Microorganisms often live in fluctuating environments. For example, the gut microbiota of a host experience fluctuating resources due to the host’s feeding rhythm (e.g., the host is eating food or starving). As recent studies show that species interactions can change depending on the amounts of resources and toxin, environmental fluctuations are then expected to change species interactions. Such changes in species interactions can result in those in species diversity. However, the time scales of environmental fluctuations may vary; in the example of the gut microbiota, some hosts may eat food three times per day while other hosts may eat more in a day (like some of you during working from home).
How does a rate of environmental fluctuations affect species interactions and diversity? We addressed this question by building a mathematical model that describes the dynamics of resources, toxins, and microbial species in a chemostat where resource supplies switch. The strength of competition between species differed over the switching rate, but it peaked at either low, high, or intermediate switching rates depending on the species’ sensitivity to toxins. Importantly, however, we can predict how species diversity changes over the switching rate once we know how the strength of competition between two species changes. Such prediction works from two- to ten-species communities.
In sum, predicting the effect of environmental switching on competition and species diversity is difficult, because the properties of community members also matter. By regarding a rate of environmental switching rate as a frequency of disturbance, these results may explain the contradicting results of earlier studies on the intermediate disturbance hypothesis. Species diversity is not always maximized at an intermediate frequency of disturbance (or an intermediate switching rate).
I would like first to thank my collaborators Professors Mostafa B. (from Univ. of Bordeaux, France), Elmadhi E. (Univ. of Cadi Ayyad, Morocco) and Fahd K(Univ. of Cadi Ayyad, Morocco), where without them nothing of this would be possible to achieve.
Our work is an investigation of dengue disease spread using a PDE mathematical model with a diffusion term as the mobility for both populations, human and mosquito. We simulated scenarios for the disease using data with respect to dengue in Brazil.
We also analyzed the dynamic of the disease applied mechanical control in the aquatic phase of mosquito, in order to minimize the infected human population. We may conclude that optimal control is the more accurate result in terms of government investments of dengue disease detraction.
I am Vahini Nareddy, a physics graduate student from UMass Amherst working in the area of classical statistical mechanics with application to ecology. Currently, I am working with Prof. Jon Machta towards my dissertation titled “Dynamical models of statistical physics for spatially-coupled ecological oscillators”. We work in collaboration with Prof. Alan Hastings and Dr. Shadisadat Esmaeili from UC Davis and Prof. Karen Abbott from Case Western.
Our research focuses on understanding and predicting emergent dynamical phenomena in spatially-coupled ecological systems. In graduate school, I was drawn to this research problem primarily due to a chance to work on applications of “Ising universality class”. Different systems such as magnets, neurons and masting trees share common behaviors near the critical transition. This phenomenon of sharing properties exactly among different systems is known as “universality” and is well studied in statistical physics. The Ising model in two dimensions is one of the simplest statistical models initially developed to explain the arrangement of electronic spins (either up or down) in magnets. Spatially-coupled, two-cycle ecological oscillators and many other systems share common features with Ising model and hence exist in Ising universality class. This ensures that a simple Ising model can replicate long-time properties of these ecological systems.
Our research currently focuses rather on dynamics of ecological oscillators. More traditionally this problem has been studied using nonlinear dynamical models and coupled lattice maps whereas our approach for this problem involves using techniques from statistical physics. Specifically, we use a dynamical Ising model with memory to represent the ecological oscillators with two-cycle behavior. This approach is advantageous in revealing properties essential for synchrony and can be more generally applied to other systems which lack details about underlying mechanisms. We use maximum likelihood inference methods and forecast prediction tools for analyzing the dynamics.
We have recently submitted this work to a journal and interested readers can check it out on the arXiv. This work encourages us to approach other complex biological and ecological systems which share common features with other universality classes.
I want to thank SMB for this award and also for giving me a chance to participate in the poster session and interact with peers from different backgrounds working on interdisciplinary research topics. My experience has been great and unique as this was my first virtual poster session and also my first professional society meeting outside traditional physics conferences.
A postdoctoral position is available immediately at the University
of Ottawa. The position is in collaboration with Environment and
Climate Change Canada. The goal is to use mechanistic models for fish
population dynamics and movement in watersheds to explore the
potential
use of structural indicators for fish conservation. Please email Prof
Frithjof Lutscher for more information.
I would like first to thank my collaborators Professors Mostafa B. (from Univ. of Bordeaux, France), Elmadhi E. (Univ. of Cadi Ayyad, Morocco) and Fahd K(Univ. of Cadi Ayyad, Morocco), where without them nothing of this would be possible to achieve.
Our work is an investigation of dengue disease spread using a PDE mathematical model with a diffusion term as the mobility for both populations, human and mosquito. We simulated scenarios for the disease using data with respect to dengue in Brazil.
We also analyzed the dynamic of the disease applied mechanical control in the aquatic phase of mosquito, in order to minimize the infected human population. We may conclude that optimal control is the more accurate result in terms of government investments of dengue disease detraction.
