Nonlinear Modeling of Temperature-Driven Mycelial Growth Reveals Divergent Thermal Niches in Pythium, Globisporangium, and Phytopythium Isolates

Authors : Muharrem Türkkan, Göksel Özer, Sibel Derviş

Pages : 189-203

Doi:10.29278/azd.1763477

View : 35 | Download : 34

Publication Date : 2025-12-29

Article Type : Research Paper

Abstract :Objective: The purpose of this research is to identify the most suitable mathematical model for characterizing the thermal biology of economically important oomycetes (Pythium dissotocum, Globisporangium heterothallicum, G. intermedium, G. sylvaticum, and Phytopythium vexans) and to use these models to define the thermal niches of these pathogens. The goal is to establish a fundamental understanding for disease epidemiology and climate-driven management strategies. Materials and Methods: In this study, 18 isolates belonging to Pythium dissotocum, Globisporangium heterothallicum, G. intermedium, G. sylvaticum, and Phytopythium vexans were used as material. Empirical data on the mycelial growth of these isolates were collected. The collected data were analyzed using fourteen different nonlinear models. The performance of the models was subjected to a multi-criteria evaluation and compared using an information-theoretic approach. Results: The comparisons unequivocally demonstrated the superiority of asymmetric functions, most notably the Briere2 model, in describing the nonlinear thermal responses of the oomycetes. The Briere2 model was identified as the optimal model for 12 of the 18 isolates studied. This modeling revealed a distinct partitioning of thermal niches: P. vexans (Topt: 26.46–26.98°C) and G. sylvaticum (Topt: 25.58–27.16°C) isolates showed clear adaptations to warmer climates, in contrast to the cooler thermal optima of G. heterothallicum (Topt: 20.65–22.06°C). Conclusion: This work establishes a definitive methodological precedent for modeling the thermal biology of oomycetes and provides critical empirical parameterization for these pathogens. The findings offer an essential foundation for advancing predictive disease forecasting and for formulating robust, climate-driven management strategies in agricultural environments.
Keywords : Pythium benzeri funguslar, Miselyal büyüme, Kardinal sıcaklıklar, Doğrusal olmayan regresyon modelleri, Termal adaptasyon, Model seçimi, Oomycete ekoloji

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