2023年度深圳红树林植被群落结构数据集
收稿日期: 2025-02-28
录用日期: 2025-05-28
网络出版日期: 2025-09-28
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
Received date: 2025-02-28
Accepted date: 2025-05-28
Online published: 2025-09-28
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； DOI：10.57760/sciencedb.15120； |
| 经费支持 | 深圳市可持续发展科技专项（KCXST20221021111404011） |
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 . DOI: 10.19788/j.issn.2096-6369.100056
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 1st-August 31st 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; DOI：10.57760/sciencedb.15120; |
| Financial support | Shenzhen Sustainable Development Technology Special Project(KCXST20221021111404011). |
Key words： The Greater Bay Area; Shenzhen; Mangrove; Community Structure
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