a two-stage model for the spread of C. pengoi. First, we developed a stochastic gravity model for dispersal based on surveys of recreational boat traffic in New York State as a proxy for propagule pressure. We then modelled the probability of establishment based on predicted levels of propagule pressure and measures of lakes’ physicochemistry. In addition, we used Monte Carlo simulations based on the gravity model to propagate variability in boater traffic through the establishment model to assess how uncertainty in dispersal influenced predictions of spread. Results  The amount recreationalists were willing to spend, lake area and population size of the city nearest to the destination lake were significant factors affecting boater traffic. In turn, boater traffic, lake area, specific conductance and turbidity were significant predictors of establishment. The inclusion of stochastic dispersal reduced the rate of false positives i.e. incorrect prediction of an invasion in detecting invasions at the upper 95% prediction interval for the probability of establishment. Main conclusions  Combinations of measures of propagule pressure, habitat suitability and stochastic dispersal allow for the most accurate predictions of spread. Further, multi-stage spread models may overestimate the extent of spread if stochasticity in early stages of the models is not considered.

Date created: 2011

DOI: doi:10.7939-R3FB4WQ1H

License information:

Rights: © 2011 Wiley-Blackwell. This version of this article is open access and can be downloaded and shared. The original authors and source must be cited.





Autor: Muirhead, J. R. Lewis, M. A. MacIsaac, H. J.

Fuente: https://era.library.ualberta.ca/


Introducción



1 1 Prediction and error in multi-stage models for spread of aquatic non-indigenous species 2 Jim R.
Muirhead1,2*, Mark A.
Lewis1,2,3 and Hugh J.
MacIsaac4 3 4 5 1 Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada 6 2 Centre for Mathematical Biology, University of Alberta, Edmonton, Alberta, Canada 7 3 Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, 8 9 10 Alberta, Canada 4 Great Lakes Institute for Environmental Research, University of Windsor, Windsor, Ontario, Canada 11 12 13 14 Correspondence: Jim R.
Muirhead, Smithsonian Environmental Research Center, Edgewater, Maryland; Email: muirheadj@si.edu, Phone: (433) 482-2450 15 16 Keywords: Cercopagis pengoi; gravity model; invasion sequence; spread; stochasticity 17 Running title: Prediction and error in multi-stage models 18 19 2 20 Abstract 21 Aim 22 Predictions of spread of nonindigenous species allow for greater efficiency in 23 managing invasions by targeting areas for preventative measures.
The invasion 24 sequence is a useful concept in predictions of spread as it allows us to test hypotheses 25 about the transport and establishment of propagules in novel habitats.
Our aims are 26 two-fold: 1) to develop and validate multi-stage invasion models for the introduced 27 fishhook waterflea, Cercopagis pengoi, and 2) assess how variability in the transport 28 patterns of the propagules influences the accuracy and spatial extent for predictions of 29 spread. 30 Location 31 New York State 32 Methods 33 We developed a two-stage model for the spread of C.
pengoi.
First, we 34 developed a stochastic gravity model for dispersal based on surveys of recreational 35 boat traffic in New York State as a proxy for propagule pressure.
We then modeled the 36 probability of establishment based on predicted levels of propagule pressure and 37 measures of lakes’ physicochemistry.
In addition, we used Mo...





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