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CABI Book Chapter

Pest risk modelling and mapping for invasive alien species.

Book cover for Pest risk modelling and mapping for invasive alien species.

Description

The International Pest Risk Mapping Workgroup acknowledges that advanced training and a 'tool kit' of software packages are needed to produce pest risk maps that are fully fit for purpose. This book is an initial attempt to address those needs. Invited chapters emphasize specific steps and data requirements to guide users through the development of pest risk models and maps, or components thereof....

Metrics

Chapter 13 (Page no: 189)

Identifying and assessing critical uncertainty thresholds in a forest pest risk model.

Pest risk maps can provide helpful decision support for invasive alien species management, but often fail to address adequately the uncertainty associated with their predicted risk values. This chapter explores how increased uncertainty in a risk model's numeric assumptions (i.e. its principal parameters) might affect the resulting risk map. We used a spatial stochastic model, integrating components for entry, establishment and spread, to estimate the risks of invasion and their variation across a two-dimensional gridded landscape for Sirex noctilio, a non-native woodwasp detected in eastern North America in 2004. Historically, S. noctilio has been a major pest of pine (Pinus spp.) plantations in the southern hemisphere. We present a sensitivity analysis of the mapped risk estimates to variation in six key model parameters: (i) the annual probabilities of new S. noctilio entries at US and Canadian ports; (ii) the S. noctilio population-carrying capacity at a given location; (iii) the maximum annual spread distance; (iv) the probability of local dispersal (i.e. at a distance of 1 km); (v) the susceptibility of the host resource; and (vi) the growth rate of the host trees. We used Monte Carlo simulation to sample values from symmetric uniform distributions defined by a series of nested variability bounds around each parameter's initial values (i.e.±5%, ..., ±50%). The results show that maximum annual spread distance, which governs long-distance dispersal, was the most sensitive of the tested parameters. At±15% uncertainty in this parameter, mapped risk values shifted notably. No other parameter had a major effect, even at wider bounds of variation. The methods presented in this chapter are generic and can be used to assess the impact of uncertainties on the stability of pest risk maps or to identify any geographic areas for which management decisions can be made confidently, regardless of uncertainty.

Other chapters from this book

Chapter: 1 (Page no: 1) The challenge of modelling and mapping the future distribution and impact of invasive alien species. Author(s): Venette, R. C.
Chapter: 2 (Page no: 18) Mapping endangered areas for pest risk analysis. Author(s): Baker, R. Eyre, D. Brunel, S. Dupin, M. Reynaud, P. Jarošík, V.
Chapter: 3 (Page no: 35) Following the transportation trail to anticipate human-mediated invasions in terrestrial ecosystems. Author(s): Colunga-Garcia, M. Haack, R. A.
Chapter: 4 (Page no: 49) Simulation modelling of long-distance windborne dispersal for invasion ecology. Author(s): Parry, H. R. Eagles, D. Kriticos, D. J.
Chapter: 5 (Page no: 65) Using the MAXENT program for species distribution modelling to assess invasion risk. Author(s): Jarnevich, C. S. Young, N.
Chapter: 6 (Page no: 82) The NCSU/APHIS plant pest forecasting system (NAPPFAST). Author(s): Magarey, R. D. Borchert, D. M. Fowler, G. A. Hong, S. C.
Chapter: 7 (Page no: 97) Detecting and interpreting patterns within regional pest species assemblages using self-organizing maps and other clustering methods. Author(s): Worner, S. Eschen, R. Kenis, M. Paini, D. Saikkonen, K. Suiter, K. Sunil Singh Vänninen, I. Watts, M.
Chapter: 8 (Page no: 115) Modelling the spread of invasive species to support pest risk assessment: principles and application of a suite of generic models. Author(s): Robinet, C. Kehlenbeck, H. Werf, W. van der
Chapter: 9 (Page no: 131) Estimating spread rates of non-native species: the gypsy moth as a case study. Author(s): Tobin, P. C. Liebhold, A. M. Roberts, E. A. Blackburn, L. M.
Chapter: 10 (Page no: 145) Predicting the economic impacts of invasive species: the eradication of the giant sensitive plant from Western Australia. Author(s): Cook, D. C. Sheppard, A. Liu Shuang Lonsdale, W. M.
Chapter: 11 (Page no: 162) Spatial modelling approaches for understanding and predicting the impacts of invasive alien species on native species and ecosystems. Author(s): Allen, C. R. Uden, D. R. Johnson, A. R. Angeler, D. G.
Chapter: 12 (Page no: 171) Process-based pest risk mapping using Bayesian networks and GIS. Author(s): Klinken, R. D. van Murray, J. V. Smith, C.
Chapter: 14 (Page no: 206) Making invasion models useful for decision makers: incorporating uncertainty, knowledge gaps and decision-making preferences. Author(s): Yemshanov, D. Koch, F. H. Ducey, M.
Chapter: 15 (Page no: 223) Assessing the quality of pest risk models. Author(s): Venette, S. J.

Chapter details

  • Author Affiliation
  • USDA Forest Service, Southern Research Station, Eastern Forest Environmental Threat Assessment Center, 3041 Cornwallis Road, Research Triangle Park, NC 27709, USA.
  • Year of Publication
  • 2015
  • ISBN
  • 9781780643946
  • Record Number
  • 20153099621