Transformation of coastal wetlands in the Sundarban Delta (1999–2020)

Abstract

Spanning across Bangladesh and India, the Sundarban Delta consists of over a thousand islands, the majority of which are protected. These islands are important for the rich biodiversity and unique species found here. However, these islands are also at the forefront of climate change due to the impact of rising sea levels and extreme weather events. Therefore, we analyzed the long-term transformations in the land use land cover (LULC) between 1999 and 2020. We used a variety of geostatistical methods, including optimized hot spots cold spots and join count statistics, to examine the spatial patterns of changes in LULC across the study area. The results of our analysis revealed substantial changes in the spatial patterns of mangroves and pond aquaculture. The changes revealed a distinct north–south demarcation in spatial patterns, in the form of clustering of mangroves in the uninhabited islands located in the south and pond aquaculture clustered in the northern inhabited islands. The loss of area under mangroves was concentrated in the southern edges of the islands, which were most exposed to erosion in the open ocean. Nevertheless, we observed an increase in the area under mangroves in some of the northern riverine islands (17 km2). In the case of pond aquaculture, it was mostly concentrated in inhabited islands in the north. Most of the expansions were concentrated in the Indian part of the delta (631 km2). It is noteworthy that because of effective conservation measures, there was very limited overlap between mangroves and pond aquaculture, denoting the conversion of agricultural land to pond aquaculture instead of mangroves. Thus, the results of our study revealed the importance of local level conservation policies and anthropogenic activities, such as deforestation and local level disturbance like over-extraction of water and pollution, on the changing patterns of LULC across this unique, fragile ecosystem. Future studies may incorporate a finer resolution time series of LULC changes over time and space to enable more detailed analysis.