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J. Elith, M. Burgman, H. Regan (2002)
Mapping epistemic uncertainties and vague concepts in predictions of species distributionEcological Modelling, 157
R. Venette, R. Moon, W. Hutchison (2002)
Strategies and statistics of sampling for rare individuals.Annual review of entomology, 47
L. Cavalli-Sforza (1959)
Population Studies: Animal Ecology and Demography.American Journal of Human Genetics, 11
A. Davis, L. Jenkinson, J. Lawton, B. Shorrocks, S. Wood (1998)
Making mistakes when predicting shifts in species range in response to global warmingNature, 391
H. Regan, M. Colyvan, M. Burgman (2002)
A TAXONOMY AND TREATMENT OF UNCERTAINTY FOR ECOLOGY AND CONSERVATION BIOLOGYEcological Applications, 12
Helen Regan, H. Akçakaya, S. Ferson, Karen Root, S. Carroll, L. Ginzburg (2003)
Treatments of Uncertainty and Variability in Ecological Risk Assessment of Single-Species PopulationsHuman and Ecological Risk Assessment: An International Journal, 9
A. Nicholson (1954)
An outline of the dynamics of animal populations.Australian Journal of Zoology, 2
J. Pitt, S. Worner, A. Suarez (2009)
Predicting Argentine ant spread over the heterogeneous landscape using a spatially explicit stochastic model.Ecological applications : a publication of the Ecological Society of America, 19 5
R. Pielke, R. Conant (2003)
BEST PRACTICES IN PREDICTION FOR DECISION‐MAKING: LESSONS FROM THE ATMOSPHERIC AND EARTH SCIENCESEcology, 84
(1988)
Ecological systems and their dynamics
Kalaris is an analyst for Plant Protection and Quarantine
R. Magarey, Glenn Fowler, D. Borchert, Turner Sutton, Manuel Colunga-Garcia, J. Simpson (2007)
NAPPFAST: An Internet System for the Weather-Based Mapping of Plant Pathogens.Plant disease, 91 4
J. Lobo, A. Jiménez‐Valverde, R. Real (2008)
AUC: a misleading measure of the performance of predictive distribution modelsGlobal Ecology and Biogeography, 17
M. Austin, Jacqui Meyers (1996)
Current approaches to modelling the environmental niche of eucalypts: implication for management of forest biodiversityForest Ecology and Management, 85
J. Jeffers (1988)
Practitioner's handbook on the modelling of dynamic change in ecosystems
A. Guisan, N. Zimmermann (2000)
Predictive habitat distribution models in ecologyEcological Modelling, 135
P. Harvey, Robert Colwell, J. Silvertown (1983)
NULL MODELS IN ECOLOGYAnnual Review of Ecology, Evolution, and Systematics, 14
D. Kriticos, R. Randall (2001)
A comparison of systems to analyze potential weed distributions.
R. Ploeg, W. Böhm, M. Kirkham (1999)
On the origin of the theory of mineral nutrition of plants and the law of the minimumSoil Science Society of America Journal, 63
(2007)
International Standards for Phytosanitary Measures (ISPM No. 2): Framework for Pest Risk Analysis. Secretariat of the International Plant Protection Convention
Townsend Peterson, D. Vieglais, On (2001)
Predicting Species Invasions Using Ecological Niche Modeling: New Approaches from Bioinformatics Attack a Pressing Problem, 51
A. Fielding, J. Bell (1997)
A review of methods for the assessment of prediction errors in conservation presence/absence modelsEnvironmental Conservation, 24
James Brown, and Stevens, Dawn Kaufman (1996)
THE GEOGRAPHIC RANGE: Size, Shape, Boundaries, and Internal StructureAnnual Review of Ecology, Evolution, and Systematics, 27
C. Parmesan, N. Ryrholm, C. Stefanescu, J. Hill, C. Thomas, H. Descimon, B. Huntley, L. Kaila, J. Kullberg, T. Tammaru, W. Tennent, Jeremy Thomas, M. Warren (1999)
Poleward shifts in geographical ranges of butterfly species associated with regional warmingNature, 399
(1992)
User's Guide for GMPHEN: Gypsy Moth Phenology Model. United States Department of Agriculture, Forest Service
(1986)
A biogeographic analysis of Australian elapid snakes
