Effect of climate change on the potential distribution of HLB in South America
DOI:
https://doi.org/10.5377/ribcc.v2i4.5925Keywords:
HLB, Climate Change, PCA, Phytosanitary riskAbstract
Huanglongbing (HLB) is the most destructive disease of citrus worldwide. In South America, it has been established in some states of Brazil. The aim of this study was to estimate effects of climate change on the potential geographical distribution of the disease. For this purpose a technique based on Principal Component Analysis was used. This technique predicts the environmental suitability of a species based on the Euclidean distance from any geographical point of South America to the places where HLB has been established in South America. To estimate potential changes in geographical distribution HLB in a scenario of climate change, the Representative Concentration Pathway 2.6 was considered, proposed by the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, through the model HadGEM2-ES by 2050 and 2070. Kappa statistic was calculated. QGIS 2.12, IDRISI Selva and Infostat were used. Areas with climate risk for the establishment of HLB, would be distributed in southern Brazil, southeastern Paraguay, northeastern and eastern part of the northwest region of Argentina and south central of Bolivia. According to the estimations of the Fifth Assessment Report of the IPCC and considering the RCP 2.6, the effects of climate change could determine that areas of climate risk for the establishment of HLB would be displaced towards the southwest of the areas considered riskier nowadays.
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References
Al-Kandari, N. M., & Jolliffe, I. T. (2001). Variable selection and interpretation of covariance principal components. Communications in Statistics-Simulation and Computation, 30(2), 339-354.
https://doi.org/10.1081/SAC-100002371
Aurambout, J. P., Finlay, K. J., Luck, J., & Beattie, G. A. C. (2009). A concept model to estimate the potential distribution of the Asiatic citrus psyllid (Diaphorina citri Kuwayama) in Australia under climate change-A means for assessing biosecurity risk. Ecological Modelling, 220(19), 2512-2524.
https://doi.org/10.1016/j.ecolmodel.2009.05.010
Halbert, S. E., & Manjunath, K. L. (2004). Asian citrus psyllids (Sternorrhyncha: Psyllidae) and greening disease of citrus: a literature review and assessment of risk in Florida. Florida entomologist, 87(3), 330-353.
https://doi.org/10.1653/0015-4040(2004)087[0330:ACPSPA]2.0.CO;2
Hall, D. G., Hentz, M. G., & Adair Jr, R. C. (2008). Population ecology and phenology of Diaphorina citri (Hemiptera: Psyllidae) in two Florida citrus groves. Environmental Entomology, 37(4), 914-924.
https://doi.org/10.1093/ee/37.4.914
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G., & Jarvis, A. (2005). Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology: A Journal of the Royal Meteorological Society, 25(15), 1965-1978.
https://doi.org/10.1002/joc.1276
Lopes, S. A., Bertolini, E., Frare, G. F., Martins, E. C., Wulff, N. A., Teixeira, D. C., ... & Cambra, M. (2009). Graft transmission efficiencies and multiplication of 'Candidatus Liberibacter americanus' and 'Ca. Liberibacter asiaticus' in citrus plants. Phytopathology, 99(3), 301-306.
https://doi.org/10.1094/PHYTO-99-3-0301
Narouei-Khandan, H. A., Halbert, S. E., Worner, S. P., & van Bruggen, A. H. (2015). Global climate suitability of citrus huanglongbing and its vector, the Asian citrus psyllid, using two correlative species distribution modeling approaches, with emphasis on the USA. European Journal of Plant Pathology, 144(3), 655-670.
https://doi.org/10.1007/s10658-015-0804-7
Pearson, R. G., & Dawson, T. P. (2004). Bioclimate Envelope Models: What they detect and what they hide: Response to hampe (2004). Global Ecology and Biogeography, 13(5), 471-473.
https://doi.org/10.1111/j.1466-822X.2004.00112.x
Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological modelling, 190(3-4), 231-259.
https://doi.org/10.1016/j.ecolmodel.2005.03.026
Robertson, M. P., Caithness, N., & Villet, M. H. (2001). A PCA‐based modelling technique for predicting environmental suitability for organisms from presence records. Diversity and distributions, 7(1‐2), 15-27.
https://doi.org/10.1046/j.1472-4642.2001.00094.x
Viera, A. J., & Garrett, J. M. (2005). Understanding interobserver agreement: the kappa statistic. Fam med, 37(5), 360-363.
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