2024 CSDMS meeting-093: Difference between revisions
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|CSDMS meeting abstract title=Emergent dynamics of soil production and sediment transport revealed using Agent-Based Models of biological agents | |||
|Working_group_member_WG_FRG=Terrestrial Working Group, Critical Zone Focus Research Group | |||
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|CSDMS meeting coauthor first name abstract=Gregory | |||
|CSDMS meeting coauthor last name abstract=Tucker | |||
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|CSDMS meeting coauthor first name abstract=Robert | |||
|CSDMS meeting coauthor last name abstract=Anderson | |||
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|CSDMS meeting coauthor first name abstract=Suzanne | |||
|CSDMS meeting coauthor last name abstract=Anderson | |||
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|CSDMS meeting abstract=In complex systems, emergence occurs when a ‘new’ property arises at higher levels of organization that cannot be directly deduced from the behavior of constituent elements. While many geomorphic systems exhibit emergence, numerical models of surface processes typically address emergence by carefully selecting the appropriate spatio-temporal scale to parameterize the relevant physics, chemistry, and biology that is occurring at lower levels of organization. This is an effective strategy where finer-scale processes are either poorly constrained or intractable to model numerically. The concept of the geomorphic transport law reifies this strategy by adopting a ‘top down’ approach where surface processes are encoded into the set of partial differential equations chosen. However, as data resolution and computational power increase, there are new opportunities to build models that simulate processes from the ‘bottom up’. | |||
One such opportunity is in the simulation of biologically driven soil production and sediment transport. Biological systems exhibit some of the most compelling examples of emergence (e.g., insect societies, flocking behavior, fairy circles) that are readily simulated using Agent-Based Models (ABMs). Given that biota drive many of the most widely used geomorphic transport laws, it is worth taking stock of whether ABMs can provide new insights into surface process modeling. We present two promising examples where we think ABMs might provide new, testable predictions of soil production and sediment transport. The first example focuses on tree seeding, recruitment, growth, and death. Rules for soil production via tree root growth monotonically decrease with soil depth. However, because soil production in the model depends not only on individual tree root growth but also the probability of an unstressed tree growing at any given location, humped soil production functions emerge over the long-term. The second example focuses on one hypothesized mechanism for mima mound formation. Rules for burrowing organisms allow for preferential upslope transport of sediment into mounds while gravitational processes (i.e., creep) degrade mounds. Both examples highlight how ABMs help make rules for ecological dynamics explicit. Bulk coefficients common to conventional treatments of soil production and sediment transport laws are thus allowed to emerge from the empirically constrained rulesets that are used. | |||
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Revision as of 17:05, 1 April 2024
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Emergent dynamics of soil production and sediment transport revealed using Agent-Based Models of biological agents
Matthew Rossi,
University of Colorado Boulder , United States. matthew.rossi@colorado.edu
Gregory Tucker, , United States.
Robert Anderson, , United States.
Suzanne Anderson, , United States.
In complex systems, emergence occurs when a ‘new’ property arises at higher levels of organization that cannot be directly deduced from the behavior of constituent elements. While many geomorphic systems exhibit emergence, numerical models of surface processes typically address emergence by carefully selecting the appropriate spatio-temporal scale to parameterize the relevant physics, chemistry, and biology that is occurring at lower levels of organization. This is an effective strategy where finer-scale processes are either poorly constrained or intractable to model numerically. The concept of the geomorphic transport law reifies this strategy by adopting a ‘top down’ approach where surface processes are encoded into the set of partial differential equations chosen. However, as data resolution and computational power increase, there are new opportunities to build models that simulate processes from the ‘bottom up’.
One such opportunity is in the simulation of biologically driven soil production and sediment transport. Biological systems exhibit some of the most compelling examples of emergence (e.g., insect societies, flocking behavior, fairy circles) that are readily simulated using Agent-Based Models (ABMs). Given that biota drive many of the most widely used geomorphic transport laws, it is worth taking stock of whether ABMs can provide new insights into surface process modeling. We present two promising examples where we think ABMs might provide new, testable predictions of soil production and sediment transport. The first example focuses on tree seeding, recruitment, growth, and death. Rules for soil production via tree root growth monotonically decrease with soil depth. However, because soil production in the model depends not only on individual tree root growth but also the probability of an unstressed tree growing at any given location, humped soil production functions emerge over the long-term. The second example focuses on one hypothesized mechanism for mima mound formation. Rules for burrowing organisms allow for preferential upslope transport of sediment into mounds while gravitational processes (i.e., creep) degrade mounds. Both examples highlight how ABMs help make rules for ecological dynamics explicit. Bulk coefficients common to conventional treatments of soil production and sediment transport laws are thus allowed to emerge from the empirically constrained rulesets that are used.
