Issue |
E3S Web Conf.
Volume 200, 2020
The 1st Geosciences and Environmental Sciences Symposium (ICST 2020)
|
|
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Article Number | 02020 | |
Number of page(s) | 5 | |
Section | Environmental Management | |
DOI | https://doi.org/10.1051/e3sconf/202020002020 | |
Published online | 23 October 2020 |
Relationship analysis of vegetation structural properties and the aboveground carbon stock of mangrove forest
1
Master Program of Remote Sensing, Faculty of Geography, Universitas Gadjah Mada, Yogyakarta, Indonesia
2
Department of Geographic Information Science, Faculty of Geography, Universitas Gadjah Mada, Yogyakarta, Indonesia
* Corresponding author: m.kamal@ugm.ac.id
Mangrove forests have important ecological functions as a controller of environmental quality in coastal areas and absorber of atmospheric carbon. The mangrove ecosystem has a unique vegetation structure which form vegetation zonation that consists of different forest stands characteristics and tree species. This study aims to analyze the relationship between vegetation structural properties and the estimated aboveground carbon (AGC) stock of mangrove forest in Bedul mangrove, Banyuwangi, East Java, Indonesia. The study was conducted by field observation at some purposively selected sample locations. Field measurement was aimed to collect data about mangrove tree diameter at breast height (DBH), species, tree height, and fractional canopy cover. Mangrove biomass was indirectly calculated by allometric method based on mangrove species to estimate AGC in mangrove stands. The highest total AGC found in this study was 114.09 tons/ha at Rhizophora mucronata dominated forest, while the lowest total AGC was 12.86 tons/ha with Ceriops tagal as the dominant species. The AGC estimation in mangrove stands correlated positively with DBH and tree height. However, the biomass content and AGC are affected by the number of mangrove stands. The difference in the number of stands affect the amount of carbon content at each sample point.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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