生物多样性 ›› 2016, Vol. 24 ›› Issue (4): 389-398. DOI: 10.17520/biods.2015243
所属专题: 中国西南干旱河谷的植物多样性
许玥1, 李鹏1, 刘晔2, 张婉君3, 秦思雨4, 沈泽昊1,*()
收稿日期:
2015-09-14
接受日期:
2015-09-14
出版日期:
2016-04-20
发布日期:
2016-05-11
通讯作者:
沈泽昊
基金资助:
Yue Xu1, Peng Li1, Ye Liu2, Wanjun Zhang3, Siyu Qin4, Zehao Shen1,*()
Received:
2015-09-14
Accepted:
2015-09-14
Online:
2016-04-20
Published:
2016-05-11
Contact:
Shen Zehao
摘要:
外来物种入侵严重威胁着乡土植物多样性并削弱了生态系统服务功能。本文基于滇西北怒江河谷植被调查的样方数据, 从群落水平研究了乡土和入侵植物多样性的空间分布格局, 以及地形、气候、人类干扰等因子对两种格局的影响。本研究共记录到外来入侵植物26种, 隶属于13科21属; 乡土植物1,145种, 分属于158科628属。沿着怒江河谷, 入侵植物物种丰富度随纬度与海拔的增加而减少; 乡土物种丰富度则随纬度增加而增加, 并在海拔梯度上呈单峰格局。运用广义线性模型分析公路边缘效应(反映生境干扰)、气候、地形和土壤等环境因素对物种丰富度分布格局的影响。等级方差分离的结果显示, 公路两侧的生境干扰对入侵种和乡土种的丰富度格局均具有首要影响。在自然环境因子中, 降水量是入侵植物丰富度的主要限制因子, 而乡土物种丰富度则主要受到地形因子尤其是坡向的影响。结构方程模型的分析结果也表明, 乡土植物和入侵植物丰富度之间的负相关关系反映了二者对环境响应的差异。本文结果支持物种入侵的资源可利用性限制假说, 并强调了人类活动对生物多样性的负面影响; 乡土植物或已较好地适应了干旱河谷气候, 但并没有显示出对外来物种入侵的抵抗作用。
许玥, 李鹏, 刘晔, 张婉君, 秦思雨, 沈泽昊 (2016) 怒江河谷入侵植物与乡土植物丰富度的分布格局与影响因子. 生物多样性, 24, 389-398. DOI: 10.17520/biods.2015243.
Yue Xu, Peng Li, Ye Liu, Wanjun Zhang, Siyu Qin, Zehao Shen (2016) Spatial patterns and determinants of species richness of alien and native plants in the Nujiang River valley. Biodiversity Science, 24, 389-398. DOI: 10.17520/biods.2015243.
图2 怒江河谷入侵(A)与乡土植物(B)丰富度随纬度和海拔的分布
Fig. 2 Distribution of invasive (A) and native (B) species richness along latitude and altitude in Nujiang River valley
图3 基于等级方差分离的怒江河谷入侵(a)和乡土植物(b)物种丰富度格局的环境因子独立和联合解释能力。*表示在0.05水平显著。
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.
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 |
表1 环境因子的主成分分析结果。表中的值为各因子在主成分中的载荷、各主成分的特征值及解释百分比。粗体为4个主成分中载荷较大的变量。
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 |
图5 环境因子主成分(PCA1, PCA2, PCA3, PCA4)和乡土种丰富度(nat_ric)对入侵种丰富度(inv_ric)影响的结构方程模型。箭头方向表示因果关系, 数字表示路径相关系数, 方框旁的数字表示模型对变量变异的解释系数, 星号表示相关的显著性水平: *P < 0.05, **P < 0.01, ***P < 0.001。
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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