灵渠和大溶江水体CO<sub>2</sub>排放通量和细菌群落结构特征

罗婷; 靳振江; 袁武; 杨承熹; 李嘉; 王诗萱; 范晨; 陈贵仑; 张晓文

doi:10.11932/karst20250509

灵渠和大溶江水体CO₂排放通量和细菌群落结构特征

doi: 10.11932/karst20250509

罗婷^1,,
靳振江^{1, 2, 3, 4, 5, ,},
袁武¹,
杨承熹¹,
李嘉¹,
王诗萱¹,
范晨¹,
陈贵仑¹,
张晓文¹

1.
桂林理工大学环境科学与工程学院, 广西桂林 541004
2.
桂林理工大学岩溶地区水污染控制与用水安全保障协同创新中心, 广西桂林 541004
3.
桂林理工大学广西环境污染控制理论与技术重点实验室, 广西桂林 541004
4.
广西生态环保现代产业学院, 广西桂林 541006
5.
桂林理工大学流域保护与绿色发展广西高校工程研究中心, 广西桂林 541006

基金项目: 广西重点研发计划项目（桂科AB21196050，桂科AB24010125）

详细信息

作者简介:
罗婷（1999—），女，硕士研究生，主要研究方向为环境微生物学。E-mail：lt15730527268@163.com

通讯作者:
靳振江( 1974—) ，男，博士，教授，主要研究方向为生态学和环境微生物学。E-mail：zhenjiangjinjin@163.com。

中图分类号: X143; X172
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出版历程
- 收稿日期: 2025-02-07
- 录用日期: 2025-06-04
- 修回日期: 2025-05-21
- 网络出版日期: 2026-01-13
- 刊出日期: 2025-10-25

CO₂ emission fluxes and bacterial community structures characteristics in the water bodies of the Lingqu and the Darongjiang Rivers

LUO Ting^1
,,
JIN Zhenjiang^{1, 2, 3, 4, 5
, ,},
YUAN Wu¹,
YANG Chengxi¹,
LI Jia¹,
WANG Shixuan¹,
FAN Chen¹,
CHEN Guilun¹,
ZHANG Xiaowen¹

1.
College of Environmental Science and Engineering, Guilin University of Technology, Guilin, Guangxi 541004, China
2.
Collaborative Innovation Center for Water Pollution Control and Water Safety in Karst Area, Guilin University of Technology, Guilin, Guangxi 541004, China
3.
Guangxi Key Laboratory of Environmental Pollution Control Theory and Technology, Guilin, Guangxi 541004, China
4.
Guangxi Ecological and Environmental Modern Industry College, Guilin, Guangxi 541004, China
5.
Guangxi Universities Engineering Research Center for Watershed Protection and Green Development, Guilin University of Technology, Guilin, Guangxi 541006, China

