连云港市滨海湿地土壤有机碳分布特征及其影响因素

摘要:
滨海湿地作为一种独特的湿地类型，海陆水文循环和生物地球化学循环复杂，有着巨大的固碳潜力，其土壤有机碳的研究对于了解碳循环、气候调节和生态系统健康等方面具有重要意义。在连云港市滨海湿地选取了光滩、碱蓬、互花米草和芦苇4种典型植物类型作为研究对象，分析了不同植物群落土壤有机碳含量的分布特征，并利用Pearson相关性分析、冗余分析(RDA)和结构方程(SEM)等统计方法，探讨了植物群落特征和土壤物理化学性质对土壤有机碳的调控作用，重点解析了滨海湿地环境因子与土壤有机碳含量间的关系。结果表明：在水平方向上，不同植物群落土壤有机碳含量大小依次为芦苇植被带((7.79±4.72) g/kg)>互花米草植被带((7.42±3.14) g/kg)>碱蓬植被带((4.95±3.40) g/kg)>光滩带((3.66±1.90) g/kg)。在垂向上，0~50 cm深度内的土壤有机碳含量的分布呈现随深度增加而降低的趋势；此外土壤有机碳含量和土壤物理化学性质、植物群落特征之间相关性显著，冗余分析结果显示在不同的植物类型中土壤有机碳含量与土壤容重呈负相关，与土壤含水率、植物株高、基径、盖度、地上生物量和地下生物量均呈正相关。结构方程模型表明，土壤含水率是影响滨海湿地土壤有机碳含量的最关键因素。以上研究可为更好地理解滨海湿地的生态系统结构和功能并为全球气候变化相关保护政策的制定提供相关的数据支持。
- 滨海湿地 /
- 植物类型 /
- 土壤有机碳 /
- 分布特征 /
- 影响因素 /
- 连云港市
Abstract: Objective
Coastal wetlands, a unique type of wetland with complex hydrologic and biogeochemical cycles, have ignificant carbon sequestration potential. Research on soil organic carbon (SOC) is critical for understanding carbon cycle, climatic regulation, and ecosystem health.
Methods
This study focused on four typical vegetation types grown in the coastal wetlands of Lianyungang, namely, Mudflats, Seepweed, Spartina alterniflora and Reeds. We analyzed the distribution characteristics of soil organic carbon content across different plant communities, and utilized statistical methods such as pearson correlation analysis, redundancy analysis (RDA), and structural equation modeling (SEM) to explore the regulatory effects of plant community characteristics and soil physicochemical properties on soil organic carbon. Particular attention was given to the relationships between environmental factors of coastal wetlands and soil organic carbon content.
Results
Horizontally, the soil organic carbon content of the different plant communities decreased in the following order: Reeds ((7.79±4.72) g/kg)>Spartina alterniflora ((7.42±3.14) g/kg)>Seepweed ((4.95±3.40) g/kg)>Mudflats ((3.66±1.90) g/kg). Vertically, the soil organic carbon content decreased with increasing depth within 0-50 cm. Additionally, significant correlations were found between SOC content and soil physicochemical properties, as well as plant community characteristics. The results of the redundancy analysis indicate that soil organic carbon content is negatively correlated with BD (bulk density) in different wetland types but is positively correlated with SWC (soil water content), height, diameter, coverage, AGB (above ground biomass) and BGB (below ground biomass). The structural equation model showed that the soil water content was the most important factor affecting soil organic carbon content in coastal wetlands.
Conclusion
These findings can not only promote a better understanding of coastal wetlands from their ecosystem structure and function but also provide relevant data support for policy making on global climate change.
- coastal wetland /
- vegetation type /
- soil organic carbon /
- distribution characteristics /
- influencing factor /
- Lianyungang
注释:

所有作者声明不存在利益冲突。

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图 1 研究区采样点示意图

Figure 1. Schematic diagram of the sampling sites in the study area

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图 2 不同覆被类型土壤有机碳的分布特征

不同字母表示不同覆被类型间w(SOC)差异显著(p＜0.05)

