DOI: 10.57760/sciencedb.15120
title: A dataset of Shenzhen Mangrove Community Structure in Guangdong Greater Bay Area Station in 2023
title: 2023年广东大湾区站深圳红树林群落结构数据集

description: 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 recent year. 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.
description: 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 recent year. 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.