2023年度深圳红树林植被群落结构数据集

doi:10.19788/j.issn.2096-6369.100056

Abstract

Abstract:

Currently, our country is striving to achieve the goal of carbon peaking. “Blue Carbon,” represented by mangrove wetlands, is an indispensable component in the field of carbon sink. In 2020, the Ministry of Natural Resources issued the “Special Action for Mangrove Conservation and Restoration (2020-2025),” and significant progress has been made in recent years. As a marine-centric city, Shenzhen boasts relatively abundant mangrove resources. A comprehensive investigation of the current status of typical coastal mangrove ecosystems and mangrove species is essential. This not only facilitates a better understanding of the species composition and community structure within the region but also allows for the evaluation of the achievements of mangrove conservation plans. Based on the geographical distribution and community structure of the city's mangroves, nine typical mangrove monitoring transects and 24 monitoring plots were selected in the summer of 2023. An area-weighted average method was utilized to determine the per-unit area biomass of the city’s mangrove vegetation, via unmanned aerial vehicles, combined with on-site inspections and fixed plot surveys. The above-ground plant biomass of Shenzhen's coastal mangrove was calculated using the allometric growth equation method, in conjunction with the results of plot surveys to get the determination of the distribution range and area of the mangrove forests along Shenzhen's coastline. Field measurements and recordings of various plant indices were conducted, along with on-site identification of plant species composition, to record community indices of the mangrove forests. Ultimately, the dataset was obtained. This dataset exhibits several characteristics: (1) It contains rich content, including the geographic coordinates of sampling points, biological information, community structure, and community characteristics. (2) It covers a wide geographical range, including all concentrated mangrove locations within the Shenzhen city area. (3) Field surveys and fixed plot sampling methods were employed, resulting in minimal errors. Utilizing this dataset enables the exploration of the governance and distribution status of mangrove wetlands in the Greater Bay Area. Furthermore, it can be integrated with investigations on carbon flux, carbon storage, water quality, and atmospheric conditions, which is of significant importance for ecological environmental monitoring and research.

Data summary:

Items	Description
Dataset name	A Dataset of Mangrove Vegetation Community Structure in Shenzhen of 2023
Specific subject area	Environmental Engineering, Ecology, Agronomy
Research topic	Mangrove Community Structure
Time range	June 1^st-August 31^st 2023
Geographical scope	The geographical range is 113.819-115.039°E, 22.469-22.773°N, the geographical area covers the areas of Shenzhen and Shanwei (Shenzhen-Shanwei Special Cooperation Zone) of Guangdong Province.
Data types and technical formats	.xls
Dataset structure	The dataset comprises 1 data file and 4 sheets, detailed as follows: (1) Contains latitude and longitude information for the 9 transects selected for this survey; (2) Contains biological information for the 24 monitoring plots selected for this survey, including distribution density, plant types, etc; (3) Provides information on the main mangrove plant communities for the 9 transects selected for this survey, including average plant height, average crown width, and diameter at breast height; (4) Presents the mangrove plant species list obtained from this survey in Shenzhen City, including 7 orders, 10 families, 13 genera, and 17 species.
Volume of dataset	36.5 KB
Key index in dataset	Monitoring point, Species name, Plant height, Crown breadth, Diameter at breast height, Branch diameter
Data accessibility	CSTR：31253.11.sciencedb.15120; https://cstr.cn/31253.11.sciencedb.15120 DOI：10.57760/sciencedb.15120; https://doi.org/10.57760/sciencedb.15120
Financial support	Shenzhen Sustainable Development Technology Special Project(KCXST20221021111404011).

Key words: The Greater Bay Area, Shenzhen, Mangrove, Community Structure

HUANG GuiSong, XIAO YouPeng, MAI YouQuan, SUN WenJun, LI XuXia, XU Xu, WANG WeiMin, WANG YuDong, HUANG ZhenGuo, WANG HaiPeng, CHEN YiMeng, LIN JunChuan, XU Wang. A Dataset of Mangrove Vegetation Community Structure in Shenzhen of 2023[J].Journal of Agricultural Big Data, 2025, 7(3): 400-409.