V. Shelford (1964)
The ecology of North America
David Stockwell (2006)
Niche Modeling: Predictions from Statistical Distributions
P. Woodbury (2003)
Dos and don'ts of spatially explicit ecological risk assessmentsEnvironmental Toxicology and Chemistry, 22
R. Holt, T. Keitt, M. Lewis, B. Maurer, M. Taper (2005)
Theoretical models of species' borders: single species approachesOikos, 108
R. Sagarin, S. Gaines, B. Gaylord (2006)
Moving beyond assumptions to understand abundance distributions across the ranges of species.Trends in ecology & evolution, 21 9
Chris Johnson, M. Gillingham (2004)
Mapping uncertainty: sensitivity of wildlife habitat ratings to expert opinionJournal of Applied Ecology, 41
R. Venette, R. Koch (2008)
Integrated Pest Management: IPM for invasive species
R. Venette, Susan Cohen (2006)
Potential climatic suitability for establishment of Phytophthora ramorum within the contiguous United StatesForest Ecology and Management, 231
A. Hirzel, G. Lay (2008)
Habitat suitability modelling and niche theoryJournal of Applied Ecology, 45
(2002)
Predicting the invasive potential of exotic insects
R. Macarthur (1960)
Population Studies: Animal Ecology and Demography. Cold Spring Harbor Symposia on Quantitative Biology. Volume XXII.The Quarterly Review of Biology, 35
R. Sutherst, A. Bourne (2009)
Modelling non-equilibrium distributions of invasive species: a tale of two modelling paradigmsBiological Invasions, 11
R. Buizza, P. Houtekamer, Z. Toth, G. Pellerin, M. Wei, Yuejian Zhu (2005)
A Comparison of the ECMWF, MSC, and NCEP Global Ensemble Prediction SystemsMonthly Weather Review, 133
R. Harrington, N. Stork (1995)
Insects in a changing environment
I. Hodkinson (1999)
Species response to global environmental change or why ecophysiological models are important: a reply to Davis et al.Journal of Animal Ecology, 68
J. Bates, C. Granger (1969)
The Combination of ForecastsJournal of the Operational Research Society, 20
J. Elith, Catherine Graham, Robert Anderson, Miroslav Dudı́k, Simon Ferrier, A. Guisan, R. Hijmans, F. Huettmann, J. Leathwick, Anthony Lehmann, Jin Li, Lúcia Lohmann, Bette Loiselle, G. Manion, Craig Moritz, Miguel Nakamura, Yoshinori Nakazawa, J. Overton, A. Peterson, Steven Phillips, Karen Richardson, R. Scachetti-Pereira, R. Schapire, Jorge Soberón, Stephen Williams, M. Wisz, N. Zimmermann (2006)
Novel methods improve prediction of species' distributions from occurrence dataEcography, 29
N. Usio, H. Nakajima, R. Kamiyama, I. Wakana, S. Hiruta, N. Takamura (2006)
Predicting the distribution of invasive crayfish (Pacifastacus leniusculus) in a Kusiro Moor marsh (Japan) using classification and regression treesEcological Research, 21
(2004)
Sudden Oak Death: Protecting America's Woodlands from Phytophthora ramorum. State and Private Forestry
M. Bulmer (2005)
The theory of natural selection of Alfred Russel Wallace FRSNotes and Records of the Royal Society, 59
S. Hartley, Richard Harris, P. Lester (2006)
Quantifying uncertainty in the potential distribution of an invasive species: climate and the Argentine ant.Ecology letters, 9 9
R. Groves, F. Panetta, J. Virtue (2008)
WEED RISK ASSESSMENT
C. Beale, J. Lennon, A. Gimona (2008)
Opening the climate envelope reveals no macroscale associations with climate in European birdsProceedings of the National Academy of Sciences, 105
D. McKenney, J. Pedlar, K. Lawrence, K. Campbell, M. Hutchinson (2007)
Beyond Traditional Hardiness Zones: Using Climate Envelopes to Map Plant Range Limits, 57
A. Peterson, M. Papeş, Jorge Soberón (2008)
Rethinking receiver operating characteristic analysis applications in ecological niche modelingEcological Modelling, 213
S. Mcdowell, R. Longmore (1987)
Atlas of elapid snakes of AustraliaCopeia, 1987
