Amazing experience of the Early Career Visiting Scientist program at Blue Carbon Hub
By Upal Mahamud
In 2022, I was selected to participate in the IORA Blue Carbon Hub Early Career Professional Program. The program took place at the Indian Ocean Marine Research Centre in Perth, Australia, and it lasted for eight weeks. My study focused on the impact of rising sea levels on mangrove species distribution in the Bangladesh Sundarbans.
Mark Wilson welcomed me at Hub and helped me with all the administrative procedures to start my research work. He also introduced all the selected fellows for this program (Mussa from Tanzania, Tai from South Africa, Kariz from Indonesia, and Mir from my country of Bangladesh). Mat, Mark, and Lauren went above and beyond, to make sure that we were well taken care of and that we had a wonderful experience.
Mangroves often modify coastlines through their ability to attenuate waves, current speeds, tide and storm surge level, capture sediments and build soils which reduces coastal vulnerability on landward margins and decreases exposure to extreme events. Around 46 mangrove species are present in Bangladesh including the Sundarbans. Climate change threatens mangrove ecosystems by raising sea levels, raising air and water temperatures, and changing precipitation and storm frequency and intensity. Among these challenges, rising sea levels may endanger mangrove survival if room for migration or expansion is not available. Such changes could impact the Sundarbans’ current and future management, as well as the livelihoods of tens of thousands of people. Salinity is an important influence on mangrove distribution and it can be altered by sea level rise, so understanding the physical and economic implications of salinity diffusion will be crucial for Sundarbans management, as well as long-term development and poverty reduction in nearby communities. The main goal of my study was to examine the impact of rising sea levels on mangrove species distribution in Sundarbans.
To be able to assess the impact of sea level rise on mangrove species distributions, a variety of datasets are needed, such as mangrove species and their spatial distribution, salinity, tidal statistics and more. I used the methodology shown in Figure 1.
First, we need to understand the past and present mangrove species in the study area and prepare a base spatial distribution map for mangrove species. For that purpose, a remote sensing application was applied to identify the mangrove species from the recently available dense series of multitemporal Sentinel-2 data. To validate the mangrove species map (Figure 2), various global and local mangrove datasets were collected. Machine learning techniques were applied using supervised classification to identify different mangrove species. Ultimately, the Random Forest approach provided greater precision. I got great support from Mat and Mussa to develop the methodology for preparing this spatial mangrove species map.
Second, I had to prepare present and future the salinity spatial maps from the available data and model. The Institute of Water Modelling (IWM) maintain a well calibrated salinity model that covers the whole coast of Bangladesh which could be useful for salinity information around the study area. I overlaid a digital map of salinity with the most recent mangrove distribution map of the Bangladesh Sundarbans to develop estimates of the salinity tolerance ranges of mangrove species.
Finally, I simulated projections of future salinity in this region for RCP8.5 based on the IPCC report (Figure 3) and combined it with our estimated species salinity tolerance ranges to produce a spatial distribution of future mangrove species map for the Sundarbans. From the result, we found about 15% of the distribution of Heritiera fomes (the dominant species in the Sundarbans) will be affected and about 5% of the distribution of Excoecaria agallocha will be affected by a projected 92-cm sea level rise (Table 1). Ceriops decandra and Sonneratia apelatala species have a higher salinity tolerance (24 to 28 ppt) and are less affected. In the future, river salinisation in the eastern part of the Sundarbans will significantly reduce the highest valued timber species, Heritiera fomes. The species composition will likely shift to higher salinity-tolerant mangrove species like Ceriops decandra and Sonneratia apelatala.
I hope that this research will provide valuable new information for local policy makers and researchers in Bangladesh and elsewhere. I also hope that this study will narrow the knowledge gap for coastal Bangladesh with local high-resolution spatial data.
The IORA Blue Carbon Hub visiting scientist program for early-career professionals has provided me with an excellent opportunity. By joining this program, I was able to devote all my time to working on the research project. Every two or three weeks, Mat and Lauren organized a progress meeting at which all participants presented their work. It assisted in keeping my research on track. We were also able to attend a NASA webinar entitled “Evaluating Ecosystem Services using Remote Sensing”. In addition, Mat organized a training program on ‘R’ programming for the analysis of blue carbon field data. Mussa, one of the participants from Tanzania, introduced me to Google Earth Engine data processing and various machine learning techniques. It was of considerable assistance to my research at Hub.
The Early Career Visiting Professionals Program has significantly improved my research skills and helped me establish new relationships with blue carbon specialists. I am extremely appreciative for the opportunity to participate in this program. If this program continues, I strongly recommend that others apply for it.