Leading Students to Investigate Diffusion as a Model of Brine Shrimp Movement

Kohler, Brynja; Swank, Rebecca; Haefner, James W.; Powell, James A.

doi:10.1007/s11538-009-9444-4

Cited by 14 publications

(13 citation statements)

References 10 publications

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“…A c c e p t e d M a n u s c r i p t 11 Throughout the semester, students studied population growth, enzyme kinetics, random walks and glucose homeostasis in the laboratory and used mathematical models to help them understand the underlying mechanisms of the observed dynamics. A brief description of each exercise is given below.…”

Section: Downloaded By [New York University] At 22:22 13 July 2015mentioning

confidence: 99%

“…We explored random walks with three experiments: a coin flip approach to assign movement of a single particle in a plane, a chemical diffusion model of dye from a "point source" in agar, and small aquatic invertebrate movement in a two dimensional space ( [11], [12]). The coin flip model of a single particle's trajectory proved to be interesting as it clearly showed the role of stochasticity.…”

Section: Diffusionmentioning

confidence: 99%

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Experimenting with Mathematical Biology

Sanft¹,

Angelelli

2015

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St. Olaf College recently added a Mathematical Biology concentration to its curriculum. The core course, Mathematics of Biology, was redesigned to include a wet laboratory. The labs required students to collect data and implement the essential modeling techniques of formulation, implementation, validation, and analysis. The four labs investigated population growth, enzyme kinetics, glucose-insulin feedback and random walks/diffusion. Based on assessment data, having the lab and class juxtaposed was an effective way to reinforce mathematical concepts and encourage collaboration among students with different majors. We discuss key factors that permitted this course's development, the continuing challenges, and how this model might be adapted to other venues.

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Section: Downloaded By [New York University] At 22:22 13 July 2015mentioning

confidence: 99%

Section: Diffusionmentioning

confidence: 99%

Experimenting with Mathematical Biology

Sanft¹,

Angelelli

2015

PRIMUS

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“…We use Artemia spp., a genus of saltwater plankton commonly known as brine shrimp, to experimentally quantify how the presence, height, and density of simplified macrophytes alter their distributions in flow. Brine shrimp, also known as sea monkeys, serve as an excellent model organism given their availability and ease of culturing [39]. Experimentally derived "diffusion" coefficients describing the random active movements of newly hatched nauplii have been determined previously by Kohler et al [39].…”

Section: Introductionmentioning

confidence: 99%

“…Brine shrimp, also known as sea monkeys, serve as an excellent model organism given their availability and ease of culturing [39]. Experimentally derived "diffusion" coefficients describing the random active movements of newly hatched nauplii have been determined previously by Kohler et al [39]. This organismal system can also be used to develop behavioral models such as movement towards light or a concentration gradient.…”

Section: Introductionmentioning

confidence: 99%

Experiments and Agent Based Models of Zooplankton Movement within Complex Flow Environments

et al. 2020

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The movement of plankton is often dictated by local flow patterns, particularly during storms and in environments with strong flows. Reefs, macrophyte beds, and other immersed structures can provide shelter against washout and drastically alter the distributions of plankton as these structures redirect and slow the flows through them. Advection–diffusion and agent-based models are often used to describe the movement of plankton within marine and fresh water environments and across multiple scales. Experimental validation of such models of plankton movement within complex flow environments is challenging because of the difference in both time and spatial scales. Organisms on the scale of 1 mm or less swim by beating their appendages on the order of 1 Hz and are advected meters to kilometers over days, weeks, and months. One approach to study this challenging multiscale problem is to insert actively moving agents within a background flow field. Open source tools to implement this sort of approach are, however, limited. In this paper, we combine experiments and computational fluid dynamics with a newly developed agent-based modeling platform to quantify plankton movement at the scale of tens of centimeters. We use Artemia spp., or brine shrimp, as a model organism given their availability and ease of culturing. The distribution of brine shrimp over time was recorded in a flow tank with simplified physical models of macrophytes. These simplified macrophyte models were 3D-printed arrays of cylinders of varying heights and densities. Artemia nauplii were injected within these arrays, and their distributions over time were recorded with video. The detailed three-dimensional flow fields were quantified using computational fluid dynamics and validated experimentally with particle image velocimetry. To better quantify plankton distributions, we developed an agent-based modeling framework, Planktos, to simulate the movement of plankton immersed within such flow fields. The spatially and temporally varying Artemia distributions were compared across models of varying heights and densities for both the experiments and the agent-based models. The results show that increasing the density of the macrophyte bed drastically increases the average time it takes the plankton to be swept downstream. The height of the macrophyte bed had less of an effect. These effects were easily observed in both experimental studies and in the agent-based simulations.

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“…They introduced sophisticated mathematical analyses and modeling projects into beginning biology labs (Kohler et al , 2010). John Milton (Professor of Computational Neuroscience in the joint science department of Claremont/McKenna, Pitzer, and Scripps Colleges) reported on multiple initiatives in mathematical biology, including a program that sends teams of undergraduate research students out to industrial sites to solve applied problems 5 …”

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confidence: 99%