中国芦苇沼泽植物物种丰富度分布格局及其驱动因素

doi:10.17520/biods.2023194

生物多样性 ›› 2024, Vol. 32 ›› Issue (2): 23194. DOI: 10.17520/biods.2023194

• 研究报告: 植物多样性 • 下一篇

中国芦苇沼泽植物物种丰富度分布格局及其驱动因素

孟敬慈²^,¹(), 王国栋¹^,^*(), 曹光兰³^,⁴^,^*(), 胡楠林¹, 赵美玲¹, 赵延彤¹, 薛振山¹, 刘波¹, 朴文华³, 姜明¹

1.中国科学院东北地理与农业生态研究所湿地生态与环境重点实验室, 长春 130102
2.延边大学融合学院, 吉林延吉 133002
3.延边大学地理与海洋科学学院, 吉林延吉 133002
4.南开大学环境科学与工程学院, 天津 300350

收稿日期:2023-06-09 接受日期:2023-11-24 出版日期:2024-02-20 发布日期:2024-03-01
通讯作者: *E-mail: wanggd@iga.ac.cn; guanglancao@ybu.edu.cn
基金资助:
国家重点研发计划(2022YFF1301000);国家自然科学基金(U23A2004);国家自然科学基金(42077070);国家自然科学基金(U19A2042);国家科技基础性工作专项(2013FY111800)

Patterns and drivers of plant species richness in Phragmites australis marshes in China

Meng Jingci²^,¹(), Wang Guodong¹^,^*(), Cao Guanglan³^,⁴^,^*(), Hu Nanlin¹, Zhao Meiling¹, Zhao Yantong¹, Xue Zhenshan¹, Liu Bo¹, Piao Wenhua³, Jiang Ming¹

1 Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102
2 College of Integration Science, Yanbian University, Yanji, Jilin 133002
3 College of Geography and Ocean Science, Yanbian University, Yanji, Jilin 133002
4 College of Environmental Science and Engineering, Nankai University, Tianjin 300350

Received:2023-06-09 Accepted:2023-11-24 Online:2024-02-20 Published:2024-03-01
Contact: *E-mail: wanggd@iga.ac.cn; guanglancao@ybu.edu.cn

摘要/Abstract

摘要：

明确大尺度物种丰富度的分布格局及其影响因素一直是生态学及生物地理学领域的核心议题之一, 其对于预测全球环境变化背景下生物多样性的响应和制定减少生物多样性丧失的保护方案有着重要意义。本文基于全国芦苇(Phragmites australis)沼泽野外调查数据, 结合气候、地理、土壤等环境因子, 探讨了中国芦苇沼泽植物物种丰富度的分布格局及其驱动机制。结果表明: (1)中国的芦苇沼泽植物物种丰富度总体表现为亚热带湿润区和温带湿润半湿润区较高, 青藏高原区、温带干旱半干旱区和滨海区较低的特点; (2)芦苇沼泽植物物种丰富度与年降水、土壤有机碳、土壤总氮、纬度均呈显著正相关, 而与年均温、最冷月最低温、土壤pH值、海拔之间表现为显著负相关; (3)土壤因子特别是土壤pH值是影响芦苇沼泽植物物种丰富度的最主要因素, 其次分别为淹水状况、气候因子和地理因子; (4)结构方程模型结果表明土壤因子、淹水状况和气候因子直接影响植物物种丰富度, 而地理因子通过调控土壤因子、淹水状况与气候因子间接影响植物物种丰富度。总体而言, 中国芦苇沼泽植物物种丰富度具有空间异质性, 其分布格局受到多种因素的共同影响, 土壤因子是影响植物物种丰富度分布格局的关键环境因素。

关键词: 物种丰富度, 芦苇沼泽, 分布格局, 土壤因子

Abstract

Aims Determining the distribution pattern and drivers of broad-scale species richness is significant for predicting the response to biodiversity and formulating conservation programs to reduce biodiversity loss. This paper discusses the distribution pattern and driving mechanism of plant species richness obtained from nationwide field survey of Phragmites australis marsh data, combined with climate, geography, soil, and other environmental factors.

Method Initially, we used correlation analysis and general linear model to determine the relationship between species richness and annual mean temperature (MAT), annual precipitation, minimum temperature of coldest month (MTCM), altitude, latitude, longitude, soil pH, soil organic carbon (SOC), soil total nitrogen (TN), and topographic wetness index (TWI). Then, we used hierarchical partitioning to determine the most important drivers of species richness utilizing the following nine variables: soil factors (soil pH, SOC, TN), climate factors (MAT, annual precipitation, MTCM), geography factors (latitude, altitude), and water regime. Finally, piecewise structural equation modeling was used to assess the direct and indirect effects of these nine variables on plant species richness.