摘要

摘要: 为研究岩溶与非岩溶区域河流CO₂排放通量差异及其驱动因素，在丰水期（2023年8月）、枯水期（2024年1月）和平水期（2024年3月），采用静态箱法测定漓江上游的灵渠断面（岩溶区）和大溶江断面（非岩溶区）的CO₂排放通量，并用高通量测序技术测定细菌群落结构特征。结果显示：（1）在三个水文期中的48 h内，灵渠的CO₂排放总量分别为25.82 kg·hm⁻²、1.38 kg·hm⁻²和2.29 kg·hm⁻²，而大溶江的CO₂排放总量分别为40.46 kg·hm⁻²、1.88 kg·hm⁻²和4.36 kg·hm⁻²；（2）灵渠的CO₂排放通量与pH（P<0.01）和总氮（TN）（P<0.05）呈显著负相关关系，而大溶江的CO₂排放通量与溶解性有机碳（DOC）（P<0.05）和TN（P<0.01）呈显著正相关关系；（3）灵渠优势细菌为栖湖菌（Limnohabitans）（1.20%~26.58%）、假单胞菌（Pseudomonas）（0.24%~22.00%）和unclassified Micrococcaceae（0.45%~21.07%）等12个属，而大溶江的优势细菌为不动杆菌（Acinetobacter）（0.23%~23.79%）、unclassified Sporichthyaceae（1.64%~13.54%）和CL500-29 marine group（3.74%~12.02%）等9个属。热图分析显示，CO₂排放通量与CL500-29 marine group（P<0.01）和hgcI clade（P<0.01）的相对丰度呈显著正相关关系，而与Pseudomonas的相对丰度呈显著负相关关系（P<0.01）；（4）生态网络分析显示，灵渠网络的节点数、总边数和模块化指数均低于大溶江，表明岩溶区细菌之间的相互作用较弱、群落结构不稳定、生态系统更脆弱。因此，生物因素（CL500-29 marine group、hgcI clade和Pseudomonas等）与非生物因素（pH、DOC和TN等）共同调控着漓江水体CO₂的排放过程。
- 灵渠 /
- 大溶江 /
- CO₂排放 /
- 细菌群落 /
- 溶解有机碳（DOC)
Abstract: Rivers connect two major carbon pools-terrestrial ecosystems and marine ecosystems-and play a crucial role in the global carbon cycle. Microorganisms are the main agents driving the carbon cycling processes within river ecosystems. To some extent, microorganisms and the physicochemical characteristics of rivers can affect the production of CO₂ in rivers and are the key factors in the riverine carbon cycle. Therefore, studying the interrelationships among CO₂ emission fluxes, microorganisms and physicochemical properties at the water-air interface of rivers is essential for understanding the underlying mechanisms of riverine carbon emissions. In South China, carbonates are widely distributed, and karst processes are highly active, serving as significant drivers of the river carbon cycle. However, the differences in CO₂ emission characteristics between rivers in Karst Areas (KA) and Non-Karst Areas (NKA) as well as their driving mechanisms, remain unclear. To investigate CO₂ emission fluxes and their driving factors in river sections in KA, the Lingqu section (KA) and the Darongjiang River section (NKA) in the upper reaches of the Lijiang River were selected as the sampling points. During the wet season (August 2023), dry season (January 2024), and normal season (March 2024), CO₂ emission fluxes were measured over 48-hour periods at both the Lingqu River section and the Darongjiang River section by the static chamber method. The bacterial community structures of the rivers were characterized by high-throughput sequencing technology. Correlations between CO₂ emission fluxes, river physicochemical properties, and the microbial communities were analyzed. The main results are as follows.(1) Within 48 hours during the three hydrological periods, the CO₂ emission fluxes at the Lingqu River section were 14.54 to 352.88 mg·(m²·h)⁻¹, 0.85 to 10.47 mg·(m²·h)⁻¹, and 1.05 to 13.83 mg·(m²·h)⁻¹, respectively. The total emissions were 25.82 kg·hm⁻², 1.38 kg·hm⁻², and 2.29 kg·hm⁻², respectively. At the Darongjiang River section, CO₂ emission fluxes were 3.70 to 399.90 mg·(m²·h)⁻¹, 1.25 to 8.24 mg·(m²·h)⁻¹, and 4.14 to 36.09 mg·(m²·h)⁻¹, respectively, with total emissions of 40.46 kg·hm⁻², 1.88 kg·hm⁻², and 4.36 kg·hm⁻², respectively. The CO₂ emission fluxes at the water-air interface in both KA and NKA were positive, indicating that the study area is a source of CO₂. The CO₂ emission followed the pattern: flood season > normal season > dry season. (2) The CO₂ emission flux at the Lingqu River section was significantly negatively correlated with pH (P<0.01) and Total Nitrogen (TN) (P<0.05), while the CO₂ emission flux at the Darongjiang River was significantly positively correlated with Dissolved Organic Carbon (DOC) (P<0.05) and TN (P<0.01). When the CO₂ emission flux and physicochemical properties of both the Lingqu River and Darongjiang River sections were analyzed, the CO₂ emission flux showed a significant positive correlation with DOC (P<0.05) and a significant negative correlation with pH (P<0.01). (3) At the bacterial genus level, twelve dominant bacterial genera were identified in the Lingqujiang River section, including Limnohabitans (1.20% to 26.58%), Pseudomonas (0.24% to 22.00%), and unclassified Micrococcaceae (0.45% to 21.07%). In contrast, nine dominant bacterial genera were found in the Darongjiang River section, including Acinetobacter (0.23% to 23.79%), unclassified Sporichthyaceae (1.64% to 13.54%), and the CL500-29 marine group (3.74% to 12.02%). Heat map analysis showed that the CO₂ emission fluxes at both the Lingqu and Darongjiang River sections were significantly positively correlated with the relative abundances of the CL500-29 marine group (P<0.01) and the hgcI clade (P<0.01). Conversely, emissions were significantly negatively correlated with the relative abundance of Pseudomonas (P<0.01). (4) Ecological network analysis shows that the number of nodes, the total number of edges, and the modularity index of the Lingqu River section network are all lower than those of the Darongjiang River section. This indicates that the interactions among bacteria in the KA are weaker, the community structure is unstable, and the ecosystem is more fragile. Therefore, both biological factors (such as the CL500-29 marine group, hgcI clade, and Pseudomonas) and abiotic factors (such as pH, DOC, and TN) jointly regulate the CO₂ emission process of the Lijiang River. To maintain a low CO₂ emission at the water-air interface, interference to the river ecosystem in the KA should be minimized as much as possible. This study analyzes the CO₂ emissions and microbial communities at the water-air interface of the river in the KA (the Lingqu River section) and the NKA (the Darongjiang River section) of the upper reaches of the Lijiang River. The research shows that the CO₂ emission flux in the KA basin is relatively low and reveals differences in the community structure and stability of microorganisms between these two areas.
- the Lingqu River /
- the Darongjiang River /
- CO₂ emission /
- bacterial community /
- Dissolved Organic Carbon

