Mangrove blue carbon dynamics in response to land-use and land-cover change
Mangrove is one of most efficient natural carbon sink forests in the tropic and subtropic regions. Removing mangrove forests generates carbon emissions and ends the ability of mangroves to capture atmospheric greenhouse gas emissions.
Mangrove forests hold substantial amounts of organic carbon — known as blue carbon — compared to other types of forests. Mangrove blue carbon is stored in the form of vegetation biomass, dead downed wood and in the soil.
Mangrove forests are found in the inter-tidal zone, and frequent tidal inundation creates anoxic conditions in the soil, resulting in minimal decomposition and mineralization, and eventually preserving the buried organic matter-rich sediments over thousands of years. The ability of mangroves to act as a long-term store of atmospheric carbon makes this ecosystem one of the most efficient nature-based climate change mitigation options.
However, we have only 13.7 million hectares of mangroves globally, and their area is decreasing at a rapid rate mainly due to land-use and land-cover change (LULCC). Disturbing mangroves results in very high greenhouse gas (GHG) emissions given the significant carbon density per unit area of these coastal forests. Disturbance also results in the loss of the carbon accumulation that would have occurred if they had been maintained in their natural state.
Mangrove regeneration via restoration and rehabilitation can return the ecosystems services (carbon sequestration, fisheries habitat, wood products, and coastal stabilization) that were previously provided.
While effective carbon management requires quantitative numbers of these impacts, to date, there is no global consensus of the magnitude of blue carbon change once mangrove is either deforested, converted then rehabilitated or even restored.
Over the last three years, we have been working to resolve these knowledge and data gaps by conducting a systematic review of carbon stocks and fluxes in natural, converted and rehabilitated mangroves.
We screened thousands of published articles and extracted any relevant data related to carbon stocks and soil greenhouse gas fluxes. These data were summarized and synthesized in our review to further application to blue carbon policy development.
In 2016 we set up an international review team involving colleagues from Charles Darwin University, the Center for International Forestry Research, and the National University of Singapore, and developed a systematic protocol, which defines review objectives and guidelines for literature searches, screening and data extraction.
Our first-tier search identified more than 5,000 articles, which was then further screened following inclusion and exclusion criteria we set in our protocol — a time-consuming step. Selection was based on publication titles, abstracts and full-text.
From the initial ~5000 publications, the application of our protocol resulted in less than 10 papers. Clearly, insufficient for a 'global' review and was due to the strict paper selection process we applied during the screening. We only included papers which reported data from both control (undisturbed mangrove) and treatment (LULCC-affected mangrove) sites within comparable habitat setting. Because of this insufficient dataset, we then repeated literature search and data screening two times, and extended the cut-off date of literature search until October 2018.
We held three times data workshops and numerous meetings over three years, finally, we have the final dataset and first manuscript draft early this year.
Conducting a systematic review is a time-consuming process but as it's 'systematic', it is thorough, transparent, identifies knowledge gaps, and informs immediate and future research directions.
The findings itself is published in Global Change Biology here: https://onlinelibrary.wiley.com/doi/10.1111/gcb.14774
The systematic review protocol for this study can be accessed here: https://www.cifor.org/library/6225
The compiled dataset are available through this link: https://data.cifor.org/dataset.xhtml?persistentId=doi:10.17528/CIFOR/DATA.00182