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

农业大数据学报 ›› 2025, Vol. 7 ›› Issue (3): 400-409.doi: 10.19788/j.issn.2096-6369.100056

2023年度深圳红树林植被群落结构数据集

黄桂松¹^,³^,⁴(), 肖佑鹏¹^,²^,^*(), 麦有全¹^,³^,⁴, 孙文郡¹^,³^,⁴, 黎栩霞¹^,³^,⁴, 徐旭¹^,³^,⁴, 王伟民¹^,³^,⁴, 王裕东¹^,³^,⁴, 黄振国¹^,³^,⁴, 王海鹏¹^,³^,⁴, 陈伊梦¹^,³^,⁴, 林俊川¹^,³^,⁴, 许旺¹^,³^,⁴^,^*()

1.广东省深圳生态环境监测中心站，广东深圳 518049
2.广东省农业技术推广中心，广州 510520
3.广东大湾区区域生态环境变化与综合治理国家野外科学观测研究站，广东深圳 518049
4.国家环境保护快速城市化地区生态环境科学观测研究站，广东深圳 518049

收稿日期:2025-02-28 接受日期:2025-05-28 出版日期:2025-09-26 发布日期:2025-09-28
通讯作者: 肖佑鹏，E-mail：576156305@qq.com；
许旺，E-mail：495081498@qq.com。
作者简介:黄桂松，E-mail：737779262@qq.com。
基金资助:
深圳市可持续发展科技专项(KCXST20221021111404011)

A Dataset of Mangrove Vegetation Community Structure in Shenzhen of 2023

HUANG GuiSong¹^,³^,⁴(), XIAO YouPeng¹^,²^,^*(), MAI YouQuan¹^,³^,⁴, SUN WenJun¹^,³^,⁴, LI XuXia¹^,³^,⁴, XU Xu¹^,³^,⁴, WANG WeiMin¹^,³^,⁴, WANG YuDong¹^,³^,⁴, HUANG ZhenGuo¹^,³^,⁴, WANG HaiPeng¹^,³^,⁴, CHEN YiMeng¹^,³^,⁴, LIN JunChuan¹^,³^,⁴, XU Wang¹^,³^,⁴^,^*()

1. Shenzhen Ecological and Environmental Monitoring Center of Guangdong Province, Shenzhen 518049, Guangdong, China
2. Agro-Tech Extension Center of Guangdong Province, Guangzhou 510520, China
3. Guangdong Greater Bay Area, Change and Comprehensive Treatment of Regional Ecology and Environment, National Observation and Research Station, Guangzhou 510630, China
4. State Environmental Protection Scientific Observation and Research Station for Ecology and Environment of Rapid Urbanization Region, Shenzhen 518049, China

Received:2025-02-28 Accepted:2025-05-28 Published:2025-09-26 Online:2025-09-28

摘要/Abstract

摘要：

我国目前正在努力完成碳达峰的目标，以红树林湿地为代表的“蓝碳”正是碳汇领域不可或缺的一部分。2020年，自然资源部印发了《红树林保护修复专项计划行动（2020-2025）》，近年来取得良好成效，深圳作为海洋中心城市，红树林资源相对较为丰富，对典型海岸带红树林生态系统基本状况及红树林物种的全面调查既能够更好的了解区域内的物种群落结构组成，还能够评估红树林养护计划的成果。根据本市红树林地理分布和群落结构，于2023年夏季选取了9条典型红树林监测样点，24个样地。通过无人机，结合现场踏查和固定样方调查的方式，采用面积加权平均法求得全市红树林的单位面积植被生物量。地上植物生物量通过异速生长方程法，结合样方调查结果计算深圳海岸带红树林的分布范围和面积。通过现场测量和记录不同植株指标，同时通过现场鉴定植物种类组成等记录群落指标，得到本数据集。本数据集包含以下几个特点：（1）本数据集内容较为充实，涵盖样点的经纬度、样点的生物信息、群落结构、群落特征；（2）提供的区域范围较广，涵盖了整个深圳市域所有红树林集中存在的点位；（3）采用实地踏查、固定样方的调查方式，误差较小。利用本数据集可以发掘大湾区红树林湿地的分布和治理现状，并且可与碳通量、碳储量的调查，或水质、大气的环境调查相结合，对生态环境监测调查研究具有重要意义。

数据摘要：

项目	描述
数据集名称	2023年度深圳红树林植被群落结构数据集
所属学科	环境工程，生态学，农学
研究主题	红树林群落结构
数据时间范围	2023年6月1日-8月31日
数据地理空间覆盖	地理范围为113.819－115.039°E，22.469－22.773°N，地理区域范围涉及的地区为广东省深圳市和汕尾市（深汕特别合作区）
数据类型与技术格式	.xls
数据库（集）组成	数据集共包含1个数据文件，4个表单：（1）9个样点的经纬度信息；（2）24个监测样方的生物信息，包括了分布密度、植物类型等；（3）9个样点主要红树植物群落信息，包括平均株高、平均冠幅和胸径；（4）调查得到的深圳市红树林植物名录，共包含7个目10个科13个属17个种。
数据量	36.5 KB
主要数据指标	监测点位、物种名、株高、冠幅、胸（基）径
数据可用性	CSTR：31253.11.sciencedb.15120； https://cstr.cn/31253.11.sciencedb.15120 DOI：10.57760/sciencedb.15120； https://doi.org/10.57760/sciencedb.15120
经费支持	深圳市可持续发展科技专项（KCXST20221021111404011）

关键词: 大湾区, 深圳, 红树林, 群落结构

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

黄桂松, 肖佑鹏, 麦有全, 孙文郡, 黎栩霞, 徐旭, 王伟民, 王裕东, 黄振国, 王海鹏, 陈伊梦, 林俊川, 许旺. 2023年度深圳红树林植被群落结构数据集[J]. 农业大数据学报, 2025, 7(3): 400-409.

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.

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参考文献 27

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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]

2023年度深圳红树林植被群落结构数据集

A Dataset of Mangrove Vegetation Community Structure in Shenzhen of 2023

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