Using a self-organizing map to predict invasive species: sensitivity to data errors and a comparison with expert opinion

被引:48
作者
Paini, Dean R. [1 ,2 ]
Worner, Susan P. [1 ,3 ]
Cook, David C. [1 ,2 ,4 ]
De Barro, Paul J. [1 ,2 ]
Thomas, Matthew B. [1 ,2 ,5 ,6 ]
机构
[1] Cooperat Res Ctr Natl Plant Biosecur, Bruce, ACT 2617, Australia
[2] CSIRO Entomol, Canberra, ACT 2601, Australia
[3] Lincoln Univ, Natl Ctr Adv Bioprotect Technol, Canterbury, New Zealand
[4] Australian Natl Univ, Fenner Sch Environm & Soc, Canberra, ACT 2000, Australia
[5] Penn State Univ, Dept Entomol, University Pk, PA 16802 USA
[6] Penn State Univ, Ctr Infect Dis Dynam, University Pk, PA 16802 USA
关键词
artificial neural networks; Australia; biosecurity; establishment; exotic pest; invasion; non-indigenous species; species assemblages; RISK;
D O I
10.1111/j.1365-2664.2010.01782.x
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
P>1. Predicting which species are more likely to invade a region presents significant difficulties to researchers and government agencies. Methods for estimating the risk of establishment are often qualitative and rely on consultation with experts and stakeholders. The inherent subjectivity of this process can lead to ambiguities in any estimate of a species' risk of establishment. 2. Using global presence/absence data of insect crop pests employed a self-organizing map (SOM) to categorize regions based on similarities in species assemblages. This technique enabled them to generate a list of species and rank them based on an index of the risk of establishment. However, the sensitivity of this risk list to errors in the presence/absence data has never been tested. 3. We evaluated the sensitivity of the SOM method by altering the original presence/absence data by increasing amounts and compared estimates of risk with those generated by a national coordinating body (Plant Health Australia) utilizing expert stakeholder opinion. 4. The risk list was unaffected by alterations of up to 20% of data over all regions. The error rate we detected in the data was within these limits. 5. Comparison with the expert stakeholder methodology revealed significant differences in the estimates of establishment risk. Further analysis of the Australian data revealed that a number of regions with strong trade links to Australia supported species assemblages similar to those in Australia, suggesting they are possible sources of pest species with high probability of establishment. 6. Synthesis and applications. This analysis confirms that the SOM methodology is a robust tool in the quantification of risk of establishment. In addition, SOMs can deliver a level of objectivity, which can complement current consultative processes employed by many biosecurity agencies around the world, providing a better overall assessment of invasion risk. This assessment can inform research and development funding decisions and incursion management plans for both government and host industries. While SOMs are utilized in this work for the prioritization of pest insects they can potentially be applied to any taxa (pest or native) or at any scale in which the data are available.
引用
收藏
页码:290 / 298
页数:9
相关论文
共 21 条
  • [1] [Anonymous], CROP PROT COMP
  • [2] *BIOS AUSTR, 2001, GUID IMP RISK AN DRA
  • [3] Multi-scale analysis of species introductions: combining landscape and demographic models to improve management decisions about non-native species
    Brown, Kerry A.
    Spector, Sacha
    Wu, Wei
    [J]. JOURNAL OF APPLIED ECOLOGY, 2008, 45 (06) : 1639 - 1648
  • [4] Expansion of Dreissena into offshore waters of Lake Michigan and potential impacts on fish populations
    Bunnell, David B.
    Madenjian, Charles P.
    Holuszko, Jeffrey D.
    Adams, Jean V.
    French, John R. P., III
    [J]. JOURNAL OF GREAT LAKES RESEARCH, 2009, 35 (01) : 74 - 80
  • [5] Burgman M., 2005, Risks and Decisions for Conservation and Environmental Management
  • [6] COHEN J, 1960, EDUC PSYCHOL MEAS, V20, P46
  • [7] Benefit cost analysis of an import access request
    Cook, David C.
    [J]. FOOD POLICY, 2008, 33 (03) : 277 - 285
  • [8] Predicting the economic impact of an invasive species on an ecosystem service
    Cook, David C.
    Thomas, Matthew B.
    Cunningham, Saul A.
    Anderson, Denis L.
    De Barro, Paul J.
    [J]. ECOLOGICAL APPLICATIONS, 2007, 17 (06) : 1832 - 1840
  • [9] Using generalized dissimilarity modelling to analyse and predict patterns of beta diversity in regional biodiversity assessment
    Ferrier, Simon
    Manion, Glenn
    Elith, Jane
    Richardson, Karen
    [J]. DIVERSITY AND DISTRIBUTIONS, 2007, 13 (03) : 252 - 264
  • [10] Germain JF, 2007, FLA ENTOMOL, V90, P755, DOI 10.1653/0015-4040(2007)90[755:FROAYH]2.0.CO