Journal of Marine Science and Technology

Journal of Marine Science and Technology

Estimation of production and carbon stock of Gowatr mangrove forests, Gulf of Oman using PnET-CN model

Document Type : Original Manuscript

Authors
Matin Khaleghi 1
Ahmad Savari 2
Alireza Safahieh 2
Mohsen Hamidian pour 3
Sadroddin Ghaemmaghami 2
1 Department of Marine Biology, Faculty of Marine Science, Chabahar University of Maritime and Marine Science, Chabahar, Iran.
2 Department of Marine Biology, Faculty of Marine Science and Oceanography, Khorramshahr University of Marine Sciences and Technology, Khorramshahr, Iran.
3 Department of Physical Geography, Faculty of Geography and Environmental Planning, University of Sistan and Baluchestan, Zahedan, Iran.
10.22113/jmst.2020.217237.2346
Abstract
 
This study was carried out in the Gowatr mangrove forests in Gulf of Oman, on September 2017 and May 2018 during high tide with the aim of quantifying production, biomass carbon stocks of Avicennia marina and introduce of PnET-CN model. The results were showed that the mean of aboveground biomass was 28.09 ± 4.52 and 28.51 ± 4.49 t/ha, moreover, the mean of aboveground carbon stock was 11.22 ± 1.83 and 11.34 ± 1.7 t/ha, and the mean of primary production was 219.251 and 238.171 gC/m2.mo in September 2017 and May 2018, respectively. The estimated of the production and biomass carbon stocks using PnET-CN model was showed that the mean of production was 289.051 and 291.487 gC/m2.mo and the mean of aboveground biomass carbon was 12.29 and 12.76 t/ha in September 2017 and May 2018, respectively. The PnET-CN model could predict the effects of simultaneous changes in several environmental variables on the interactions among several ecosystem processes and it could estimate the amount of tree carbon stock and primary production with proper validation. PnET-CN model shown ecosystem models extended our understanding of the forest carbon cycle spatially and temporally and generated additional information about carbon stocks and fluxes.
 

INTRODUCTION

Mangrove forest ecosystem is known to possess various benefits including high carbon sequestration rates and storage. Deforestation or disturbance of these ecosystems results in large emissions of CO2 to the atmosphere. Therefore, it is suggested that mangrove forests are an important component in reducing the emissions of greenhouse gases resulting from deforestation and climate change, and consequently require scrupulous quantification of ecosystem carbon stocks to monitor temporal carbon sequestration and emissions. However, little is known about the carbon stocks of these ecosystems.
 

MATERIALS AND METHODS

This study was carried out in the mangrove forests of Gowatr Bay, Gulf of Oman, with the aim of quantifying carbon stocks of all components of this forest, including live and dead trees, soil, pneumatophores, herbaceous, and litter in three stations. Overall, 27 plots, each of which has an area of 154 m2 were evaluated in September 2017 and May 2018. The estimation of carbon stock in this ecosystem was done using the PnET-CN model.
 

RESULTS

The mean of aboveground biomass was 28.09 ± 4.52 and 28.51 ± 4.49 t/ha in September 2017 and May 2018, respectively. The mean of aboveground carbon stock was 11.22 ± 1.83 and 11.34 ± 1.7 t/ha in September 2017 and May 2018, respectively. The mean of primary production was 219.251 and 238.171 gC/m2.mo in September 2017 and May 2018, respectively.
The result of the PnET-CN model showed that the mean aboveground carbon stock was 12.29 and 12.77t/ha in September 2017 and May 2018, respectively. The mean primary production was 289.051 and 291.487 gC/m2.mo in September 2017 and May 2018, respectively.
 

DISCUSSION AND CONCLUSION

This reveals that Gowatr mangrove forest stores substantial amount of atmospheric carbon, and therefore needs to be conserved and sustainably managed. Also, the development of models was conducted for all components of tree instead of the direct measurement of tree biomass and carbon stock in the future, which are costly, time-consuming, damaging, and sometimes unavailable.
The estimation of the biomass and carbon stocks was carried out using the PnET-CN model to predict the effects of simultaneous changes in several environmental variables on the interactions of several critical ecosystem processes. Moreover, it could estimate the amount of tree carbon stock and primary production with proper validation. PnET-CN model showed that ecosystem models extended our understanding of the forest carbon cycle spatially and temporally and generated additional information about carbon stocks and fluxes.
 

REFERENCES

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Keywords
Avicennia marina
Gulf of Oman
Climate change
Modeling

Subjects

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Journal of Marine Science and Technology
Volume 23, Issue 4
Autumn 2024
Pages 99-112

  • Receive Date 26 January 2020
  • Revise Date 10 March 2020
  • Accept Date 15 March 2020
  • Publish Date 21 November 2024