Figure 2. Distribution of soil organic carbon in different coastline types

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图 3 不同植物群落w(SOC)随土壤深度的变化

Figure 3. Changes in soil organic carbon content with depth in different plant communities

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图 4 不同植物群落土壤有机碳密度分布情况

Figure 4. Distribution of soil organic carbon density under different cover types

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图 5 w(SOC)与环境因子间的相关性分析

红色表示正相关，蓝色表示负相关；“** ”表示p=0.01水平的显著性；“*** ”表示p=0.001水平的显著性，椭圆的集中度表示相关性的强度；SWC.土壤含水率；BD.容重；EC.电导率；AGB.地上生物量；BGB.地下生物量；下同

Figure 5. Correlation analysis between soil organic carbon content and influencing factors

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图 6 土壤有机碳与土壤理化性质、植物群落特征的冗余分析

空心箭头连线代表环境因子，2个箭头夹角余弦值与箭头长度的乘积代表环境因子与w(SOC)的相关性大小，该值为正时表示为正相关关系，反之为负相关关系，其绝对值越大相关性也就越大。RDA1，RDA2为排序轴，解释环境变量和响应变量之间关系的主成分，百分比指每个排序轴解释的方差比例

Figure 6. Redundancy analysis of soil organic carbon, soil physicochemical properties and plant community characteristics

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图 7 土壤物理化学性质、植物群落特征和w(SOC)间拟合的结构方程模型

χ²=50.572; DF=18;χ²/DF=1.383;GFI=0.943; AGFI=0.886; RMSEA=0.101。红色表示负相关，蓝色表示正相关，箭头粗细表示相关性大小，其中χ²/DF为卡方自由度比值；GFI为拟合优度参数；AGFI为调整后拟合优度参数；RMSEA为近似误差均方根；e₁~e₇为残差变量

Figure 7. Structural equation model fitting between soil physicochemical properties, plant community characteristics and soil organic carbon content

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表 1 研究区w(SOC)和土壤物理化学性质特征统计(n=180)

Table 1. Statistics of the soil organic carbon content and soil physicochemical properties in the study area(n=180)

变量	均值	标准差	变异系数/%
含水率/%	52.55	21.35	40.62
容重/(g·cm^-3)	1.01	0.28	28.06
电导率/(mS·cm^-1)	4.84	2.36	48.79
pH值	8.55	0.29	3.41
w(SOC)/(g·kg^-1)	6.34	3.50	55.26

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表 2 w(SOC)与植物群落特征统计

Table 2. Statistics of the soil organic carbon content and plant community characteristics

植物群落	w(SOC)/(g·kg^-1)	株高/cm	基径/mm	盖度/%	地上生物量/(g·m^-2)	地下生物量/(g·m^-2)
互花米草	7.42±3.14	76.54	8.25	60.30	2 510.74	3 428.95
碱蓬	4.95±3.40	47.33	5.89	35.91	3 132.43	7 870.05
芦苇	7.79±4.72	165.36	6.71	90.00	4 643.25	14 474.90

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表 3 植被带深度0~50 cm地下生物量(BGB)及w(SOC)分布情况

Table 3. Distribution of below-ground biomass(BGB) and soil organic carbon(SOC) content in the 0-50 cm vegetation zone

土壤深度/cm	互花米草		碱蓬		芦苇
土壤深度/cm	BGB/(g·m^-2)	w(SOC)/(g·kg^-1)	BGB/(g·m^-2)	w(SOC)/(g·kg^-1)	BGB/(g·m^-2)	w(SOC)/(g·kg^-1)
0~10	1 350.40	8.28±2.67	4 040.42	5.97±4.31	5 629.15	15.16±7.62
10~20	789.38	8.15±2.88	1 469.21	4.74±3.30	1 286.37	6.79±1.57
20~30	575.82	6.98±3.10	1 086.37	4.49±3.35	1 297.37	6.07±0.46
30~40	435.59	7.12±3.72	1 168.01	4.41±2.69	801.93	5.03±0.77
40~50	277.76	6.21±3.26	1 244.05	5.13±3.65	152.56	5.89±0.35

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