Distribution of first detection locations of invasive alien species in mainland China.

<p>Provincial administrative units in mainland China were separated into three groups according to their geographic position: coastal region in blue ( = provinces with sea coasts except Beijing), border region in grey ( = provinces continuous to other countries) and midland region in white ( = provinces without sea coasts or borders on other countries). Bars in red are the number of first detection locations in each province. Bars in yellow and green (for the average GDP and import value of commodities from 1986 to 2007, respectively) are standardized with same height in Guangdong province which has the highest GDP and the highest number of first detection locations. AH, BJ, CQ, FJ, GS, GD, GX, GZ, HeB, HeN, HLJ, HN, HuB, HuN, JL, JS, JX, NMG, NX, QH, SD, SaX, SaaX, SC, SH, TJ, XJ, XZ, YN and ZJ are provinces codes, standing for Anhui, Beijing, Chongqing, Fujian, Gansu, Guangdong, Guangxi, Guizhou, Hebei, Henan, Heilongjiang, Hainan, Hubei, Hunan, Jilin, Jiangsu, Jiangxi, Inner Mongolia, Ningxia, Qinghai, Shandong, Shanxi, Shaanxi, Sichuan, Shanghai, Tianjin, Xinjiang, Tibet, Yunnan and Zhejiang, respectively.</p

Regression tree analysis for the determinants of first detection location of invasive alien species.

<p>A: using all explanatory variables; B: using explanatory variables except those classified into “IP” category (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031734#pone-0031734-t001" target="_blank">Table 1</a>). Each node of the tree is described by the splitting variable, its splitting criteria, percentage of variance the splitter explains, mean ± standard deviation for the number of first detection locations of invasive alien species, and the number of sample (i.e. species) at that node in brackets. (<i>Inset</i>) Cross-validation processes for selection of the best regression trees. Line shows a single representative 10-fold cross-validation of the most frequent (modal) best trees with standard error (SE) estimates of each tree size. Bar charts are the numbers of the optimal trees of each size (frequency of tree) selected from a series of 50 cross-validations based on the minimum cost tree, which minimizes the cross-validated relative error (white, SE rule 0), and 50 cross-validations based on the one-SE rule (gray, SE rule 1), which minimizes the cross-validated relative error within one SE of the minimum. The most frequent trees have four terminal nodes. See the legend of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031734#pone-0031734-g001" target="_blank">Fig. 1</a> for province codes.</p

List of explanatory variables in China by province.

a<p>DI: Disturbance; EB: Ecological/bio-geographical variance; IP: Introduction pressure; SE: Search and recording effort; SI: Spread by unintentional introduction.</p>b<p>Data of variables except EN, AP, WP, LP, NC and NP were collected from National Bureau of Statistics of China (1986–2007) China statistical yearbook. The mean values of these variables were used for data analysis. Endemism score (EN) means the total values of endemism of species including plants, mammals and birds in each province, collected from McBeath G.A & Leng T.K. (2006) Governance of Biodiversity Conservation in China and Taiwan. Information about AP, WP, LP, NC and NP was collected from China Association of Port-of-Entry (2003) Practical Manual of Ports of Entry in China.</p>c<p>EEIQ: Entry-Exit Inspection and Quarantine.</p>d<p>Scientific research refers to state-owned research and development institutions above county level in the field of natural sciences and technology.</p