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Many species of soil fungi grow in the form of branched networks that enable long-range communication and mass flow of nutrient. These networks play important roles in the soil ecosystem as a major decomposer of organic materials. While there have been investigations on the branching of the fungal networks, their long-term growth dynamics in space and time is still not very well understood. In this study, we monitor the spatio-temporal growth dynamics of the plant-promoting filamentous fungus Serendipita indica for several days in a controlled environment within a microfluidic chamber. We find that S. indica cells display synchronized growth oscillations with the onset of sporulation and at a period of 3 h. Quantifying this experimental synchronization of oscillatory dynamics, we show that the synchronization can be recapitulated by the nearest neighbour Kuramoto model with a millimetre-scale cell-cell coupling. The microfluidic set-up presented in this work may aid the future characterization of the molecular mechanisms of the cell-cell communication, which could lead to biophysical approaches for controlling fungi growth and reproductive sporulation in soil and plant health management.

Climate warming is causing shifts in reproductive phenology, a crucial life history trait determining offspring survival and population productivity. Evaluating these impacts on exploited marine resources is essential for implementing adaptive measures from an ecosystemic approach. This study introduces a statistical model designed to predict fish spawning phenology from sea surface temperature profiles, integrating mortality-corrected hatch-date distributions inferred from fishery-dependent samplings, along with the gonadosomatic index of adult individuals. When applied to different dolphinfish (Coryphaena hippurus) populations across a broad latitudinal range, the model reasonably predicts the spawning phenology across its extensive thermal ranges, elucidating a direct relationship between mean annual temperature and the breadth of the spawning season. Despite the varying thermal profiles, results show a consistent timing of spawning peaks approximately 49 days before the peak in temperature. Importantly, these findings account for the impact of fishery constraints, such as seasonal closures or different sampling schedules, offering a robust tool for adjusting management practices in response to inter-annual temperature variations. These insights are critical for both short-term fishery management, including the strategic planning of seasonal closures, and long-term projections of spawning phenology shifts under changing thermal regimes. By enhancing our ability to predict spawning times, this research contributes significantly to the sustainable management of fish populations and the adaptive response to environmental changes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)