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An assessment of mangrove vegetation changes in reference to cyclone impacted climatic alterations at land–ocean interface of Indian Sundarbans with application of remote sensing–based analytical tools

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Abstract

Mangrove ecoregions of the Indian Sundarbans (IS) are highly productive ecosystems in the Bengal delta of the Indian subcontinent. These mangroves are crucial in reducing the negative consequences of extreme environmental events like excessive wave movements and periodic storm surges, in addition to serving as an important habitat for a variety of distinct flora and animals. The Bay of Bengal has been increasingly affected by climatic changes like increase in sea surface temperature (SST), salinization, and sediment loads, a decrease in freshwater intake, and sea level rise. In the last two decades (2000–2020), these climatic phenomena have increased the frequency of tropical cyclones. From 2000 to 2020, the loss of landmass has been attributed to exposure to these climate changes. According to open-source satellite imaging data, such losses in land area have also led to a decrease in the amount of mangrove vegetation. Thus, to monitor the health of mangrove vegetation, Landsat-based health indicators like normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and combined mangrove recognition index (CMRI) have been considered in this study. CMRI, as a mangrove-specific index, was measured on the basis of the difference of NDVI and normalized difference water index for remote sensing of vegetation liquid water from space (NDWI_Gao). Furthermore, datasets for abiotic variables have been extrapolated from remotely sensed data for the said period using specific formulae. Both long-term and short-term temporal trends have been considered to better envisage the impact of episodic cyclonic events on mangrove health (1990–2020). Our findings indicate that cyclones altered the habitat with respect to land area and salinization status which would possibly render the dominance of more halotolerant forms with loss of freshwater mangrove biodiversity. Even though plantation efforts have shown the recovery of mangroves in this area, sudden storm surges and concomitant salinization of habitat put the plantation efforts in vain. A combination of factors like salinization, rise in SST, rainfall reduction in pre- and post-monsoon periods and episodic cyclonic events would probably lead to further deterioration of mangrove health in this area. Since the IS is suffering the most from climatic change and intermittent cyclonic occurrences, it is crucial to consider this when making policy decisions. Appropriate actions must be taken along with stronger conservation techniques, to protect this vulnerable environment. Better conservation tactics and ongoing plantation efforts would stop the loss of mangrove vegetation and its habitat, even though the growing frequency of episodic storm occurrences cannot be stopped.

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The authors declare that if needed, the authors will share the datasets during the review process or after the publication of the manuscript.

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Authors and Affiliations

  1. Phycology Lab, Department of Botany, Ramakrishna Mission Vivekananda Centenary College, Rahara, Kolkata, West Bengal, 700118, India

    Arghadeep Das & Avik Kumar Choudhury

  2. Department of Geography, Krishnagar Government College, Nadia, West Bengal, 741101, India

    Kaustabi Maitra Choudhury

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All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Arghadeep Das, Kaustabi Maitra, and Avik Kumar Choudhury. The first draft of the manuscript was written by Avik Kumar Choudhury, and all authors commented on the previous versions of the manuscript. All authors have read and approved the final manuscript.

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Correspondence to Avik Kumar Choudhury.

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Das, ., Choudhury, K.M. & Choudhury, A.K. An assessment of mangrove vegetation changes in reference to cyclone impacted climatic alterations at land–ocean interface of Indian Sundarbans with application of remote sensing–based analytical tools. Environ Sci Pollut Res 30, 89311–89335 (2023). https://doi.org/10.1007/s11356-023-28486-w

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