Results (1) The overall richness of plant species in Chinese P. australis marshes was (a) higher in the subtropical humid zone, temperate humid and semi-humid zone, and (b) lower in the Tibetan Plateau region, temperate arid and semi-arid zone, and coastal region. (2) The richness of plant species in P. australis marshes was significantly positively correlated with annual precipitation, SOC, TN, and latitude, but negatively correlated with the MAT, MTCM, soil pH, and altitude. (3) Soil factors, especially soil pH, were the most important factors affecting the richness of plant species in P. australis marshes, followed by water regime, climate factors, and geography factors. (4) Piecewise structural equation modeling showed that soil factors, water regime, and climate factors directly affected the richness of plant species, while geography factors indirectly affected the species richness of plants by regulating soil factors, water regime, and climate factors.

Conclusion Species richness of plants in Chinese P. australis marshes is spatially heterogeneous between the different regions. The species richness distribution pattern is affected by a combination of factors, where soil factors are the key environmental factors affecting the species richness pattern of plants. This study provides a new understanding of the broad-scale distribution pattern of plant diversity and the pattern’s conservation in P. australis marshes.

Key words: species richness, Phragmites australis marshes, distribution pattern, soil factors

孟敬慈, 王国栋, 曹光兰, 胡楠林, 赵美玲, 赵延彤, 薛振山, 刘波, 朴文华, 姜明 (2024) 中国芦苇沼泽植物物种丰富度分布格局及其驱动因素. 生物多样性, 32, 23194. DOI: 10.17520/biods.2023194.

Meng Jingci, Wang Guodong, Cao Guanglan, Hu Nanlin, Zhao Meiling, Zhao Yantong, Xue Zhenshan, Liu Bo, Piao Wenhua, Jiang Ming (2024) Patterns and drivers of plant species richness in Phragmites australis marshes in China. Biodiversity Science, 32, 23194. DOI: 10.17520/biods.2023194.

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链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2023194

https://www.biodiversity-science.net/CN/Y2024/V32/I2/23194

图/表 5

图1 中国芦苇沼泽植物物种丰富度的空间分布(a)及不同沼泽分布区植物物种丰富度的差异性分析(b) (平均值 ± 标准误)。采用单因素方差分析方法分析不同沼泽分布区植物物种丰富度的差异性, 不同字母表示差异显著(P < 0.05)。

Fig. 1 Distribution of plant species richness in Phragmites australis marshes in China (a) and the differences in plant species richness in P. australis marshes between different distribution areas (b) (mean ± SE). One-way ANOVA was used to analyze the differences in plant species richness in different distribution areas, different letters indicate significant difference (P < 0.05).

图2 中国芦苇沼泽植物物种丰富度与环境因子的相关性分析。* P < 0.05; ** P < 0.01; *** P < 0.001。

Fig. 2 Correlation analysis of plant species richness and environmental factors in Phragmites australis marshes in China. * P < 0.05; ** P < 0.01; *** P < 0.001.

图3 中国芦苇沼泽植物物种丰富度与环境因子之间的线性关系

Fig. 3 Linear relationships between plant species richness and environmental factors in Phragmites australis marshes in China

图4 物种丰富度与各环境因子之间的层次分割分析

Fig. 4 Hierarchical partitioning analysis between species richness and environmental factors

图5 通过分段结构方程模型分析地理、气候、土壤和淹水状况对芦苇沼泽植物物种丰富度的直接和间接影响。将地理、气候和土壤变量划分为复合变量, 与测量变量相邻的数字是它们与复合变量的系数, 与箭头相邻的数字是路径系数, 是直接标准化效果大小的关系。* P < 0.05; ** P < 0.01; *** P < 0.001。R2 marginal指由固定效应解释的部分, R2 condition指由固定效应和随机效应同时解释的部分。

Fig. 5 Piecewise structural equation modeling accounting for the direct and indirect effects of geography factors, climate factors, soil factors, and water regime on the species richness of Phragmites australis marshes. Dividing the geography, climate, and soil factors into composite variables, with the numbers adjacent to measured variables being their coefficients with composite variables, and the numbers adjacent being arrows are path coefficients, which is the relationship between the magnitude of the direct normalization effect. * P < 0.05; ** P < 0.01; *** P < 0.001. R2 marginal is explained by fixed effects, and R2 condition is explained by both fixed effects and random effects.

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中国芦苇沼泽植物物种丰富度分布格局及其驱动因素

Patterns and drivers of plant species richness in Phragmites australis marshes in China

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