Mapping Mangrove Opportunities with Open Access Data: A Case Study for Bangladesh
Abstract
:1. Introduction
2. Theoretical Background
2.1. Coastal Protection by Mangroves in Bangladesh
2.2. Finding Suitable Locations for Mangroves Foreshores
3. Materials and Methods
3.1. Description of the Study Area
3.2. Open Access Databases
3.3. Screening Methodology
- Suitability of a site as potential habitat: we considered sites within 10 km of existing mangroves as potentially suitable for colonization. This limit was based on dispersal distances observed by Clarke [56] for Avicennia marina seedlings. In practice, the dispersal distances will vary between mangrove species, and will depend on the local hydrodynamic processes. However, this value provides a preliminary indication of the areas that could recruit naturally. The existing mangrove sites were obtained from the maps by the Global Forest Watch (Table 1).
- Method needed to implement vegetation: the techniques needed to vegetate a site were based on the rates of coastline change from the Aqua-monitor tool [52]. We assumed that natural colonization would happen at locations with expanding coastlines near existing mangroves, and if seedling availability was low, or natural processes were too slow compared to coastal protection targets, they could be complemented by planting efforts. At sites with retreating coastlines, erosion mitigation measures, such as bamboo structures or nourishments, would be needed.
- Prioritization criterion based on vulnerability: we evaluated the level of priority based on the flooding risk of landward areas using the ground elevation measurements from CoastalDEM® [51], and 3 scenarios of relative sea level rise (RSLR) from IPCC [55]: +0.3 m (expected value in 2050), +1 m (worst case scenario in 2050), and +2 m (worst case scenario in 2100). Since polders comprise inhabited areas and valuable assets, their protection was prioritized compared to non-polder areas. Moreover, polders are blocked from any sediment input by the tide, which means that, unlike unembanked areas, they have no mechanisms to accrete and keep up with rising sea levels. Polders that would be below MSL in the RSLR scenario of +1 m in 2050 were given the highest flooding risk, and we prioritized vegetated foreshores seawards of them.
4. Results
5. Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Dataset Type | Description | Source |
---|---|---|
Digital elevation model | CoastalDEM® is a digital elevation model at 90 × 90 m resolution, with a maximum vertical accuracy of −0.29 m. | Kulp and Strauss [51] |
Coastline change | The Aqua-monitor tool provides the rate of coastline change, and sediment composition (sandy or not sandy), since 2016, in transects every 15 m along the coastline. | Luijendijk [52] |
Intertidal areas | Global Intertidal provides maps with tidal flat areas until 2016 | Murray [53] |
Mangrove cover | Global Forest Watch provides the areas of mangrove coverage from 2001 to 2018 (https://www.globalforestwatch.org, accessed on the 1 May 2020) | Global Forest Watch |
Rivers | Maps of rivers of Bangladesh (https://data.humdata.org/, accessed on the 1 May 2020). | LGED |
Tidal range | Tidal range measurements | Bricheno [54] |
Country boundaries and regions | Boundaries of the country and its regions (https://gadm.org, accessed on the 1 May of 2020) | GADM |
Sea level rise | Global predictions of relative sea level rise | IPCC [55] |
ID | Location | Polder | Vegetation Implementation Technique |
---|---|---|---|
1 | Galachipa | P55/3 | Natural recruitment/planting |
2 | Galachipa | P55/4 | Natural recruitment/planting |
3 | Bhola | P56/57 | Natural recruitment/planting |
4 | Hatiya South | P73/2 | Natural recruitment/planting |
5 | Manpura | P58/1–3 | Erosion mitigation/Natural recruitment/Planting |
6 | Hatiya North | P73/1 | Erosion mitigation/Natural recruitment/Planting |
7 | Khangona | P66/3 | Natural recruitment/planting |
8 | Boro Moheshkhali | P69 | Natural recruitment/planting |
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Gijón Mancheño, A.; Herman, P.M.J.; Jonkman, S.N.; Kazi, S.; Urrutia, I.; van Ledden, M. Mapping Mangrove Opportunities with Open Access Data: A Case Study for Bangladesh. Sustainability 2021, 13, 8212. https://doi.org/10.3390/su13158212
Gijón Mancheño A, Herman PMJ, Jonkman SN, Kazi S, Urrutia I, van Ledden M. Mapping Mangrove Opportunities with Open Access Data: A Case Study for Bangladesh. Sustainability. 2021; 13(15):8212. https://doi.org/10.3390/su13158212
Chicago/Turabian StyleGijón Mancheño, Alejandra, Peter M. J. Herman, Sebastiaan N. Jonkman, Swarna Kazi, Ignacio Urrutia, and Mathijs van Ledden. 2021. "Mapping Mangrove Opportunities with Open Access Data: A Case Study for Bangladesh" Sustainability 13, no. 15: 8212. https://doi.org/10.3390/su13158212
APA StyleGijón Mancheño, A., Herman, P. M. J., Jonkman, S. N., Kazi, S., Urrutia, I., & van Ledden, M. (2021). Mapping Mangrove Opportunities with Open Access Data: A Case Study for Bangladesh. Sustainability, 13(15), 8212. https://doi.org/10.3390/su13158212