Predicting ecological dynamics in fluctuating environments

Tuesday, June 15 at 04:15am (PDT)
Tuesday, June 15 at 12:15pm (BST)
Tuesday, June 15 08:15pm (KST)

SMB2021 SMB2021 Follow Monday (Tuesday) during the "MS06" time block.
Note: this minisymposia has multiple sessions. The second session is MS07-EVOP (click here).

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Anna Miller (Department of Integrated Mathematical Oncology, Moffitt Cancer Center, United States), Nancy Huntly (Ecology Center and Department of Biology, Utah State University, United States)


Most living organisms, from bacteria to animals, experience temporal fluctuations in their environment. For example, bacteria may face fluctuating periods of antibiotic exposure, or animals experience variations in temperature and resources. To survive through stressful environments, organisms have evolved strategies such as phenotypic plasticity for predictable fluctuations, or bet-hedging for unpredictable fluctuations. Furthermore, temporal variability in resources or treatment can promote coexistence between species or strains that did not occur in constant environments through mechanisms including the storage effect and relative nonlinearity. Mathematical modeling is a useful framework to study how the rate of fluctuations impacts the dynamics of heterogeneous populations, which is useful for a variety of applications including predicting changes to biodiversity due to climate change, or response of coexisting populations of sensitive and resistant cancer cells to treatment. In this minisymposium, we aim to bring together researchers that use both theoretical and experimental approaches in a variety of ecosystems to share ideas centered around the common theme of species evolution and coexistence in fluctuating environments.

Ivana Gudelj

(Biosciences, University of Exeter, UK)
"Predicting community dynamics of antibiotic sensitive and resistant species in fluctuating environments"
Microbes occupy almost every niche within and on their human hosts. Whether colonising the gut, mouth or bloodstream, microorganisms face temporal fluctuations in resources and stressors within their niche. Yet we still know little of how environmental fluctuations mediate certain microbial phenotypes, notably antimicrobial resistant ones. For instance, do rapid or slow fluctuations in nutrient and antimicrobial concentrations select for, or against, resistance? We tackle this question using an ecological approach by studying the dynamics of a synthetic and pathogenic microbial community containing two species, one sensitive and one resistant to an antibiotic drug where the community is exposed to different rates of environmental fluctuation. We provide mathematical models, supported by experimental data, to demonstrate that simple community outcomes, like competitive exclusion, can shift to coexistence and ecosystem bi-stability as fluctuation rates vary. Theory gives mechanistic insight into how these dynamical regimes are related. Our approach highlights a fundamental difference between resistance in single species populations and in communities. While fast environmental changes are known to select against resistance in single-species populations, here we show that they can promote the resistant species in mixed-species communities. Our theoretical observations are verified empirically using a two-species Candida community.

Shota Shibasaki

(Department of Fundamental Microbiology, University of Lausanne, Switzerland)
"Environmental and demographic stochasticity together changes microbial interactions and diversity"
Microorganisms live in environments that fluctuate between mild and harsh conditions. As harsh conditions may cause extinctions, the rate at which fluctuations occur can shape microbial communities and their diversity, but we still lack an intuition on how. Here, we build a mathematical model describing two microbial species living in an environment where substrate supplies randomly switch between abundant and scarce. We then vary the rate of switching as well as different properties of the interacting species, and measure the probability of the weaker species driving the stronger one extinct. We find that this probability increases with the strength of demographic noise, and peaks at either low, high, or intermediate switching rates depending on both species' ability to withstand the harsh environment. This complex relationship shows why finding patterns between environmental fluctuations and diversity has historically been difficult. In parameter ranges where the fittest species was most likely to be excluded, however, the beta diversity in larger communities also peaked. In sum, while we find no simple rules on how the frequency of fluctuations shapes species diversity, we show that their effect on interactions between two representative species predicts how diversity in the whole community will change.

Audrey Freischel

(Department of Integrated Mathematical Oncology, Moffitt Cancer Center, USA)
"Utilizing a Consumer-Resource model to hypothesize foraging trade-offs in “cream skimmers” and “crumb pickers”"
Solid tumors consist of heterogeneous clones presenting unique metabolism and function. Metabolic variation allows cancer cells to be characterized as either “cream-skimmers,” which consume resources quickly at the cost of efficiency (glycolysis), or “crumb-pickers,” which consume resources slowly but have a higher metabolic payoff (oxidative phosphorylation). As observed in nature, fluctuating resources allow for coexistence of different species. To better understand the coexistence of “cream-skimmers” and “crumb-pickers” in the tumor, we utilized a classic consumer-resource model with fluctuating resource to evaluate tradeoffs in encounter probability, handling time, and fixed and variable costs. These models elucidate novel hypotheses in tumor cell competition as well as provide new insights to consumer-resource dynamics.

David Demory

(School of Biological Sciences, Georgia Institute of Technology, USA)
"Temperature drives virus-host coexistence in the ocean"
Diverse marine viruses coexist with microbial hosts across a range of fluctuating marine environments. Here, we used population dynamic models to explore the role of temperature variation in modulating virus-phytoplankton coexistence. Dynamic models suggest that variation in sea surface temperature influences the range of viral life-history traits underlying coexistence amongst virus-microbe pairs, including the prediction that warmer temperatures can suppress viral persistence. Using in situ ocean datasets, we find evidence of a latitudinal trend in viral diversity, decreasing in warmer regions. Yet, we also find that temperature fluctuations can be a driver of coexistence, allowing for a succession of (in)favorable conditions, potentially promoting the coexistence of different virus types infecting the same host via the storage effect. These findings highlight the importance of integrating environmental feedback into the study of host-virus coexistence in the global oceans.

Hosted by SMB2021 Follow
Virtual conference of the Society for Mathematical Biology, 2021.