会仙岩溶湿地底栖硅藻群落结构特征及水质评价

doi:10.16088/j.issn.1001-6600.2025111601

Abstract

Abstract: Huixian Karst Wetland, the largest karst wetland inlow-altitude regions of China, plays a crucial role in promoting the healthy circulation of ecosystems, regulating urban climate, and purifying the water quality of the Li River.Diatom indicesis used to evaluate the water ecological health status of HuixianKarst Wetland,and 16 representative sampling sites were established in July 2024 across the surface waters of the Shiziyan Underground River System (SZ), the Ancient Guiliu Canal (GL), the Muzong Lake Dispersed Discharge System Waters (ML), and the Muzong River (MR). The results indicated that: ① A total of 29 genera and 124 species of benthic diatoms were identified in the Huixian Karst Wetland, with three common dominant species across all water bodies. Nutrient-sensitive and eutrophication-preferred species, such asNitzschia palea andMelosira varians, were the primary dominant and indicator species in the wetland. ② Canonicalcorrespondence analysis (CCA) and Mantel test results indicated that total nitrogen (TN) and total phosphorus (TP) were the primary environmental factors influencing changes in the benthic diatom community in the Huixian Karst Wetland, with ammonia nitrogen (NH⁺₄-N), calcium ions (Ca²⁺), dissolved oxygen (DO), and conductivity (Cond) serving as important influencing factors. ③ Specific pollution sensitivity index (IPS), hurlimann trophic index (DI-CH), and trophic diatom index (TDI), selected through cluster analysis, non-metric multidimensional scaling (NMDS), and box plot analysis, can serve as reference biological indicators for water quality assessment in the Huixian Karst Wetland. ④ Comprehensive water quality evaluation based on the three indices revealed that the overall water quality of the Huixian Karst Wetland is poor, with only43.7% of sampling sites rated as “moderate” or “good”,while 56.3% were rated as “poor” or worse. The overall water quality status across different water bodies showed ML > MR ≈ SZ > GL.

Key words: water quality assessment, diatom indices, benthic diatom, community structure characteristics, environmental factors, Huixian Wetland, Guilin, China

CLC Number: X824;Q948.8

Lin Kang, Cai Desuo, Ma Xinyu, Yang Tao, Chen Yuzhi. Characteristics of benthic diatom community structure and water quality assessment in Huixian Karst Wetland, Guilin, China[J].Journal of Guangxi Normal University(Natural Science Edition), 2026, 44(5): 168-178.

