Mangrove forests play a significant role in maintaining the health of the coastal ecosystems globally and support life for birds, flora, and fauna. Healthy mangrove forests protect the coastal ecosystem against natural hazards and are a great source of carbon sequestration than any other type of forest. The mangrove forests provide significant ecological, social, and economic services to the coastal communities. Mangrove forests are one of the most productive ecosystems in the world, being the abode of diverse fauna and flora. In spite of providing immense benefits, these ecosystems are under constant degradation due to anthropogenic disturbance and climate change. Nearly half of the mangrove biomes have been despaired since 1950 due to huge habitat alteration and inadequate protection. It is anticipated that if this rate of loss is continued then the mangrove biome will be vanished from the earth by the next 100 years. A recent study by Polidoro et al. on mangrove species over the world reported that more than 16% of species are in the state of becoming extinct and another 10% are under threat of degradation. The mangroves experience higher losses than the average losses of the tropical and sub-tropical.
Mangrove forests being the abode of diverse fauna and flora are vital for healthy coastal ecosystems. These forests act as a carbon sequester and protection shield against floods, storms, and cyclones. The mangroves of the Sundarban Biosphere Reserve (SBR), being one of the most dynamic and productive ecosystems in the world are in constant degradation. Hence, habitat suitability assessment of mangrove species is of paramount significance for its restoration and ecological benefits. This study aims to assess and prioritize restoration targets for 18 true mangrove species using 10 machine-learning algorithm-based habitat suitability models in the SBR. They identified the degraded mangrove areas between 1975 and 2020 by using Landsat images and field verification. The reserve was divided into 5609 grids using 1 km gird size for understanding the nature of mangrove degradation and collection of species occurrence data. A total of 36 parameters covering physical, environmental, soil, water, bio-climatic and disturbance aspects were chosen for habitat suitability assessment. Niche overlay function and grid-based habitat suitability classes were used to identify the species-based restoration prioritize grids. Habitat suitability analysis revealed that nearly half of the grids are highly suitable for mangrove habitat in the Reserve. Restoration within highly suitable mangrove grids could be achieved in the areas covered with less than 75 percent mangroves and lesser anthropogenic disturbance. This study calls for devising effective management strategies for monitoring and conserving the degraded mangrove cover. Monitoring and effective management strategies can help in maintaining and conserving the degraded mangrove cover. This model proves to be useful for assessing site suitability for restoring mangroves. The other geographical regions interested in assessing habitat suitability and prioritizing the restoration of mangroves may find the methodology adopted in this study effective.
Sources:
Nature-Scientific Reports
https://www.nature.com/articles/s41598-022-24953-5 .
Provided by the IKCEST Disaster Risk Reduction Knowledge Service System
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