Figures/Tables 6

Table 1

Fig. 1

Table 2

Table 3

Fig. 2

Table 4

References 27

[1]	GIRI C, OCHIENG E, TIESZEN L L, et al. Status and distribution of mangrove forest of the world using earth observation satellite data. Global Ecology and Biogeography, 2011, 20(1):154-159. DOI: 10.1111/j.1466-8238.2010.00584.x.
[2]	DAS S, VINCENT J R. Mangrove protected villages and reduced death toll during Indian super cyclone. Proceedings of the National Academy of Sciences of the United States of America, 2009, 106(18):7357-7360. DOI: 10.1073/pnas.0810440106.
[3]	POLIDORO B A, CARPENTER K E, COLLINS L, et al. The loss of species: mangrove extinction risk and geographic areas of global concern. PLoS One, 2010, 5(4):e10095. DOI: 10.1371/journal.pone.0010095.
[4]	李皓宇, 彭逸生, 刘嘉健, 等. 粤东沿海红树林物种组成与群落特征. 生态学报, 2016, 36(1):252-260. DOI: 10.5846/stxb201408031548.
	LI H Y, PENG Y S, LIU J J, et al. Current state of mangrove floristic composition and characteristics of communities on the eastern coast of Guangdong Province. Acta Ecologica Sinica, 2016, 36(1):252-260. DOI: 10.5846/stxb201408031548.
[5]	BOUILLON S, BORGES A V, CASTAÑEDA-MOYA E, et al. Mangrove production and carbon sinks: a revision of global budget estimates. Global Biogeochemical Cycles, 2008, 22(2): GB2013. DOI: 10.1029/2007gb003052.
[6]	WANG B S, LIANG S C, ZHANG W Y, et al. Mangrove flora of the world. Acat Botanica Sinica, 2003, 45(6):644-653.
[7]	常云蕾, 廖静娟, 张丽. 全球红树林时空变化及演变趋势. 生态学报, 2024, 44(9):3830-3843. DOI: 10.20103/j.stxb.202304220838.
	CHANG Y L, LIAO J J, ZHANG L. Spatio-temporal changes and trends of global mangroves. Acta Ecologica Sinia, 2024, 44(9):3830-3843. DOI: 10.20103/j.stxb.202304220838.
[8]	王日明, 梁喜幸, 周晓妍. 钦江河口潮滩红树林群落空间分布. 遥感学报, 2022, 26(6):1143-1154. DOI: 10.11834/jrs.20221540
	WANG R M, LIANG X X, ZHOU X Y, et al. Spatial distribution pattern of mangrove community in tidal flats of the Qinjiang Estuaty. National Remote Sensing Bulletin, 2022, 26(6):1143-1154. DOI: 10.11834/jrs.20221540.
[9]	李德玲, 曾德华, 王炳宇, 等. 三亚市红树林群落分布特征及物种多样性研究. 安徽农业科学, 2023, 51(21): 131-133. DOI: 10.3969/j.issn.0517-6611.2023.21.029.
	LI D L, ZENG D H, WANG B Y, et al. Study on the distribution characteristics and species diversity of mangrove communities in Sanya City. Journal of Anhui Agricultural Sciences, 2023, 51(21): 131-133. DOI: 10.3969/j.issn.0517-6611.2023.21.029.
[10]	邓秋香, 郭国, 潘良浩. 广西北海滨海国家湿地公园红树林植物群落调查与分析. 广西林业科学, 2022, 51(3):388-393. DOI: 10.19692/j.issn.1006-1126.20220314.
	DENG Q X, GUO G, PAN L H. Investigation and analysis on mangrove plant communities in Guangxi Beihai Coastal National Wetland Park. Guangxi Forestry Science, 2022, 51(3):388-393. DOI: 10.19692/j.issn.1006-1126.20220314.
[11]	唐秋霞, 王友绍. 雷州半岛红树林群落特征及其分布格局. 生态科学, 2021, 40(5):23-32.
	TANG Q X, WANG Y S. Characteristics and distribution pattern of mangrove community in the Leizhou Peninsula. Ecological Science, 2021, 40(5):23-32.
[12]	张崧, 王建国, 陈晓茜, 等. 深圳福田红树林湿地浮游植物群落结构及影响因素研究. 南方水产科学, 2025, 21(2):70-80. DOI: 10.12131/20240184.
	ZHANG S, WANG J G, CHEN X Q, et al. Research on phytoplankton community structure and its influencing factors in mangrove wetlands of Futian, Shenzhen. South China Fisheries Science, 2025, 21(2):70-80. DOI: 10.12131/20240184.
[13]	褚艳玲, 张千湖, 张丽, 等. 未来海平面变化对红树林空间分布的影响分析——以深圳市为例. 湿地科学与管理, 2025, 21(1):19-25+51. DOI: 10.3969/j.issn.1673-3290.2025.01.04.