References

[1] 李谊, 张敬一凡, 毕心怡, 等. 拉鲁湿地芦苇根际土壤真菌多样性、群落结构和功能预测[J]. 应用与环境生物学报,2026, 32(3): 467-479.DOI:10.19675/j.cnki.1006-687x.2025.06012.
[2] 李艳琼, 黄玉清, 徐广平, 等. 桂林会仙喀斯特湿地芦苇群落土壤养分及微生物活性[J]. 生态学杂志, 2018, 37(1): 64-74. DOI: 10.13292/j.1000-4890.201801.004.
[3] 黄宏伟, 李洁月, 王敦球, 等. 睦洞湖和古桂柳运河表层沉积物中汞和砷含量及其生态风险评价[J]. 湿地科学, 2019, 17(6): 676-681. DOI: 10.13248/j.cnki.wetlandsci.2019.06.010.
[4] 韦春伊, 徐保利, 马惠娟, 等. 不同连通类型对会仙湿地水质影响分析及评价[J]. 人民珠江, 2023, 44(2): 37-43, 69. DOI: 10.3969/j.issn.1001-9235.2023.02.005.
[5] 陈言, 张漓杉, 周如月, 等. 会仙岩溶湿地微塑料的时空分布特征及其影响因素[J]. 生态与农村环境学报, 2023, 39(7): 934-942. DOI: 10.19741/j.issn.1673-4831.2022.0752.
[6] 夏飞扬, 马冬冬, 张军, 等. 会仙湿地典型河流抗生素污染特征及风险评价[J]. 桂林理工大学学报, 2021, 41(1): 174-182. DOI: 10.3969/j.issn.1674-9057.2021.01.022.
[7] 孙小双. 会仙岩溶湿地动态变化分析及敏感性分析[D]. 邯郸: 河北工程大学, 2020.
[8] Stevenson J. Ecological assessments with algae: a review and synthesis[J]. Journal of Phycology, 2014, 50(3): 437-461. DOI: 10.1111/jpy.12189.
[9] Hirst H, Jüttner I, Ormerod S J. Comparing the responses of diatoms and macro-invertebrates to metals in upland streams of Wales and Cornwall[J]. Freshwater Biology, 2002, 47(9): 1752-1765. DOI: 10.1046/j.1365-2427.2002.00904.x.
[10] 张岚, 王坤, 王岚, 等. 潍河潍坊段底栖硅藻群落特征及水生态健康评价[J]. 应用与环境生物学报, 2025, 31(8): 1201-1213. DOI: 10.19675/j.cnki.1006-687x.2024.07028.
[11] 陈威, 张俊芳, 赵萍, 等. 三峡库区24条支流底栖硅藻群落结构的空间格局与评价[C]//中国水利学会2018学术年会论文集:第二分册.北京:中国水利水电出版社, 2018: 177-182. DOI: 10.26914/c.cnkihy.2018.017107.
[12] Venkatachalapathy R, Karthikeyan P. Application of diatom-based indices for monitoring environmental quality of riverine ecosystems: a review[M]//RamkumarM, Kumaraswamy K, Mohanraj R. Environmental management ofriver basin ecosystems. Cham: Springer International Publishing, 2015: 593-619. DOI: 10.1007/978-3-319-13425-3_28.
[13] Rimet F, Cauchie H M, Hoffmann L, et al. Response of diatom indices to simulated water quality improvements in a river[J]. Journal of Applied Phycology, 2005, 17(2): 119-128. DOI: 10.1007/s10811-005-4801-7.
[14] Coste M, Boutry S, Tison-Rosebery J, et al. Improvements of the biological diatom index (BDI): description and efficiency of the new version (BDI-2006)[J]. Ecological Indicators, 2009, 9(4): 621-650. DOI: 10.1016/j.ecolind.2008.06.003.
[15] SláDečEk V. Diatoms as indicators of organic pollution[J]. Acta Hydrochimica et Hydrobiologica, 1986, 14(5): 555-566. DOI: 10.1002/aheh.19860140519.
[16] Muscio C. The diatom pollution tolerance index: assigning tolerance values[R].Austin: Watershed Protection & Development Review Department, 2002:1-17.
[17] Kelly M G, Whitton B A. The trophicdiatom index: a new index for monitoring eutrophication in rivers[J]. Journal of Applied Phycology, 1995, 7(4): 433-444. DOI: 10.1007/bf00003802.
[18] Chessman B C, Bate N N, Gell P A, et al. A diatom species index for bioassessment of Australian rivers[J]. Marine and Freshwater Research, 2007, 58(6): 542. DOI: 10.1071/mf06220.
[19] 薛浩, 郑丙辉, 孟凡生, 等. 基于着生硅藻指数的梧桐河水生态健康评价[J]. 生态毒理学报, 2018, 13(4): 83-90.