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图 1 研究区土地类型及样点分布

Figure 1. Distribution of land types and sampling points in the study area

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图 2 灵渠和大溶江三个水文期48 h内CO₂排放通量

Figure 2. CO₂ emission fluxes within 48 hours during three hydrolo-gical periods of the Lingqu River and the Darongjiang River

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图 3 灵渠和大溶江三个水文期48 h内CO₂排放总量

Figure 3. Total CO₂ emissions within 48 hours in three hydrolo-gical periods of the Lingqu River and the Darongjiang River

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图 4 灵渠和大溶江细菌属水平上的相对丰度

Figure 4. Relative abundances of bacteria at genus level in the Lingqu River and the Darongjiang River

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图 5 灵渠（a）、大溶江（b）和灵渠+大溶江（c）在属水平上的优势细菌与理化特征的相关性

注：*表示数据在0.05水平上显著相关，**表示在0.01水平上显著相关。

Figure 5. Correlations between dominant bacteria at genus level and physicochemical properties in the Lingqu River(a), the Darongjiang River(b) and Lingqu + Darongjiang Rivers (c)

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图 6 灵渠和大溶江细菌OTUs与理化特性的共现网络关系

注：不同颜色节点表示不同物种的属分类水平和理化特征，节点大小表示物种连接度大小，红色连线表示正相关边，绿色连线表示负相关边。

Figure 6. Co-occurrence network relationship between bacteria at the OTUs level and physicochemical properties in the Lingqu River and the Darongjiang River

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表 1 灵渠和大溶江水体的理化特征

Table 1. Physicochemical properties of water bodies in the Lingqu River and the Darongjiang River