	ZHE Y L, ZHANG Q H, ZHANG L, et al. Analysis of the impact of future sea level changes on the spatial distribution of mangrove forest: A case study of Shenzhen City. Wetland Science & Management, 2025, 21(1):19-25+51. DOI: 10.3969/j.issn.1673-3290.2025.01.04.
[14]	洪冉, 张烨, 宋迎春, 等. 深圳福田红树林湿地沉积物与凋落叶小型底栖动物的群落特征. 中国海洋大学学报, 2025, 55(2):57-66. DOI: 10.16441/jc.nki.hdxb.20230062.
	HONG R, ZHANG Y, SONG Y C, et al. Community characteristics of meiofauna in sediment and on leaf litter of Futian Mangrove Wetland, Shenzhen. Periodical of Ocean University of China, 2025, 55(2):57-66. DOI: 10.16441/jc.nki.hdxb.20230062.
[15]	巫金敏. 深圳东涌红树林湿地植物资源特征与生态修复策略研究. 乡村科技, 2024, 15(15):137-139.
	WU J M. Research on the characteristics of plant resources and ecological restoration strategies of the mangrove wetland in Dongchong, Shenzhen. Rural Science and Technology, 2024, 15(15):137-139.
[16]	TAM N F Y, WONG Y S, LAN C Y, et al. Community structure and standing crop biomass of a mangrove forest in Futian Nature Reserve, Shenzhen, China. Hydrobiologia, 1995, 295(1):193-201. DOI: 10.1007/BF00029126.
[17]	KOMIYAMA A, POUNGPARN S, KATO S. Common allometric equations for estimating the tree weight of mangrove. Journal of Tropical Ecology, 2005, 21(4):471-477. DOI: 10.1017/s0266467405002476.
[18]	胡懿凯, 徐耀文, 薛春泉, 等. 广东省无瓣海桑和林地土壤碳储量研究. 华南农业大学学报, 2019, 40(6):95-103. DOI: 10.7671/j.issn.1001-411X.201810008.
	HU Y K, XU Y W, XUE C Q, et al. Studies on carbon storage of Sonneratia apetala forest vegetation and soil in Guangdong Province. Journal of South China Agricultural University, 2019, 40(6):95-103. DOI: 10.7671/j.issn.1001-411X.201810008.
[19]	CLOUGH B F, SCOTT K. Allometric relationships for estimating above-ground biomass in six mangrove species. Forest Ecology and Management, 1989, 27(2):117-127. DOI: 10.1016/0378-1127(89)90034-0.
[20]	吴德邻. 广东植物志[M]. 广州: 广东科技出版社, 2011.
	WU D L, Flora of Guangdong[M]. Guangzhou: Guangdong Science & Technology Press, 2011.
[21]	Global Mangrove Alliance. The state of the world`s mangroves 2022[R]. https://www.wetlands.org/publication/the-state-of-the-worlds-mangroves-2022/, 2022.
[22]	侯宽昭, 何椿年. 中国红树科志. 植物分类学报, 1952, 2(2):133-158.
	HOW F C, HO C N. Rhizophoraceae in the Chinese Flora. Acta Phytotaxonomica Sinica, 1952, 2(2):133-158.
[23]	HY/T 081—2005. 红树林生态监测技术规程[S]. 北京: 国家海洋局, 2005.
	HY/T 081-2005. Technical specification for eco-monitoring of mangrove ecosystem[S]. Beijing: State Oceanic Administration, 2005.
[24]	全国林业碳汇计量监测技术指南(试行)[S]. 北京: 国家林业局调查规划设计院, 2011.
	National Technical Guidelines for Forestry Carbon Sink Measurement and Monitoring (Trial)[S]. Beijing: Survey & Planning Institute of State Forestry Administration, 2011.
[25]	STEPHEN C, MICHWLLE O, IGINO E, et al. Guiding principles for delivering coastal wetland carbon projects[M]. United Nations Environment Programme (UNEP), 2014.
[26]	陈鹭真, 卢伟志, 林光辉(译). 滨海蓝碳:红树林、盐沼、海草床碳储量和碳排放因子评估方法[M]. 厦门: 厦门大学出版社, 2018.
	CHEN L, LU Z, LIN G(trans). Coastal blue carbon: Method for assessing carbon stocks and emissions factors in mangroves, tidal salt marshes, and seagrass meadows[M]. Xiamen: Xiamen University Press, 2018.
[27]	GB 17378.2—2007. 海洋监测规范第2部分:数据处理与分析质量控制[S]. 北京: 中华人民共和国国家质量监督检验检疫总局, 2007.
	GB 17378.2—2007. The specification for marine monitoring-Part 2: Data processing and quality control of analysis[S]. Beijing: General Administration of Quality Supervision, Inspection and Quarantine of the People`s Republic of China, 2007.

