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<p>Invasive species, the second leading cause of biodiversity loss worldwide, significantly disrupt the goods and services provided by aquatic ecosystems. Our study aimed to identify the local environmental variables most influencing the distribution of the non-native species <i>Macrobrachium</i> <i>pantanalense</i> (Decapoda, Palaemonidae) in the Furnas hydropower reservoir (Brazil). We tested the effects of land use, physical habitat, water physical and chemical variables on the distribution of the non-native species through model selection by General Linear Models with binomial distribution. <i>M.</i> <i>pantanalense</i> presence was positively correlated with aquatic macrophytes (total cover of emerging and floating plants), heterogeneity of littoral cover, and the biochemical oxygen demand. Our findings can be used to develop predictive models that help identify areas in tropical hydropower reservoirs at risk of invasions. This proactive approach allows for a targeted response in different parts of the world. In addition, it can guide integrated water resource management policies, environmental managers and decision-makers in developing solutions to the complex challenge of managing non-native species in tropical hydropower reservoirs.</p>

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Influence of local environmental factors on the distribution of the invasive species Macrobrachium pantanalense dos Santos, Hayd and Anger, 2013 in a large hydropower reservoir

  • 期刊论文

  • 发表日期：

    2025年4月23日

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  • Karoline H. Madureira,
  • Marden S. Linares,
  • Marcos Callisto

摘要

Invasive species, the second leading cause of biodiversity loss worldwide, significantly disrupt the goods and services provided by aquatic ecosystems. Our study aimed to identify the local environmental variables most influencing the distribution of the non-native species Macrobrachium pantanalense (Decapoda, Palaemonidae) in the Furnas hydropower reservoir (Brazil). We tested the effects of land use, physical habitat, water physical and chemical variables on the distribution of the non-native species through model selection by General Linear Models with binomial distribution. M. pantanalense presence was positively correlated with aquatic macrophytes (total cover of emerging and floating plants), heterogeneity of littoral cover, and the biochemical oxygen demand. Our findings can be used to develop predictive models that help identify areas in tropical hydropower reservoirs at risk of invasions. This proactive approach allows for a targeted response in different parts of the world. In addition, it can guide integrated water resource management policies, environmental managers and decision-makers in developing solutions to the complex challenge of managing non-native species in tropical hydropower reservoirs.