Predicting the geographical distribution of Glycaspis brimblecombei (Hemiptera: Psylloidea) in Brazil

被引:32
|
作者
de Queiroz, Dalva Luiz [1 ,2 ]
Majer, Jonathan [2 ]
Burckhardt, Daniel [3 ]
Zanetti, Ronald [4 ]
Fernandez, Jaime Ivan R. [5 ,6 ]
de Queiroz, Elisiane Castro [5 ]
Garrastazu, Marilice [1 ]
Fernandes, Bianca Vique [7 ]
dos Anjos, Norivaldo [8 ]
机构
[1] Embrapa Florestas, BR-83411000 Colombo, PR, Brazil
[2] Curtin Univ Technol, Curtin Inst Biodivers & Climate, Perth, WA 6845, Australia
[3] Nat Hist Museum, CH-4001 Basel, Switzerland
[4] Univ Fed Lavras, DEN, BR-37200000 Lavras, MG, Brazil
[5] Univ Fed Parana, BR-80060000 Curitiba, PR, Brazil
[6] Inst Ecol, La Paz, Bolivia
[7] V&M Florestal, BR-35790000 Curvelo, MG, Brazil
[8] Univ Fed Vicosa, BR-36570000 Vicosa, MG, Brazil
来源
AUSTRALIAN JOURNAL OF ENTOMOLOGY | 2013年 / 52卷 / 01期
关键词
distribution; ecological modelling; eucalypt; red gum lerp psyllid; 1ST RECORD; PSYLLIDAE; PEST;
D O I
10.1111/aen.12001
中图分类号
Q96 [昆虫学];
学科分类号
摘要
The red gum lerp psyllid, Glycaspis brimblecombei Moore, has been introduced from Australia into several countries, mostly in the Americas and Europe. It was first discovered in Brazil in 2003 and has continued to spread there. Today, the species is a major pest in eucalypt plantations and often requires expensive control measures. Ecological modelling is used here to estimate the potential spread of G.brimblecombeii, worldwide and particularly in Brazil, based on environmental variables from 502 records of G.brimblecombei around the world. Distribution data from Australia were obtained from the literature and recent field surveys. For the first time, G.brimblecombei is recorded from Western Australia. Through the Openmodeller (R) program interface, 22 bioclimatic variables were used to test the efficacy of the following models: BIOCLIM, Climate Space Model, Envelope Score, Environmental Distance, GARP with best subsets (new Openmodeller implementation), GARP new Openmodeller implementation, GARP best subsets (Desktop GARP implementation), Niche Mosaic and Support Vector Machines. Among these models, Environmental Distance was the best predictor for the potential distribution of G.brimblecombei in new regions. Temperate areas appeared to be more favourable for G.brimblecombei. Regions with highest probability of occurrence in Brazil, in hierarchical order are: the southern part of the Atlantic Forest, Pampa, Caatinga and Cerrado. This modelling procedure provides a useful tool that should be incorporated in future strategies for pest management in eucalypt plantations.
引用
收藏
页码:20 / 30
页数:11
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