序号	样地代码	计划经度（°E）	计划纬度（°N）	监测日期
1	SZTC1-01	114.000052	22.529411	2023/7/6
2	SZTC1-02	113.999883	22.529116	2023/7/6
3	SZTC1-03	113.999695	22.528780	2023/7/6
4	SZTC1-04	114.012621	22.524148	2023/6/24
5	SZTC1-05	114.012451	22.524002	2023/6/24
6	SZTC1-06	114.012284	22.523842	2023/6/24
7	SZTC1-07	114.025896	22.519743	2023/7/12
8	SZTC1-08	114.019835	22.521930	2023/7/12
9	SZTC1-09	114.019402	22.520664	2023/7/12
10	SZTC2-01	113.949354	22.506136	2023/8/3
11	SZTC2-02	113.949220	22.506289	2023/8/3
12	SZTC2-03	113.949099	22.507016	2023/8/3
13	SZTC3-01	113.984253	22.532698	2023/7/21
14	SZTC4-01	114.032205	22.508954	2023/7/14
15	SZTC4-02	114.031333	22.508229	2023/7/14
16	SZTC4-03	114.031416	22.507774	2023/7/14
17	SZTC5-01	113.831536	22.590526	2023/8/1
18	SZTC5-02	113.831287	22.591113	2023/8/1
19	SZTC6-01	113.769246	22.747042	2023/7/12
20	SZTC7-01	114.574687	22.494311	2023/7/6
21	SZTC7-02	114.574365	22.494296	2023/7/6
22	SZTC8-01	114.513114	22.650587	2023/6/27
23	SZTC8-02	114.509493	22.648628	2023/6/27
24	SZTC9-01	115.038172	22.772183	2023/7/26

物种		分类			调查方式
中文名	拉丁名	目	科	属	调查方式
秋茄	Kandelia obovata	桃金娘目	红树科	秋茄树属	样方调查
木榄	Bruguiera gymnorrhiza	桃金娘目	红树科	木榄属	样方调查
海莲	Bruguiera sexangula	桃金娘目	红树科	木榄属	样点调查
红海榄	Rhizophora stylosa	桃金娘目	红树科	红树属	样点调查
红树	Rhizophora apiculata	桃金娘目	红树科	红树属	样点调查
小花木榄	Bruguiera parviflora	桃金娘目	红树科	木榄属	样点调查
海桑	Sonneratia caseolaris	桃金娘目	海桑科	海桑属	样方调查
无瓣海桑	Sonata apetala	桃金娘目	海桑科	海桑属	样方调查
玉蕊	Barringtonia racemosa	桃金娘目	玉蕊科	玉蕊属	样点调查
白骨壤	Avicennia marina	管状花目	马鞭草科	海榄雌属	样方调查
许树	Clerodendrum inerme	管状花目	马鞭草科	大青属	样点调查
老鼠簕	Acanthus ilicifolius	管状花目	爵床科	老鼠簕属	样方调查
桐花树	Aegiceras conialatum	报春花目	紫金牛科	蜡烛果属	样方调查
海漆	Excoecaria agallocha	大戟目	大戟科	海漆属	样方调查
银叶树	Heritiera littoralis	锦葵目	梧桐科	银叶树属	样方调查
卤蕨	Acrostichum aureum	水龙骨目	凤尾蕨科	卤蕨属	样方调查
水椰	Rhizophora apiculata	初生目	棕榈科	水椰属	样点调查

