Potential geographical distributions of the fruit flies ceratitis capitata, ceratitis cosyra, and ceratitis rosa in China

Journal of Economic Entomology

Volumn 102, Issue 5, 2009, Pages 1781-1790

  Li, Baini ^a,b   Ma, Jun ^b   Hu, Xuenan ^b   Liu, Haijun ^b   Zhang, Runjie ^a  

^a SUN YAT SEN UNIVERSITY   (China)

^b Guangdong Inspection and Quarantine Technology Center   (China)

Author keywords

Ceratitis capitata; Ceratitis cosyra; Ceratitis rosa; GARP; Maxent

Indexed keywords

CERATITIS CAPITATA; CERATITIS COSYRA; CERATITIS ROSA;

ALGORITHM; ANIMAL; ARTICLE; CHINA; CLIMATE; ECOSYSTEM; FRUIT; GEOGRAPHY; GROWTH, DEVELOPMENT AND AGING; MEDITERRANEAN FRUIT FLY; PARASITOLOGY; POPULATION DENSITY; SEASON; TEPHRITIDAE;

ALGORITHMS; ANIMALS; CERATITIS CAPITATA; CHINA; CLIMATE; ECOSYSTEM; FRUIT; GEOGRAPHY; POPULATION DENSITY; SEASONS; TEPHRITIDAE;

EID: 73949141891     PISSN: 00220493     EISSN: None     Source Type: Journal    
DOI: 10.1603/029.102.0508     Document Type: Article

References (49)