时期	样点	时间	T	pH	EC	DO	Ca²⁺	Mg²⁺	K⁺	Na⁺	${\rm{HCO}}_3^{-}$	TN	TP	Chl-a	COD_Mn	DOC	${\rm{NO}}_3^{-}$-N	NH$_4^{+}$-N
时期	样点	时间	/℃	pH	/μS·cm⁻¹	/mg·L⁻¹	mg·L⁻¹	/mg·L⁻¹	/mg·L⁻¹	/mg·L⁻¹	/mmol·L⁻¹	/mg·L⁻¹	/mg·L⁻¹	/ug·L⁻¹	/mg·L⁻¹	/mg·L⁻¹	/mg·L⁻¹	/mg·L⁻¹
丰水期	灵渠	昼	25.96±0.49c	7.09±0.07b	276.10±1.12a	7.39±1.56b	48.35±0.05a	2.55±0.07a	1.97±0.05a	1.69±0.05b	1.82±0.06a	1.67±0.17a	0.04±0.01a	0.24±0.00b	2.61±0.10a	6.41±1.61a	1.24±0.01e	0.12±0.00a
	灵渠	夜	26.68±0.33b	7.04±0.03b	260.73±1.08b	11.42±0.41a	43.50±0.02b	2.45±0.02b	1.83±0.02a	1.60±0.04c	1.92±0.02a	1.50±0.10b	0.03±0.00a	0.18±0.00b	2.76±0.31a	5.61±1.72a	1.13±0.01f	0.10±0.01c
	大溶江	昼	29.14±0.17a	7.36±0.05a	131.43±0.09c	8.00±0.35b	22.30±0.03c	2.32±0.05c	1.24±0.03b	0.76±0.06d	0.92±0.06b	1.83±0.19a	0.03±0.01a	0.51±0.07a	3.03±0.16a	2.40±1.51b	1.44±0.02c	0.10±0.01b
	大溶江	夜	28.87±0.08a	7.35±0.03a	112.30±0.14d	7.96±0.16b	17.78±0.20d	2.02±0.03d	1.12±0.20b	0.51±0.00f	0.91±0.02b	1.67±0.04a	0.02±0.00b	0.46±0.02a	2.73±0.25a	2.78±1.69a	1.42±0.00c	0.09±0.01d
枯水期	灵渠	昼	14.65±0.07d	7.92±0.01b	243.97±0.42a	7.57±0.03d	45.72±0.37a	2.11±0.01a	1.31±0.01b	1.22±0.01b	1.73±0.05b	2.18±0.04a	0.02±0.00a	0.30±0.00b	1.53±0.03b	5.15±0.28a	4.83±0.02a	0.01±0.00b
	灵渠	夜	14.85±0.03c	8.10±0.01a	237.97±0.12b	7.94±0.04c	44.83±0.44a	2.07±0.02b	1.32±0.01b	1.18±0.02c	1.83±0.03a	2.26±0.02a	0.03±0.01a	0.55±0.00a	1.63±0.05a	3.53±1.12a	4.79±0.01a	0.01±0.01b
	大溶江	昼	15.04±0.01b	7.33±0.01d	68.30±0.10c	9.28±0.04b	10.02±0.16b	1.31±0.01c	0.60±0.01c	1.04±0.02d	0.50±0.05c	1.10±0.07b	0.01±0.00b	0.59±0.00a	1.47±0.03b	1.05±0.20b	2.41±0.02c	0.01±0.00a
	大溶江	夜	15.24±0.00a	7.35±0.01c	67.43±0.05d	9.40±0.01a	9.60±0.11b	1.30±0.01c	0.59±0.00d	0.99±0.01e	0.45±0.00c	1.10±0.03b	0.01±0.00b	0.66±0.16a	1.46±0.00c	1.90±0.32b	2.42±0.04c	0.01±0.01b
平水期	灵渠	昼	14.96±0.02b	8.01±0.01b	195.90±0.14b	15.99±0.10b	39.33±0.13a	2.45±0.01a	0.75±0.01a	1.18±0.05c	1.55±0.13a	1.88±0.02b	0.11±0.01b	1.27±0.13a	1.53±0.03b	2.43±0.10b	1.72±0.00a	0.06±0.00c
	灵渠	夜	15.15±0.02a	8.18±0.03a	198.20±0.37a	17.15±0.16a	39.83±0.57a	2.48±0.01a	0.78±0.02a	1.17±0.02c	1.40±0.06a	2.33±0.01a	0.16±0.01a	1.12±0.00a	1.63±0.05a	2.15±0.03b	1.70±0.01b	0.06±0.00d
	大溶江	昼	13.23±0.02d	7.25±0.03c	67.90±0.14c	9.90±0.06c	9.86±0.44b	1.30±0.06b	0.44±0.00a	0.98±0.01e	0.40±0.00b	1.32±0.00d	0.09±0.01c	0.90±0.02b	1.47±0.03b	1.56±0.28d	1.25±0.00c	0.05±0.00e
	大溶江	夜	13.35±0.01c	7.17±0.01d	67.97±0.12c	9.79±0.02c	9.70±0.30b	1.25±0.04b	0.44±0.01a	1.28±0.05a	0.45±0.12b	1.38±0.01c	0.04±0.01d	0.80±0.11b	1.46±0.00c	1.80±0.09c	1.23±0.01c	0.07±0.00b
注：表中数据为平均值±标准差，不同字母表示灵渠和大溶江在0.05水平上差异显著，最大的平均数标记为a。

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表 2 灵渠和大溶江CO₂排放通量与理化特征的相关性

Table 2. Correlation between CO₂ emission fluxes and physicochemical properties in the Lingqu River and the Darongjiang River

CO₂排放通量	T	pH	EC	DO	Ca²⁺	Mg²⁺	K⁺	Na⁺
灵渠	0.650*	−0.699*	0.599*	−0.105	0.357	0.615*	0.476	0.524
大溶江	0.119	0.263	0.472	0.221	0.580*	0.434	0.354	0.413
灵渠+大溶江	0.384	−0.617**	0.114	−0.194	0.089	0.323	0.201	−0.012

CO₂排放通量	${\rm{HCO}}_3^{-}$	TN	TP	Chl-a	COD_Mn	DOC	${\rm{NO}}_3^{-}$-N	NH$_4^{+}$-N
灵渠	0.238	−0.706*	−0.175	−0.399	0.640*	0.559	−0.757**	0.615*
大溶江	0.419	0.739**	0.260	−0.151	0.407	0.713*	−0.441	0.751**
灵渠+大溶江	0.017	−0.225	−0.124	−0.318	0.450*	0.455*	−0.718**	0.599**
注：表示数据在0.05水平上显著相关，*表示在0.01水平上显著相关。

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表 3 灵渠和大溶江优势细菌与理化特征的网络关键拓扑参数

Table 3. Key network topological parameters of dominant bacteria and physicochemical properties in the Lingqu River and the Darongjiang river

参数	灵渠	大溶江	灵渠+大溶江
节点数	49	66	51
边数	462	952	644
网络直径	3	3	3
模块化	0.32	0.44	0.21
平均路径长度	1.63	1.60	1.62
图密度	0.39	0.44	0.51
平均聚类系数	0.72	0.73	0.69
正相关边数和占比/%	257	509	326
正相关边数和占比/%	55.63	53.47	50.62
负相关边数和占比/%	205	443	318
负相关边数和占比/%	44.37	46.53	49.38

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