样点	主要物种	平均株高(m)	平均冠幅(m)	平均胸（基）径(cm)
福田红树林保护区	秋茄	5.58±1.18	3.78±2.11	10.46±3.71
	木榄	3.35±1.03	3.60±1.55	5.13±2.71
	无瓣海桑	9.43±4.75	9.31±9.03	18.92±14.52
	桐花树	2.52±0.59	1.80±1.13	3.61±2.07
	白骨壤	5.50±1.12	4.09±2.02	19.99±5.52
	海桑	3.30±0.17	2.00±0.40	4.99±0.49
南山深圳人才公园	无瓣海桑	8.38±3.07	6.69±1.80	23.14±10.55
南山深圳人才公园	桐花树	1.27±0.22	0.93±0.33	5.68±2.36
南山华侨城湿地公园	秋茄	6.64±0.87	4.88±0.80	12.85±4.19
南山华侨城湿地公园	桐花树	2.85±0.49	2.55±0.21	5.57±1.13
福田红树林生态公园	秋茄	2.68±1.03	1.68±1.03	4.63±3.77
	木榄	1.85±0.32	1.16±0.43	3.96±1.35
	桐花树	1.39±0.34	1.55±0.46	3.70±1.07
	卤蕨	1.69±0.25	2.39±0.50	--
宝安西湾红树林公园	秋茄	4.91±1.07	4.74±1.06	11.30±4.11
宝安西湾红树林公园	无瓣海桑	9.77±2.24	10.00±2.80	30.75±8.31
宝安东宝河河口	无瓣海桑	12.14±3.21	4.50±0.85	10.25±6.23
大鹏东涌红树林湿地公园	海漆	3.70±0.79	3.34±0.87	10.39±3.71
大鹏东涌红树林湿地公园	桐花树	2.28±0.27	1.51±0.61	5.35±1.58
大鹏坝光红树林湿地公园	银叶树	11.58±2.73	9.16±2.66	44.60±27.51
大鹏坝光红树林湿地公园	白骨壤	3.60±0.71	4.10±0.95	9.64±2.22
深汕小漠渔港码头	白骨壤	2.48±0.81	2.59±1.04	8.12±2.79
深汕小漠渔港码头	桐花树	1.80±0.31	1.06±0.41	3.30±0.53

主要物种	地上生物量	地下生物量	来源文献
秋茄	W_AGB=651.63（D²H）^1.053	W_BGB=271.02（D²H）^0.990	TAM等, 1995[16]
海桑	W_AGB= 0.119 D^2.46	W_BGB=0.102D^2.22	KOMIYAMA等, 2005[17]
木榄	W_AGB=0.186D^2.31	W_BGB=0.4697D^1.5541	CLOUGH等, 1989[19]
无瓣海桑	W_AGB= 0.034（D²H）^0.966	W_BGB=0.003（D²H）^1.119	胡懿凯等, 2019[18]
桐花树	W_AGB= 31.34（D²H）^0.465	W_BGB= 9.33（D²H）^0.303	TAM等, 1995[16]
白骨壤	W_AGB=123.59(D²H)^0.529	W_BGB=22.96(D²H)^0.615	TAM等, 1995[16]
海漆	W_AGB= 0.1029D^2.46	W_BGB= 0.08928D^2.22	KOMIYAMA等, 2005[17]
银叶树	W_AGB= 0.2108D^2.46	W_BGB= 0.1701D^2.22	KOMIYAMA等, 2005[17]

A Dataset of Mangrove Vegetation Community Structure in Shenzhen of 2023

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