[20] 薛浩, 孟凡生, 郑丙辉, 等. 硅藻指数在嫩江支流甘河的适用性评估[J]. 环境科学研究, 2020, 33(3): 617-625. DOI: 10.13198/j.issn.1001-6929.2019.12.04.
[21] 黎征武, 曹然, 毛建忠, 等. 适于北江水质生物评价的附着硅藻指数研究[J]. 生态环境学报, 2017, 26(2): 275-284. DOI: 10.16258/j.cnki.1674-5906.2017.02.013.
[22] 林永生, 刘金辉, 邹胜章, 等. 会仙岩溶湿地水体中多环芳烃的含量特征及健康风险评价[J]. 环境监测管理与技术, 2025, 37(3): 52-60. DOI: 10.19501/j.cnki.1006-2009.2025.03.001.
[23] 黄奇波, 邹胜章, 覃小群, 等. 桂林市会仙岩溶湿地水资源特征及有效调控[J]. 中国岩溶, 2023, 42(4): 722-732, 762.
[24] 李晖, 蒋忠诚, 马祖陆, 等. 桂林会仙岩溶湿地健康评价与补偿机制研究[J]. 中国水土保持, 2013(1): 61-64. DOI: 10.14123/j.cnki.swcc.2013.01.004.
[25] Krammer K, Lange-Bertalot H. Bacillariophyceae[M]. Berlin:Spektrum Akademischer Verlag Gmbh Heidelberg, 2000.
[26] 齐雨藻. 中国淡水藻志:第四卷硅藻门中心纲[M]. 北京: 科学出版社, 1995: 1-89.
[27] 齐雨藻. 中国淡水藻志: 第十卷硅藻门羽纹纲(无壳缝目拟壳缝目)[M]. 北京: 科学出版社, 2004: 1-130.
[28] 魏复盛. 水和废水监测分析方法[M]. 4版. 北京: 中国环境科学出版社, 2002.
[29] 苗蔚, 吴秋双, 欧延静, 等. 赤水河丰水期水生生物群落结构特征分析及水质评价[J]. 水利水电技术(中英文),2026, 57(3): 27-42. DOI: 10.13928/j.cnki.wrahe.2026.03.003.
[30] 张昆, 蔡德所, 林金城, 等. 硅藻指数在龙江与刁江流域生态健康评价中的应用[J]. 中国农村水利水电, 2021(4): 98-106. DOI: 10.3969/j.issn.1007-2284.2021.04.017.
[31] 单涛, 袁安龙, 黄子芮, 等. 拉林河流域底栖硅藻群落结构特征及水生态健康评价[J]. 环境科学, 2023, 44(3): 1465-1474. DOI: 10.13227/j.hjkx.202205168.
[32] 周景, 刘朔孺, 蔡德所, 等. 漓江水系底栖硅藻的水质评价[J]. 广西师范大学学报(自然科学版), 2012, 30(4): 123-129. DOI: 10.16088/j.issn.1001-6600.2012.04.011.
[33] 孙世鹏, 孔超, 陆欣鑫, 等. 暴雨期前后库里泡底栖硅藻群落结构变化及其环境因子相关性[J]. 海洋与湖沼, 2021, 52(1): 162-174.
[34] 张露, 李滔, 章叶飞, 等. 九岭山国家级自然保护区底栖硅藻群落结构特征及水质评价[J]. 生态学杂志, 2025, 44(2): 530-537. DOI: 10.13292/j.1000-4890.202502.010.
[35] 谢纯林. 赤水河流域底栖藻类群落结构特征及其水体富营养化评价[D]. 武汉: 中南民族大学, 2022.
[36] 王旭涛. 珠江水质生物监测与评价技术[M]. 北京: 中国水利水电出版社, 2020.
[37] Wu N C, Tang T, Qu X D, et al. Spatial distribution of benthic algae in the Gangqu River, Shangrila, China[J]. Aquatic Ecology, 2009, 43(1): 37-49. DOI: 10.1007/s10452-007-9153-8.
[38] 王倩, 支崇远, 康福星. 黔桂喀斯特区域河流水体离子对底栖硅藻群落的影响[J]. 环境科学学报, 2009, 29(7): 1517-1526. DOI: 10.13671/j.hjkxxb.2009.07.030.
[39] Neal C, House W A, Jarvie H P, et al. The water quality of the River Dun and the Kennet and Avon Canal[J]. Journal of Hydrology, 2006, 330(1/2): 155-170. DOI: 10.1016/j.jhydrol.2006.04.017.
[40] 曾鸿滨, 龙琦, 高景恒, 等. 机器学习在河流断面水质预测分析中的应用[J/OL]. 环境工程, 2025: 1-14. (2025-09-03).https://kns.cnki.net/KCMS/detail/detail.aspx?filename=HJGC20250901002&dbname=CJFD&dbcode=CJFQ.
[41] 李路祥, 李金城, 韦春满, 等. 广西会仙湿地水质现状分析与评价[J]. 桂林理工大学学报, 2019, 39(3): 693-699.
[42] 邢梦龙, 李海翔, 姜磊, 等. 临桂新区环城水系及会仙岩溶湿地水污染时空特征[J]. 桂林理工大学学报, 2019, 39(1): 168-176.
[43] 文云峰. 会仙岩溶湿地水体富营养化现状及对策研究[D]. 南宁: 广西大学, 2013.
[44] Trábert Z, Tihamér Kiss K, Várbíró G, et al. Comparison of the utility of a frequently used diatom index (IPS) and the diatom ecological guilds in the ecological status assessment of large rivers[J]. Fundamental and Applied Limnology, 2017, 189(2): 87-103. DOI: 10.1127/fal/2016/0933.
[45] 刘麟菲, 徐宗学, 殷旭旺, 等. 应用硅藻指数评价渭河流域水生态健康状况[J]. 北京师范大学学报(自然科学版), 2016, 52(3): 317-321. DOI: 10.16360/j.cnki.jbnuns.2016.03.011.
[46] 邓培雁, 雷远达, 刘威, 等. 七项河流附着硅藻指数在东江的适用性评估[J]. 生态学报, 2012, 32(16): 5014-5024. DOI: 10.5846/stxb201112071867.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 10

