Long-Term Heavy Metal Retention by Mangroves and Effect on Its Growth: A Field Inventory and Scenario Simulation

Anh Nguyen, Otto Richter, Bao V.Q. Le, Nguyen Thi Kim Phuong and Kim Chi Dinh
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Anh Nguyen: Institute for Environment and Resources, Vietnam National University Ho Chi Minh City, 142 To Hien Thanh, District 10, Ho Chi Minh City 72506, Vietnam
Otto Richter: Institute of Geoecology, Technical University of Braunschweig, 38106 Braunschweig, Germany
Bao V.Q. Le: Institute for Environment and Resources, Vietnam National University Ho Chi Minh City, 142 To Hien Thanh, District 10, Ho Chi Minh City 72506, Vietnam
Nguyen Thi Kim Phuong: National Institute of Applied Mechanics and Informatics, Vietnam Academy of Science and Technology, 291 Dien Bien Phu, District 3, Ho Chi Minh City 722007, Vietnam
Kim Chi Dinh: Institute for Environment and Resources, Vietnam National University Ho Chi Minh City, 142 To Hien Thanh, District 10, Ho Chi Minh City 72506, Vietnam

IJERPH, 2020, vol. 17, issue 23, 1-24

Abstract: The ability of mangroves in taking up and storing heavy metal (HM) helps in reducing HM pollution. However, HMs likewise adversely affect the growth of mangroves. We assess the effects of the long-term soil HMs enrichment on the growth of Rhizophora apiculata forest in the Can Gio Mangrove Forest (Southern Vietnam) in different environmental conditions of soil salinity, ground elevation, and tree density based on a novel set of measured data. These data were analyzed and were used to calibrate and validate for a tree growth model with influencing factors salinity, elevation, tree density, and heavy metals content. Three scenario simulations were performed to predict the mangrove dynamics under different levels of heavy metal pollution in combined environmental conditions of salinity and elevation. Simulation results show the decline of total forest biomass from 1,750,000 tons (baseline scenario with no HM pollution) down to 850,000 tons and 350,000 tons for the current HM pollution and double HM pollution scenarios, respectively. Both data analysis and simulations have shown that although mangroves can assist in reducing HM pollution, the quality and health of this ecosystem will be severely affected if the environment is excessively polluted. In addition, a data-and-model driven management tool is devised for the sustainable management of the mangrove environmental resources.

Keywords: mangroves; mangrove modelling; Rhizophora apiculata; phytoremediation; heavy metal pollution (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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