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1 June 2014 Predicting Current and Future Invasion of Solidago canadensis: a Study from China
Zhonglin Xu, Huanhua Peng , Zhaodong Feng , Nurbay Abdulsalih
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Abstract

Solidago canadensis, which is native to North America, is considered to be the most widespread invasive alien plant. The invasion of Solidago canadensis in China has resulted in serious environmental problems. Therefore, understanding the relationship between the geographical distribution of S. canadensis and bioclimatic variables, and then predicting the potential distribution of this species is essential for management actions and practices. Although several studies have delineated the potential distribution of S. canadensis in China, how this species would respond to variations in future climatic conditions remains unclear. In the present study, we predicted the potential distribution of S. canadensis under current and future climatic conditions using species distribution models. We also analyzed range shifting of this species under current and future climatic conditions. We arrived at several conclusions. First, the potential distribution of S. canadensis may expand 40% under future climatic condition compare with that of under current condition. Second, mean diurnal range, isothermality, mean temperature of the wettest quarter, mean temperature of the warmest quarter, precipitation of the driest month, and precipitation seasonality (coefficient of variation) are key bioclimatic variables in determine the potential distribution of S. canadensis. Third, expansion of S. canadensis can be partly attributed to the relatively warmer and wetter future bioclimatic condition than current one.

Zhonglin Xu, Huanhua Peng , Zhaodong Feng , and Nurbay Abdulsalih "Predicting Current and Future Invasion of Solidago canadensis: a Study from China," Polish Journal of Ecology 62(2), 263-271, (1 June 2014). https://doi.org/10.3161/104.062.0207
Received: 1 December 2013; Published: 1 June 2014
KEYWORDS
alien invasive species
climate change
distribution
environmental variables
species distribution modeling
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