Mandyam Dhati, A. | bioRxiv Science

bioRxiv2026

Environmental history can counteract nutrient quality in shaping the evolution of bacterial growth rates

Despite sharing nearly identical enzymes, strains of the same microbial species display wide variability of growth rates when growing on the same nutrients. Here, we show that such growth rate variability can emerge as a consequence of evolutionary adaptation to different patterns of environmental fluctuations. We develop a mathematical model combining cellular proteome allocation with eco-evolutionary dynamics in fluctuating environments. We find that different patterns of environmental fluctuations select for distinct growth profiles. Slow-growing strains repeatedly outcompete fast-growers when evolved in rapidly changing environments. In a range of environments with asymmetric nutrient availability, evolution reproducibly leads to the robust diversification of two coexisting strains. We develop a theoretical framework based on adaptive dynamics which quantitatively predicts these evolutionary outcomes and explains them in terms of the growth-lag tradeoff that all cells face. Finally, we show that the model can reproduce several patterns in growth-rate data from closely-related strains. Our results highlight that bacterial growth rates can rapidly adapt to their recent environmental history by proteome allocation alone, in ways that often oppose expectations based on nutrient quality.

evolutionary biology↗

bioRxiv2025

Vocal sequences of diverse parrots suggest an important role for note repetition

Sequencing and syntax in complex animal vocal signals have been studied using several mathematical analyses. Commonly, sequences of vocalizations are assumed to follow a first-order Markov process, where each state depends on the state immediately before it. However, more recent computational analyses challenge this assumption, suggesting alternative processes may be important in vocal sequences. Open-ended vocal learners such as parrots possess complex, variable vocal sequences that may be dynamically modified throughout their lives and contain information about group membership and identity. Although this makes them important systems in which to identify general patterns within vocal sequences, parrot vocalizations remain generally understudied compared to passerine birds. Here, we examined vocal sequence structure in six species of parrots (Psittaculidae). We fit various metrics of sequence structure to those generated by multiple simulated processes, including Markov, random, hidden Markov and renewal processes. Two metrics exhibited the best fit to a renewal process (where a note repeats a certain number of times before transitioning to a new note), and two others to Markov processes. Importantly, all analyses were broadly concordant across species, and multiple metrics indicated an elevated probability of note repetition. Reconciling these results, we suggest a general vocal mechanism across the highly variable vocal sequences of parrots, where both note repetition and Markov processes are important. Note repetition patterns could help communicate individual or group identity, as well as social and behavioral context. Our study thus extends a simulation-based approach using diverse metrics to comparatively examine the complex, variable vocal sequences of these open-ended vocal learners.

animal behavior and cognition↗