1. Adjemian, J.C.Z., E. H. Girvetz, L. Beckett, and J. E. Foley. 2006. Analysis of genetic algorithm for rule-set production (GARP) modeling approach for predicting distributions of ßeas implicated as vectors of plague, Yersinia pestis, in California. J. Med. Entomol. 43: 93-103.
2. Allouche, M., A. Tsoar, and R. Kadmon. 2006. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43: 1223-1232.
3. Anderson, R. P., M. Gomez-Laverde, and A. T. Peterson. 2002. Geographical distributions of spiny pocket mice in South America: insights from predictive models. Global Ecol. Biogeogr. 11: 131-141.
4. Anderson, R. P., D. Lew, and A. T. Peterson. 2003. Evaluating predictive models of speciesÕ distributions: criteria for selecting optimal models. Ecol. Model. 162: 211-232.
5. Beyer, H. 2007. HawthÕs analysis tools for ESRIÕs ArcGIS. (http://www.spatialecology.com/htools/tooldesc.php).
6. Byrt, T., J. Bishop, and J. B. Carlin. 1993. Bias, prevalence and kappa. J. Clin. Epidemiol. 46: 423-429.
7. [CABI] Centre Agriculture Bioscience International. 2005. Crop protection compendium. Centre Agriculture Bioscience International, Wallingford, United Kingdom. [CABI/EPPO] Centre Agriculture Bioscience International/
8. European Plant Protection Organization. 1999. Distribution maps of plant pests: Ceratitis cosyra. 592: 2.
9. Carey, J. R. 1991. Establishment of the Mediterranean fruit ßy in California. Science (Wash., D.C.) 253: 1369-1373.
10. Cicchetti, D. V., and A. R. Feinstein. 1990. High agreement but low kappa. II. Resolving the paradoxes. J. Clin. Epidemiol. 43: 551-558.
11. Cohen, J. 1960. A coefficient of agreement of nominal scales. Educ. Psychol. Meas. 20: 37-46.
12. De Meyer, M. 2001. On the identity of the natal fruit ßy, Ceratitis rosa Karsch (Diptera, Tephritidae). Bull. Inst. R. Sci. Nat. Belg. Entomol. 71: 55-62.
13. De Meyer, M., M. P. Robertson, A. T. Peterson, and M. W. Mansell. 2008. Ecological niches and potential geographical distributions of Mediterranean fruit ßy (Ceratitis capitata) and natal fruit ßy (Ceratitis rosa). J. Biogeogr. 35: 270-281.
14. Duyck, P. F., P. David, and S. Quilici. 2006. Climatic niche partitioning following successive invasions by fruit ßies in La Réunion. J. Anim. Ecol. 75: 518-526.
15. Duyck, P. F., and S. Quilici. 2002. Survival and development of different life stages of three Ceratitis spp. (Diptera: Tephritidae) reared at five constant temperatures. Bull. Entomol. Res. 92: 461-469.
16. Elith, J. 2002. Quantitative methods for modeling species habitat: comparative performance and an application to Australian plants. pp. 39-58. In S. Ferson and M. Burgman [eds.], Quantitative methods for conservation biology. Springer, New York.
17. Elith, J., C. H. Graham, R. P. Anderson, M. Dudik, S. Ferrier, A. Guisan, R. J. Hijmans, F. Huettmann, J. R. Leathwick, A. Lehmann, et al. 2006. Novel methods improve prediction of speciesÕ distributions from occurrence data. Ecography 29: 129-151.
18. Engler, R., A. Guisan, and L. Rechsteiner. 2004. An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudoabsence data. J. Appl. Ecol. 41: 263-274.
19. [EPPO] European and Mediterranean Plant Protection Organization. 2006. Distribution maps of quarantine pests for Europe: Ceratitis rosa. 153: 1-2.
20. ESRI Inc. 2006. ArcGIS 9.2 desktop. ESRI Inc., Redlands, CA.
21. Fielding, A. H., and J. F. Bell. 1997. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environ. Conserv. 24: 38-49.
22. Gilstrap, F. E., and W. G. Hart. 1987. Biological control of the Mediterranean fruit ßy in the United States and Central America. ARS-U.S. Department of Agriculture 56: 1052-5386.
23. Hernandez, P. A., C. H. Graham, L. L. Master, and D. L. Albert. 2006. The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography 29: 773-785.
24. Hijmans, R. J., S. E. Cameron, J. L. Parra, P. G. Jones, and A. Jarvis. 2005. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25: 1965-1978.
25. Lantza, C. A., and E. Nebenzahl. 1996. Behavior and interpretation of the k statistic: resolution of two paradoxes. J. Clin. Epidemiol. 49: 431-434.
26. Levine, R. S., A. T. Peterson, K. L. Yorita, D. Carroll, I. K. Damon, and M. G. Reynolds. 2007. Ecological niche and geographic distribution of human monkeypox in Africa. PLoS ONE 1: 1-7.
27. Lobo, J. M., A. Jiménez-Valverde, and R. Real. 2008. AUC: a misleading measure of the performance of predictive distribution models. Global Ecol. Biogeogr. 17: 145-151.
28. Loiselle, B. A., C. A. Howell, C. H. Graham, J. M. Goerck, T. Brooks, K. G. Smith, and P. H. Williams. 2003. Avoiding pitfalls of using species distribution models in conservation planning. Conserv. Biol. 17: 1591-1600.
29. Lux, S. A., N. Zenz, and S. Kimani. 1998. The African fruit ßy initiative: development, testing and dissemination of technologies for the control of fruit ßies. ICIPE Annual Scientific Report 1998-1999. 7: 78-80.
30. Papadopoulos, N. T., J. R. Carey, B. I. Katsoyannos, and N. A. Kouloussis. 1996. Overwintering of the Mediterranean fruit ßy (Diptera: Tephritidae) in northern Greece. Ann. Entomol. Soc. Am. 89: 526-534.
31. Papadopoulos, N. T., B. I. Katsoyannos, J. R. Carey, and N. A. Kouloussis. 2001. Seasonal and annual occurrence of the Mediterranean fruit ßy (Diptera: Tephritidae) in northern Greece. Ann. Entomol. Soc. Am. 94: 41-50.
32. Pape, M., and P. Gaubert. 2007. Modelling ecological niches from low numbers of occurrences: assessment of the conservation status of poorly known viverrids (Mammalia, Carnivora) across two continents. Divers. Distrib. 13: 890-902.
33. Pearson, R. G., C. J. Raxworthy, M. Nakamura, and A. T. Peterson. 2007. Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. J. Biogeogr. 34: 102-117. (Pubitemid 44952533)
34. Peterson, A. T. 2001. Predicting speciesÕ geographic distributions based on ecological niche modeling. Condor 103: 599-605.
35. Peterson, A. T., and K. P. Cohoon. 1999. Sensitivity of distributional prediction algorithms to geographic data completeness. Ecol. Model. 117: 159-164.
36. Peterson, A. T., M. Papes, and M. Eaton. 2007. Transferability and model evaluation in ecological niche modeling: a comparison of GARP and Maxent. Ecography 30: 550-560.
37. Petit, S., D. Chamberlain, K. Haysom, R. Pywell, J. Vickery, L. Warman, D. Allen, and L. Firbank. 2003. Knowledgebased models for predicting species occurrence in arable conditions. Ecography 26: 626-640.
38. Phillips, S. J. 2006. A brief tutorial on Maxent. (http://www. cs.princeton.edu/-schapire/maxent/tutorial/tutorial. doc).
39. Phillips, S. J., and M. Dudik. 2008. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31: 161-175.
40. Phillips, S. J., R. P. Anderson, and R. E. Schapire. 2006. Maximum entropy modeling of species geographic distributions. Ecol. Model. 190: 231-259.
41. Rouget, M., D. M. Richardson, J. L. Nel, D. C. Le Maitre, B. Egoh, and T. Mgidi. 2004. Mapping the potential ranges of major plant invaders in South Africa, Lesotho and Swaziland using climatic suitability. Divers. Distrib. 10: 475-484.
42. SAS Institute. 2003. SAS for Windows 9.1.2, service pack 2. SAS Institute, Cary, NC.
43. Segurado, P., and M. B. Araú jo. 2004. Anevaluation of methods for modelling speciesÕ distributions. J. Biogeogr. 31: 1555-1568.
44. SPSS Inc. 2007. SPSS 16.0 for Windows. SPSS Inc., Chicago, IL.
45. Steck, G. J. 2003. Mango fruit ßy, marula fruit ßy, Ceratitis cosyra (Walker) (Insecta: Diptera: Tephritidae). DPI Entomology Circular 403. EENY-286.
46. Tsoar, A., O. Allouche, O. Steinitz, D. Rotem, and R. Kadmon. 2007. A comparative evaluation of presence-only methods for modelling species distribution. Divers. Distrib. 13: 397-405.
47. Vargas, R. I., W. A. Walsh, D. Kanehisa, J. D. Stark, and T. Nishida. 2000. Comparative demography of three Hawaiian fruit ßies (Diptera: Tephritidae) at alternating temperatures. Ann. Entomol. Soc. Am. 93: 75-81.
48. Weems,H. V., and T. R. Fasulo. 2007. Natal fruit ßy. (http://entnemdept.uß.edu/creatures/fruit/tropical/natalfruitßy. htm).
49. White, I. M., and M. M. Elson-Harris. 1992. Fruit ßies of economic significance: their identification and bionomics. CAB International, Wallingford, United Kingdom.