Using distribution models to estimate blooms of phytosanitary cyanobacteria in Brazil

• Autor(a) principal: Guimarães,Ariane
• Data de Publicação: 2020
• Outros Autores: Silva,Pablo Henrique da, Carneiro,Fernanda Melo, Silva,Daniel Paiva
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Biota Neotropica
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1676-06032020000200202
• topic: freshwater ecosystems; species distribution models; bloom occurrence; cyanobacteria

Abstract: The multiple uses of aquatic ecosystems by humankind and the continuous interference of their activities have contributed to the emergence of potentially toxic cyanobacteria blooms. Here, we firstly created a database of occurrences of cyanobacteria blooms in Brazil through a systematic review of the scientific literature available in online platforms (e.g. Web of Science, Capes Thesis Catalogue). Secondly, we carried out ecological niche models with occurrence data obtained from these studies to predict climatically suitable areas for blooms. We select 21 bioclimatic variables input environmental data. We used five modeling methods for the current climate scenario: (1) Maxent; (2) Support Vector Machines; (3) Random Forest; (4) Maximum Likelihood e (5) Gaussian. We found that the number of publications about bloom events was higher in 2009 with a decline in the years 2012, 2013 and 2017. Furthermore, the years with the higher records of blooms in freshwater environments were 2005, 2011 e 2014. These events occurring mainly in public supply reservoirs and are mostly of the genera Microcystis Lemmermann, 1907, Dolichospermum (Ralfs ex Bornet & Flahault) P.Wacklin, L.Hoffmann & J.Komárek, 2009 and Raphidiopsis F.E.Fritsch & F.Rich, 1929. Modeling the potential distribution of blooms, we found sampling gaps that should be targeting for future researches, especially in the Amazon biome. Overall, the models did not predict highly suitable areas in the /north of Brazil, while other regions were relatively well distributed with a higher number of occurrence records in the Southeast region.