Satellites and algorithms anticipate the death of fish
Scientists from CONICET and the National University of Rio Cuarto developed a model to predict outbreaks of a lethal disease for mojarras and other species.
During the years 2007, 2010 and 2016, fish mortality was recorded in several reservoirs in the center of the province of Córdoba due to a disease that produces a fungus. The most serious outbreak occurred in the Rio Terceroreservoir, the largest reservoir in the province with hundreds of dead fish.
Now, a model based on algorithms and satellite images developed by researchers from Rio Cuarto will allow us to estimate the probability of outbreaks of this disease, called saprolegniasis, in that reservoir.
It is a fungal disease or mycosis caused mainly by a microorganism called Saprolegnia parasitica, which covers an extensive area of the body of fish and causes them to swim and feed. The main species affected were two colored-tailed mojarras: Astyanax eigenmanniorum and Astyanax fasciatus.
“ Development can be of great interest to both local authorities, decision makers and water management and management agencies, and nonprofit organizations related to environmental care and the general public,” said the director of the advancement, Dr. Matías Bonansea, CONICETresearcher at the Institute of Earth Sciences, Biodiversity and Environmental Sustainability (ICBIA), at the National University of Rio Cuarto (UNRC).
Saprolegniasis tends to occur seasonally, mainly in the winter months and in the presence of other predisposing factors such as low fishes. “The low temperature of the water is one of the most important triggers, since in certain fish species it creates favorable conditions for the rapid proliferation of the fungus,” explained Bonansea, also a member of the Department of Basic and Agricultural Studies of the Faculty of Agronomy and Veterinary (FAYV) of the UNRC.
To monitor this variable, scientists resorted to satellite imagery, a form of periodic measurement that has low economic costs and logistical requirements, the researcher added. They integrated this information with sampling campaigns in the reservoir, in order to assess all fish species affected by the disease, as well as environmental and water quality parameters.
Based on the data obtained in the field, the researchers validated a technique called “Single-Channel method”, used to estimate the surface temperature from Landsat satellite images.
“ The model works as a practical, low-cost and easy to apply tool to predict the likelihood of disease in the reservoir,” Bonansea said. “And it could be extrapolable to other aquatic environments in the province and country where similar outbreaks have been recorded,” he added.
Lucio Pinotti, from ICBIA-CONICET, and Miguel Mancini, Micaela Ledesma, Claudia Rodríguez and Susana Ferrero, from UNRC, also participated in the study, published in the journal “The Science of the Total Environment”.
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