CT02 - ECOP-2
Cartoon Room 2 (#3147) in The Ohio Union

ECOP Subgroup Contributed Talks

Tuesday, July 18 at 2:30pm

SMB2023 SMB2023 Follow Tuesday during the "CT02" time block.
Room assignment: Cartoon Room 2 (#3147) in The Ohio Union.
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Aneequa Sundus

Indiana University Bloomington
"Investigating the potential for light-mediated spatial-temporal pattern formation in cyanobacteria mixed populations using agent-based modeling"
Cyanobacteria are the largest group of photosynthetic organisms on earth. They can survive in very severe conditions (e.g., in deep oceans and near poles) due to complex mechanisms that help them adapt to the specific light spectrum of their surroundings. They are evolved to adjust their metabolism and photosynthesis optimally to their environment. One such genetic switch found in cyanobacteria is the blue-green light switch: a simple system that is likely transferrable to other bacterial species. Thus, this switch has potential use in new regulatory systems for biotechnology and optogenetics. Additionally, cyanobacteria are phototrophs and are already being used to develop more sustainable biotechnology platforms. Characterizing and optimizing a highly responsive gene regulatory system that works efficiently in individuals and populations of cyanobacteria will help to advance their usefulness in biotechnology and in the production of biofuels. We developed an agent-based model of cyanobacteria mixed populations using PhysiCell, an open source physics-based modeling software. We explored the potential of combining opto-genetic and diffusible chemical controls to guide novel spatiotemporal pattern formation. We experimented with different blue-green light spectrums along with population density and cell motility parameters to probe this system for light mediated spatial pattern formation.
Additional authors: Mohammed Khaled, Indiana University Bloomington David M. Kehoe, Indiana University Bloomington Paul Macklin, Indiana University Bloomington



Laura Wadkin

Newcastle University
"Mathematical and statistical modelling of the spread of tree diseases and invasive pests through forest environments"
The loss of biodiversity due to the spread of destructive tree diseases and invasive pests within forests across the world is having an enormous environmental, economic, and social impact. Enhancing biosecurity is a key priority, through the control of existing diseases and pests, and by building forest resilience against new ones. Thus, we are working in collaboration with multiple forestry partners to develop mathematical models to deepen our understanding of the fundamental behaviours of key pests and pathogens, act as predictive tools for forecasting, and to explore different control strategies. Broadly, we use a combination of partial differential equations, agent-based modelling, and statistical inference techniques. This talk will present an overview of the collaborative work to date, including a case study example of the oak processionary moth infestation in London.



Suman Chakraborty

Friedrich Schiller University Jena
"Selection pressure by specialist and generalist insect herbivores leads to optimal constitutive plant defense. A mathematical model"
Brassicaceae plants have the glucosinolate-myrosinase defense system, jointly active against herbivory. Glucosinolates (GLS) are hydrolyzed by myrosinase to produce isothiocyanates as soon as herbivory begins. Isothiocyanates exert detrimental effects on the feeding insects. However, constitutive GLS defense is observed to occur at levels that do not deter all insects from feeding. That prompts the question of why Brassicaceae plants have not evolved a high constitutive defense. The answer may lie in the contrasting relationship between plant defense and host plant preference of specialist and generalist herbivores. One of the reasons plants are in this dilemma is that they do not know what kind of herbivore will attack them in any given year, and thus have to be prepared for different possibilities. GLS content increases the susceptibility to specialist insects because these are attracted to plants with a high GLS content and are capable of coping with the toxin. In contrast, generalists are deterred by the plant GLS. Although GLS can attract the natural enemies (predators and parasitoids) of these herbivores, enemies can reduce herbivore pressure to some extent only. So, plants can be overrun by specialists if GLS content is too high, whereas generalists can invade the plants if it is too low. Therefore, an optimal constitutive plant defense can minimize the overall herbivore pressure. To explain optimal defense theoretically, we represent the contrasting host selection behavior of insect herbivores and, in addition, the emergence of their natural enemies by a non-autonomous ordinary differential equation model, where the independent variable is the plant GLS concentration. From the model, we quantify the optimal amount of GLS, which minimizes the total herbivore (specialists and generalists) pressure. That quite successfully explains the evolution of constitutive defense in plants from the perspective of optimality theory.
Additional authors: Jonathan Gershenzon & Stefan Schuster



Hong-Sung Jin

Chonnam National University, Korea
"Assessment of American Bullfrog spreading in Korea using cellular automata learning"
The spread of American Bullfrog, one of the 100 of the World’s Worst Invasive Alien Species, has a great impact on the surrounding ecosystem, so it will be very important to find out the possibility of spread by region. We assess whether bullfrogs will continue to spread, stop spreading and maintain populations, or become extinct 60 years after their introduction to Korea. This study is based on the results of national surveys that observed the distribution. The entire data is divided into 25 regional clusters using the Hierarchical clustering method, and the degree of spread is predicted by CNN(Convolution Neural Network) method which trains and learns the rules of ECA(elementary cellular automata) that determine evolution of the clusters. We predict the probabilities of the ECA rules for each cluster. The mean value of the population according to the predicted rules is defined as the spreading intensity and evaluated, which is multiplied by the habitat suitability to get an assessment of bullfrog spreading. Habitat suitability is obtained using Maxent.
Additional authors: Yunju Wi, Department of Mathematics & Statistics, Chonnam National University ; Gyujin Oh, Department of Mathematics & Statistics, Chonnam National University ; Hee-Jin Kang, School of Biological of Sciences and Biotechnology, Chonnam National University ; Seung-ju Cheon, School of Biological of Sciences and Biotechnology, Chonnam National University; Ha-Cheol Sung, Department of Biological Sciences, College of Natural Sciences, Chonnam National University



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