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                <term xml:lang="en">linear model</term>
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              <p>Cyanobacterial blooms are known to cause significant ecological and public health concerns by altering the physico-chemical conditions of aquatic environments and releasing harmful toxins. This issue has recently been observed in lake Léon (Landes, France), where the proliferation of cyanobacteria has become a major issue. Various chemical (e.g., nutrient concentrations), physical (e.g., water level), and meteorological factors are known to favor the development of cyanobacterial blooms. The aim of this study is to test the relative importance of these factors on the development of cyanobacteria biovolume in the lake Léon. To this end, the relevant variables have been compiled from 2008 onwards and incorporated into a series of linear models. These models were constructed both across the entire study period and at a seasonal scale to identify the specific conditions that contribute to the biovolume variability over time. Physico-chemical factors-particularly nutrient levels such as phosphorus-show strong correlations with cyanobacterial biovolumes. Meteorological conditions also play a key role, although the timing and intensity of their effects vary by parameter and season. Among these, temperature emerges as the most influential variable. Additionally, water level is significantly associated with biovolume during the summer months. Seasonal persistence was also observed, with biovolumes depending on those of the preceding seasons. Consequently, the occurrence of blooms appears to result from the interplay of these multiple factors. These findings align with existing literature and offer new insights into cyanobacterial proliferation in the specific context of lake Léon. Nevertheless, expanding the dataset-both in terms of duration and resolution-would improve model reliability and support the development of predictive tools for managing future public health risks.</p>
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