Modeling the Effects of Seawater pH and Temperature on the Growth and Biofilm Formation of Cobetia sp strain MM1IDA2H-1. Using Nonlinear GAMLSS and Mixed Residual Analysis

Milan StehlikAlejandro Dinamarca^*Fernando Rojas^*Claudia IbacacheKaroll González-PizarroFernanda Figueroa-AjrazsBastián Barraza-Morales

• Universidad de Valparaiso, Valparaíso, Chile

Understanding how environmental factors modulate microbial growth and biofilm formation is essential for predicting ecosystem dynamics and biotechnological outcomes. In this study, we investigated the responses of Cobetia sp. MM1IDA2H-1 across controlled temperature and pH gradients, combining laboratory assays with advanced predictive models. Growth trajectories were analyzed using nonlinear logistic fits and generalized additive models for location, scale, and shape (GAMLSS), with linear mixed-effects models applied to residual structures. This two-step approach provided robust estimates of fixed and random effects, allowing us to disentangle replicate-level variability and capture non-additive dynamics. The results revealed a clear trade-off: while maximum growth rates peaked at intermediate temperatures (37–39◦C) with a slightly acidic to neutral pH, biofilm formation was enhanced under alkaline conditions (pH ≥8) and over a wider thermal window, indicating a dissociation between planktonic growth efficiency and sessile resilience. This antagonistic response highlights how environmental variability can modify microbial strategies between rapid proliferation and persistent colonization. Importantly, the predictive quality of the models allowed the extrapolation of these patterns to ecosystem scenarios, underscoring their potential for both environmental prediction and applied microbial management. By integrating experimental data with predictive frameworks, this study provides a methodological and conceptual bridge between laboratory microbiology and quantitative ecology.