Biodiversity Science ›› 2016, Vol. 24 ›› Issue (4): 389-398.doi: 10.17520/biods.2015243

Special Issue: Plant Diversity in the Dry Valleys of Southwest China

• Original Papers • Previous Article     Next Article

Spatial patterns and determinants of species richness of alien and native plants in the Nujiang River valley

Yue Xu1, Peng Li1, Ye Liu2, Wanjun Zhang3, Siyu Qin4, Zehao Shen1, *()   

  1. 1 Department of Ecology, College of Urban and Environmental Sciences, Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing 100871.
    2 School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen, Guangdong 518055
    3 Beijing Guodaotong Highway Design & Research Institute CO., LTD, Beijing 100053.
    4 Conservation International, 2011 Crystal Drive, Arlington, VA 22202
  • Received:2015-09-14 Accepted:2015-09-14 Online:2016-05-11
  • Shen Zehao E-mail:shzh@urban.pku.edu.cn

Biological invasion has attracted widespread attention because invasive species threaten native biodiversity and weaken ecosystem services. Based on field investigation of vegetation in Nujiang River valley, Northwest Yunnan, we analyzed the spatial patterns of native and invasive species richness, and the effects of topography, climate, and roadside habitat disturbance on the invasive versus native plant species richness. We recorded 26 exotic invasive plant species that belong to 13 families and 21 genera, and 1,145 native plant species, belonging to 158 families and 628 genera. Along the Nujiang River valley, species richness of invasive plants decreased with increasing latitude and altitude, while species richness of native plants increased with increasing latitude, and showed a hump-shaped pattern with elevation. A generalized linear model was used to estimate the roles of roadside disturbance, climate, topography and soil nutrients on the distribution of both native and invasive species richness. Results of hierarchical variation partitioning revealed that roadside habitat disturbance had primary impact on the distribution of two groups of species. Precipitation was the climatic determinant of invasive species diversity, and small-scale topographic factors, especially aspect, mainly affected native species diversity. It is likely that native species became drought-resistant in the evolutionary process while invasive species failed to adapt themselves to the local arid environments due to the short colonization time. This research supports the hypothesis that resource availability is the main factor limiting plant invasion, and highlights the negative effects of human activity on biodiversity. In addition, results of structural equation modelling revealed that native communities aren’t resistant to plant invasion. The negative relationship between invasive and native species richness reflects the different responses of the two group species to environmental factors.

Key words: invasive species, native species, spatial patterns, climate, human activity

Fig. 1

Distribution map of plant investigation plots alongside road in Nujiang River region"

Fig. 2

Distribution of invasive (A) and native (B) species richness along latitude and altitude in Nujiang River valley"

Fig. 3

Independent and joint contributions of environmental variables accounting for the spatial pattern of invasive and native species richness in Nujiang River valley, based on hierarchical variation partitioning model. * indicates that influence is significant at the 0.05 level. RG, Road grade; MAP, Mean annual precipitation; PDQ, Precipitation of driest quarter; PWQ, Precipitation of wettest quarter."

Fig. 4

Relationship between richness of invasive and native species"

Table 1

Principal component analysis (PCA) of environmental factors. Entries are factor loadings, eigenvalues and percentage of variation explained for the four principal components. Large component loadings among four principal components were bolded."

环境因子 Environmental factors 第一主成分 PCA1 第二主成分 PCA2 第三主成分 PCA3 第四主成分 PCA4
公路等级 Road grade 0.108 -0.028 -0.056 0.021
与公路距离 Distance to roads -0.029 0.129 -0.153 -0.487
样方内是否存在乔木
Presence or absence of trees
0.029 -0.006 -0.046 -0.113
坡形 Shape -0.019 0.011 -0.007 0.024
坡位 Position 0.099 -0.151 0.086 -0.461
坡度 Slope 0.039 -0.062 0.050 -0.581
裸地比例 Bare land percentage -0.148 -0.087 0.077 0.420
年均温 Mean annual temperature -0.351 -0.082 -0.033 -0.048
最冷季均温 Mean temperature of coldest quarter -0.349 -0.112 -0.032 -0.042
最湿季均温 Mean temperature of wettest quarter -0.353 -0.022 -0.029 -0.054
年潜在蒸散 Potential evapotranspiration -0.351 -0.082 -0.032 -0.048
年降水 Mean annual precipitation -0.179 0.507 -0.162 0.002
最干季降水 Precipitation of driest quarter -0.185 0.415 0.376 -0.008
最湿季降水 Precipitation of wettest quarter -0.116 0.323 -0.611 0.019
年实际蒸散 Actural evapotranspiration -0.351 0.059 -0.049 -0.045
水分亏缺 Water deficit 0.311 0.275 0.003 0.047
温度季节性 Temperature seasonality 0.103 0.507 0.038 -0.052
降水季节性 Precipitation seasonality 0.164 -0.211 -0.637 0.055
特征值 Eigenvalue 8.288 2.662 1.578 1.203
解释百分比 Percentage explained (%) 48.600 15.600 9.300 7.100

Fig. 5

A structural equation model showing the multivariate effects on invasive plant richness (inv_ric) by native plant richness (nat_ric) and four principal components (PCA1, PCA2, PCA3, PCA4) of environmental factors. The direction of arrows shows the causal relationships, numbers are standardized path coefficients, accompanied by positive (+) or negative (-) illustrations. The proportion of variation explained by the model is indicated by the number near each textbox. Asterisks imply the level of significance: *P < 0.05, **P < 0.01, ***P < 0.001."

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