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Inference of Submerged Macrophytes Colonization Using the Weights of Evidence Method

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Open Access
Article Type Research Article
Subject Environmental Sciences
OCLC JBRES Record
Ligia Flavia A Batista*, Fernanda SY Watanabe, Luiz Henrique S Rotta and Nilton N Imai
Issue: Volume3-Issue9
Pages: 1057-1064
Received: 2022-09-08
Accepted: 2022-09-13
Published: 2022-09-16

Abstract

In some tropical reservoirs, aquatic macrophytes have covered extensive areas and it is difficult to monitor, control and forecast their proliferation. The major issues are economic and ecological because macrophyte growth has caused significant financial losses to hydroelectric power plants and has affected the ecological balance. Thus, this work aimed to infer the most likely areas to be colonized by Submerged Aquatic Vegetation (SAV), using influencing factors, such as the morphometric aspects of the area and any preexisting vegetation, to support the management decision-making process. Four field surveys were carried out to collect hydroacoustic data, which indicate presence of SAV, in Taquaruçu reservoir, Paranapanema River, Brazil. The inference procedure was applied using the weights of evidence method. The results showed that depths up to 6 m have a high probability of colonization and that points with five or six colonized neighbor’s cells, considering a regular grid, are also more likely to be colonized. The weights for the slope map behaved differently at each survey interval. The probability maps of colonization were generated and can be very useful in supporting the decision-making process of SAV management activities, such as concentrating the monitoring efforts for the high-probability colonization areas, in this case those which the lowest depths or next to colonized regions.

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Copyright

© 2022 Batista LFA, et al. Distributed under Creative Commons CC-BY 4.0 Creative CommonsAttribution

How to cite this article

How to cite this article: Batista LFA, Watanabe FSY, Rotta LHS, Imai NN. Inference of Submerged Macrophytes Colonization Using the Weights of Evidence Method. J Biomed Res Environ Sci. 2022 Sep 16; 3(9): 1057-1064. doi: 10.37871/jbres1555, Article ID: JBRES1555, Available at: https://www.jelsciences.com/articles/jbres1555.pdf

Subject area(s)

Ecosystem ScienceEcohydrology

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