Individual-based modeling of genome evolution in haplodiploid organisms

Ants, bees, wasps, bark beetles, and other species have haploid males and diploid females. Although such haplodiploid species play key ecological roles and are threatened by environmental changes, no general framework exists for simulating their genetic evolution. Here, we use the SLiM simulation environment to build a novel model for individual-based forward simulation of genetic evolution in haplodiploid populations. We compare the fates of adaptive and deleterious mutations and find that selection is more effective in haplodiploid species than in diploid species. Our open-source model will help understand the evolution of sociality and how ecologically important species may adapt to changing environments.

USING INDIVIDUAL-BASED MODELING TO BETTER UNDERSTAND THE HIDDEN CURRICULUM OF ENGINEERING

Engineering culture perpetuates norms that are unwelcoming to minoritized identities, particularlywomen and racialized folks. A theory useful for understanding this is “hidden curriculum” whichdescribes the assumptions and beliefs that are unintentionally and implicitly taught in engineeringeducation. This paper outlines an initial conceptual model for using IBM (individual-based modeling) to better understand the hidden curriculum of engineering. We provide an overview of the driving question behind the model design, the agents and their attributes, the rules andprocesses which change these attributes, and the scale of the model. This overview of the model building process provides insight into the model design for simulating and better understanding the perpetuation of the hidden curriculum within engineering education.

Stochastic branching at the edge: individual-based modeling of tumor cell proliferation

An individual-based model of stochastic branching is proposed and studied, in which point particles drift in $$\bar{\mathbb {R}}_{+}:=[0,+\infty )$$ R ¯ + : = [ 0 , + ∞ ) toward the origin (edge) with unit speed, where each of them splits into two particles that instantly appear in $$\bar{\mathbb {R}}_{+}$$ R ¯ + at random positions. During their drift, the particles are subject to a random disappearance (death). The model is intended to capture the main features of the proliferation of tumor cells, in which trait $$x\in \bar{\mathbb {R}}_{+}$$ x ∈ R ¯ + of a given cell is time to its division and the death is caused by therapeutic factors. The main result of the paper is proving the existence of an honest evolution of this kind and finding a condition that involves the death rate and cell cycle distribution parameters, under which the mean size of the population remains bounded in time.

A model to illustrate the potential pairing of animal biotelemetry with individual-based modeling

Background Animal biotelemetry and individual-based modeling (IBM) are natural complements, but there are few published examples where they are applied together to address fundamental or applied ecological questions. Existing studies are often found in the modeling literature and frequently re-use small datasets collected for purposes other than the model application. Animal biotelemetry can provide the robust measurements that capture relevant ecological patterns needed to parameterize, calibrate, and assess hypotheses in IBMs; together they could help meet demand for predictive modeling and decision-support in the face of environmental change. Results We used an simple exemplar IBM that uses spatio-temporal movement patterns of 103 acoustic-tagged juvenile yearling Chinook salmon (Oncorhynchus tshawytscha), termed ‘smolts’, to quantitatively assess plausibility of two migratory strategies that smolts are hypothesized to use while migrating north through the plume of the Columbia River (United States of America). We find that model smolts that seek to maximize growth demonstrate movement patterns consistent with those of tagged smolts. Model smolts that seek to move quickly out of the plume region by seeking favorable currents do not reproduce the same patterns. Conclusions Animal biotelemetry and individual-based modeling are maturing fields of inquiry. Our hope is that this model description and the basic analytical techniques will effectively illustrate individual-based models for the biotelemetry community, and perhaps inspire new collaborations between biotelemetry researchers and individual-based modelers.

A Model to Illustrate the Potential Pairing of Animal Biotelemetry with Individual-Based Modeling

Background. Animal biotelemetry and individual-based modeling (IBM) are natural complements, but there are few published examples where they are applied together to address fundamental or applied ecological questions. Existing studies are often found in the modeling literature and frequently re-use small datasets collected for purposes other than the model application. Animal biotelemetry can provide the robust measurements that capture relevant ecological patterns needed to parameterize, calibrate, and assess hypotheses in IBMs; together they could help meet demand for predictive modeling and decision-support in the face of environmental change. Results. We used an simple exemplar IBM that uses spatio-temporal movement patterns of 103 acoustic-tagged juvenile yearling Chinook salmon (Oncorhynchus tshawytscha), termed ‘smolts’, to quantitatively assess plausibility of two migratory strategies that smolts are hypothesized to use while migrating north through the plume of the Columbia River (United States of America). We find that model smolts that seek to maximize growth demonstrate movement patterns consistent with those of tagged smolts. Model smolts that seek to move quickly out of the plume region by seeking favorable currents do not reproduce the same patterns. Conclusions. Animal biotelemetry and individual-based modeling are maturing fields of inquiry. Our hope is that this model description and the basic analytical techniques will effectively illustrate individual-based models for the biotelemetry community, and perhaps inspire new collaborations between biotelemetry researchers and individual-based modelers.