MS07 - ECOP-1
Student-Alumni Council Room (#2154) in The Ohio Union

Microbial and ecological dynamics across the many natural scales

Thursday, July 20 at 04:00pm

SMB2023 SMB2023 Follow Thursday during the "MS07" time block.
Room assignment: Student-Alumni Council Room (#2154) in The Ohio Union.
Note: this minisymposia has multiple sessions. The other session is MS06-ECOP-1 (click here).

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Christopher Heggerud, Tyler Meadows


Biological interactions occur in a myriad of different temporal, spatial, and ecological scales. Explicit consideration of such multiscale dynamics has led to a much deeper understanding of ecological phenomena and has left even more unanswered questions. In this session we wish to explore the scientific advances that have taken place in modeling biological dynamics that occur on the various natural scales. In particular we highlight transient dynamics that occur on biologically relevant timescales, trophic interactions among species of various size scales, and community dynamics that can occur on various spatial scales. The goal of this session is to highlight the many different scales involved in biological dynamics, discuss the useful mathematical tools for studying such systems and to show comparison by giving examples within both ecological and microbial systems.

Kara Taylor

University of Florida (Department of Biology)
"Simulating microbial metacommunities within the constraints of expected mean-variance relationships"
Taylor's Power Law (TPL) is one of the few established laws in ecology, applicable to both single-species populations and communities. The relationship between species abundance means and variances calculated across mixed-species aggregates is an indicator of joint species distribution. Additionally, TPL is useful for diagnosing instances of observed unusual population distribution. One such instance is sample saturation, in which the finite capacity of a sample unit is reached, variance declines, and the mean-variance relationship takes on an inverse parabolic shape. High-diversity systems like microbiomes are excellent for exploring the properties of community TPLs; however, their complexity obfuscates analysis of generating processes. Agent-based models are a useful tool in studying complex systems. In these bottom-up models, system-level properties emerge from numerous interactions in a set environment. By altering the processes defining interactions between individuals, one can change the state of an emergent property in a quantifiable way. In this simulation study, we use an agent-based model to test ecological processes that generate abundance mean-variance relationships observed in nature. The processes under investigation are dispersal, diversification, and ecological drift, parameterized as inter-host transmission, microbial speciation rate, and microbial growth under host growth conditions, respectively. The model utilizes a finite area (simulating a host gut, for example) for microbial occupancy, and as such, we expect to observe sample saturation. We find that, of the three processes parameterized, microbial dispersal between hosts alone acts to stabilize TPL towards expectation. In the absence of dispersal, sample saturation affects the TPL of rare species but not dominant species. This effect generates aberrant mean-variance relationships across the community that we tentatively interpret as Allee effects in the closed environment. In this system, dispersal may be stabilizing because it allows poor competitors to be rescued by neighboring populations, thereby alleviating positive density dependence.
Additional authors: Matthieu Barbier, Plant Health Institute Montpellier, CIRAD, Universite de Montpellier, Montpellier, France; Mathew A. Leibold, Dept of Biology, University of Florida, Gainesville, Florida, USA

James Powell

Utah State University (Mathematics and Statistics)
"Homogenization across scales reveals relative strengths of environmental and direct transmission of Chronic Wasting Disease in deer"
Chronic Wasting Disease is an untreatable, fatal prion disease of deer and related species, spread both directly and by indirect contact with environmental reservoirs of the pathogen. Over the last twenty years the disease has spread across North America, and prevalence is approaching 40% in some highly impacted areas. The prion, a misfolded version of a naturally occurring protein, is very stable and remains infectious for years, even when exposed to ambient cold, heat and UV. However, experiments indicate that indirect transmission depends on exceeding a critical exposure. Thus the infectious landscape is sensitive to deer aggregation (and subsequent pathogen deposition) in desirable habitats, which vary on the scale of tens of meters, while home ranges are of kilometer size and some individuals relocate home ranges over tens of kilometers. We introduce a reaction-diffusion PDE model, including terms for pathogen deposition and critical environmental hazard to exposure. The model includes spatially explicit aggregation and the potential for developing prion hot-spots via an ecological diffusion model for deer movement. The technique of homogenization reveals emergent disease behavior on large scales, and the impact of critical exposure integrated across aggregating habitats appears as an Allee effect for disease prevalence. This raises the possibility that waves of disease are `pushed’ by the accumulation of prions in pathogen reservoirs, as opposed to being `pulled’ by the movement of infected individuals into regions where R0 > 1. In fact, parameter estimates show that the critical population susceptible density is almost always too high to give R0>1 via direct transmission. We tease out the relative contribution of indirect and direct transmission pathways for CWD spread in southwestern Wisconsin, USA, the epicenter of an outbreak which has been spreading among White Tail Deer for over twenty years.
Additional authors: William J. McClure

Chris Heggerud

UC Davis (Environmental Science and Policy)
"A model free method of predicting transient dynamics."
Transient dynamics are referred to as those dynamics that happen on ecologically relevant timescales, in which classical modelling techniques often fail to capture. Due to the ever changing environments and ecosystems, increased interest has been placed on the study of transient dynamics. However, many of the advances made towards understanding transients are fundamentally mathematical and beg to be connected to ecology and ecological data. In this talk I will show how uniting the underlying theory of dynamical attractors and empirical dynamical modelling we can understand when an ecological system is in a transient state based solely on ecological time series data. We further show that several metrics can be used to predict when a transient event is coming to an end. This work connects the mathematical literature on transient dynamics to the real-world application of understanding transients and short term changes in ecological systems.
Additional authors: Alan Hastings

Punit Gandhi

Virginia Commonwealth University (Department of Mathematics and Applied Mathematics)
"Conceptual modeling of dryland vegetation patterns across timescales"
Strikingly regular, large-scale patterns of vegetation growth were first documented by aerial photography in the Horn of Africa circa 1950 and are now known to exist in drylands across the globe.  The patterns often appear on very gently sloped terrain as bands of dense vegetation alternating with bare soil, and models suggest that they may be a strategy for maximizing usage of the limited water available.  A particular challenge for modeling these patterns is appropriately resolving fast processes such as surface water flow during rainstorms while still being able to capture slow dynamics such as the uphill migration of the vegetation bands, which has been observed to occur on the scale of a band width per century.  We propose a pulsed-precipitation model that treats rainstorms as an instantaneous kick to the soil water as it interacts with vegetation on the timescale of plant growth. The model allows for predictions about the influence of storm characteristics on the large-scale patterns. Analysis and simulations suggest that the distance water travels on the surface before infiltrating into the soil during a typical storm plays a key role in determining the spacing between the bands.
Additional authors: Lily Liu, Mary Silber

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Annual Meeting for the Society for Mathematical Biology, 2023.