Site suitability mapping for different seaweed cultivation systems along the coastal and marine waters of Bangladesh: A Generalized Additive Modelling approach for prediction

Abstract

While seaweed cultivation has reached an advanced stage in many Asian countries, this industry remains nascent in Bangladesh, hindered by a lack of comprehensive site suitability mapping. To address this gap, we employed the Generalized Additive Model (GAM) approach to develop habitat suitability maps for different seaweed cultivation systems encompassing the entire coastal and marine territorial areas of Bangladesh. Our study leveraged an in-situ dataset comprising production and environmental factors from 180 cultivation plots of four species (Gracilaria sp., Enteromorpha intestinalis, Ulva lactuca, and Hypnea musciformis) across five cultivation sites, supplementing this data with other ecological variables derived from satellite observations and model simulations. The GAM analysis identified seven key explanatory variables that collectively accounted for 78 %, 76 %, and 79 % of the observed variability in seaweed data for off-bottom long-line, off-bottom net, and floating long-line cultivation systems, respectively. The model predicted that total suspended solids (TSS) predominantly influenced the habitat suitability for off-bottom net and floating long-line cultivation systems, while salinity was a crucial determinant for off-bottom long-line cultivation systems. The study further demonstrated that the predicted suitable areas (50–100 %) for floating long-line cultivation systems (1850 km2) substantially outnumbered those for off-bottom long-line (372 km2) and off-bottom net (380 km2) cultivation systems. The model showed that the southeast coast, specifically the sandy bottom areas of the Moheshkhali channel and its surroundings, exhibited high suitability (>75 % probability) for off-bottom long-line and off-bottom net cultivation systems. In contrast, the floating long-line cultivation system appeared most suitable for seaweed farming along almost the entire coastline of Bangladesh, excluding the Meghna and adjacent estuaries in the central region. Notably, the most suitable areas were specifically concentrated in the coastal areas of Moheshkhali Island, Cox's Bazar, Teknaf, and Saint Martin's Island in the southeast coastal zone, extending potentially to far offshore waters. The predictions of our model aligned well with in-situ observations, as evidenced by an area under the curve (AUC) of 0.83 and an R2 value of 0.85. The insights gleaned from this research offer invaluable guidance to seaweed farmers, entrepreneurs, and policymakers, thereby contributing to the sustainable development of the emerging seaweed-based blue economy in Bangladesh.