[1]	Tang Chenghua, Yi Jianbing, Wu Xin, Xiong Wenwu, Wang Jingyong. A review of cross-domain few-shot image semantic segmentation methods[J]. Journal of Guangxi Normal University(Natural Science Edition), 2026, 44(4): 1 -27 .
[2]	Tian Sheng, Xie Hualin, Chen Dong. Energy management strategy for fuel cell vehicles based on improved deep reinforcement learning[J]. Journal of Guangxi Normal University(Natural Science Edition), 2026, 44(4): 28 -45 .
[3]	Zhang Xu, Liu Didi. Intelligent charging/discharging scheduling strategy for electric vehicles based on TD3 algorithm[J]. Journal of Guangxi Normal University(Natural Science Edition), 2026, 44(4): 46 -55 .
[4]	Yan Yuanyang, Xie Lirong, Zhang Longjun, Ren Juan, Huang Chenchen, Hu Chao. Ultra-short-term wind power prediction model based on multi-objective optimization[J]. Journal of Guangxi Normal University(Natural Science Edition), 2026, 44(4): 56 -70 .
[5]	Lü Hui, Su Jing, Xiong Feng, Zhang Duanyu, Chang Wenhan, Wang Can, Ma Hui. Bi-level coordinated optimization scheduling method for microgrid clusters based on improved SAC algorithm[J]. Journal of Guangxi Normal University(Natural Science Edition), 2026, 44(5): 1 -15 .
[6]	Yang Zhen, Tang Yue, Geng Zhaojie, Yin Xu, Huang Yong. Giant magnetoimpedance biosensor based on composite amorphous wire for sensitive detection of cTnI[J]. Journal of Guangxi Normal University(Natural Science Edition), 2026, 44(5): 16 -26 .
[7]	Tian Peiyi, Jiang Pinqun, Song Shuxiang, Xia Haiying, Cai Chaobo. High-efficiency and fast-stabilizing boost charge pump controlled by multi-phase clock[J]. Journal of Guangxi Normal University(Natural Science Edition), 2026, 44(5): 27 -37 .
[8]	Chen Geng, Song Shuxiang, Jiang Pinqun, Cai Chaobo. Design of 12 bit 100 MS/s successive approximation analog-to-digital converter[J]. Journal of Guangxi Normal University(Natural Science Edition), 2026, 44(5): 38 -48 .
[9]	Suo Guidong, Lu Zhimin, Li Zili. EMD-YOLO: a PCB defect detection model based on improved YOLO11n[J]. Journal of Guangxi Normal University(Natural Science Edition), 2026, 44(5): 49 -62 .
[10]	Hu Zhiqiang, Lü Xiaoqi, Gu Yu. Skin lesion segmentation model based on improved Mamba local feature acquisition[J]. Journal of Guangxi Normal University(Natural Science Edition), 2026, 44(5): 63 -74 .

Characteristics of benthic diatom community structure and water quality assessment in Huixian Karst Wetland, Guilin, China

PDF (PC)

Abstract

Cite this article

share this article

References

Related Articles 3

Metrics

Comments

Recommended 10

[1]	YANG Haiju, WEI Feng, CHEN Jiamei, CHEN Bei, LI Fang, DU Lina, HAN Xuerong. Development of Biotic Index Based on Macroinvertebrates to Assess the River’s Health in Lijiang [J]. Journal of Guangxi Normal University(Natural Science Edition), 2024, 42(4): 172-185.
[2]	ZHANG Haoran. Benthic Diatom Assemblages Distribution in Longjiang and Diaojiang Rivers, in Relation to Chemical and Physiographical Factor [J]. Journal of Guangxi Normal University(Natural Science Edition), 2018, 36(1): 132-141.
[3]	ZHOU Jing, LIU Shuo-ru, CAI De-suo, ZHANG Yong-xiang, WANG Bei-xing. Water Quality Bioassessment with Benthic Diatom in Lijiang River, Guilin,China [J]. Journal of Guangxi Normal University(Natural Science Edition), 2012, 30(4): 123-129.