H. Andrewartha, L. Birch (1954)
The distribution and abundance of animals., 20
C. Jarvis, R. Baker (2001)
Risk assessment for nonindigenous pests: 1. Mapping the outputs of phenology models to assess the likelihood of establishmentDiversity and Distributions, 7
M. Monmonier (1991)
How to Lie with Maps
Gordon Fretwell, S. Pritchard, S. Intner (2000)
References CitedJournal of Library Administration, 28
S. Barry, J. Elith (2006)
Error and uncertainty in habitat modelsJournal of Applied Ecology, 43
R. Baker, C. Sansford, C. Jarvis, R. Cannon, A. MacLeod, K. Walters (2000)
The role of climatic mapping in predicting the potential geographical distribution of non-indigenous pests under current and future climatesAgriculture, Ecosystems & Environment, 82
D. Richardson, W. Thuiller (2007)
Home away from home — objective mapping of high‐risk source areas for plant introductionsDiversity and Distributions, 13
M. Araújo, M. New (2007)
Ensemble forecasting of species distributions.Trends in ecology & evolution, 22 1
S. Isard, J. Russo, E. DeWolf (2006)
The Establishment of a National Pest Information Platform for Extension and EducationPlant Health Progress, 7
M. Gevrey, S. Worner (2006)
Prediction of Global Distribution of Insect Pest Species in Relation to Climate by Using an Ecological Informatics Method, 99
R. Pearson, W. Thuiller, M. Araújo, E. Martínez‐Meyer, L. Brotóns, C. McClean, L. Miles, P. Segurado, T. Dawson, D. Lees (2006)
Model‐based uncertainty in species range predictionJournal of Biogeography, 33
E. Radcliffe, W. Hutchison, Rafael Cancelado (2009)
Integrated Pest Management: Concepts, Tactics, Strategies and Case Studies
M. Gevrey, S. Worner (2006)
Prediction of global distribution of insect pest species in relation to climate by using an ecological informatics method.Journal of economic entomology, 99 3
D. Yemshanov, F. Koch, D. McKenney, Marla Downing, F. Sapio (2009)
Mapping Invasive Species Risks with Stochastic Models: A Cross‐Border United States‐Canada Application for Sirex noctilio FabriciusRisk Analysis, 29
Steven Phillips (2008)
Transferability, sample selection bias and background data in presence‐only modelling: a response to Peterson et al. (2007)Ecography, 31
D. Kriticos, K. Potter, NEIL Alexander, ANDY Gibb, D. Suckling (2007)
Using a pheromone lure survey to establish the native and potential distribution of an invasive Lepidopteran, Uraba lugens.Journal of Applied Ecology, 44
R. Sutherst, G. Maywald (1985)
A computerised system for matching climates in ecologyAgriculture, Ecosystems & Environment, 13
Pest risk maps are powerful visual communication tools to describe where invasive alien species might arrive, establish, spread, or cause harmful impacts. These maps inform strategic and tactical pest management decisions, such as potential restrictions on international trade or the design of pest surveys and domestic quarantines. Diverse methods are available to create pest risk maps, and can potentially yield different depictions of risk for the same species. Inherent uncertainties about the biology of the invader, future climate conditions, and species interactions further complicate map interpretation. If multiple maps are available, risk managers must choose how to incorporate the various representations of risk into their decisionmaking process, and may make significant errors if they misunderstand what each map portrays. This article describes the need for pest risk maps, compares pest risk mapping methods, and recommends future research to improve such important decision-support tools.
BioScience – Oxford University Press
Published: May 1, 2010
Keywords: Keywords biological invasions biosecurity ecological niche models climate change pest risk assessment
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