A geospatial habitat suitability index model for Ulva sp. in Jamaica Bay, NY: Model validation using Ulva biomass data

Macroalgal blooms have been a significant indicator of eutrophication in estuaries worldwide, from Europe to North America, for many decades. Jamaica Bay is no exception to this issue, with blooms from the genus Ulva being widespread during the spring and summer months. This Habitat Suitability Index Model aims to predict the distribution of Ulva in Jamaica Bay based on prevailing water quality conditions. It involves the inclusion of several water quality parameters, the most important being temperature, percent light to the bottom, nitrate-nitrite, and ammonium. The other parameters included pH, dissolved oxygen, salinity, dissolved organic carbon, dissolved organic nitrogen, and phosphates. The method employed spatial interpolation using Inverse Distance Weighting in ArcGIS Pro. These were reclassified and weighted based on the suitability and importance, respectively, of each water quality parameter for the growth of Ulva. Overall, when the model predictions were compared to biomass data, there was an 82 % correlation for 2012, as well as 60 % and 80 % correlations for July and October 2015, respectively. Additionally, there were 50 % and 47.5 % correlations for July and August 2017, respectively. This model is based on the summation of the weighted scores for each parameter in the model outputs. The locations with the highest suitability index had the highest weighted scores while those with the lower suitability index had lower weighted scores. It should be noted that between June and July in 2012, 2015 and 2017, there were the highest coincidences of biomass measurements and model index results which confirm that during these months, the blooms tend to occur to the highest extent. The major gap filled by this study is to develop an index model for the estimation of Ulva blooms in Jamaica Bay. This was validated using biomass data to confirm whether these index estimations were valid. The implication of this study is to ensure that once adequate water quality data is available, this method can be used to indicate which areas of eutrophic estuaries are prone to Ulva blooms in different locations in the USA and other countries.