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Computer Science Department 
Montana State University
Bozeman, MT 59717
Dr. Clemente Izurieta
Tel: (406) 994-3720
Fax: (406) 994-4376

Department of Land Resources and Environmental Sciences   
Montana State University
P.O. Box 173120
Bozeman, MT 59717-3120
Dr. Geoffrey Poole
Tel: (406) 994-5564
Fax: (406) 994-3933

Dr. Robert Payne

Tel: (406) 994-7197

Department of Computer Science Undergraduate Research

Isaac Griffith
Stuart Winslow
Ryan Nix


Computational Ecology Research Group


Computational Ecology

The computational ecology research group is concerned with the advancement of scientific processes and research of new techniques to model environmental processes.  We focus on modeling scientific information in the fields of hydrology and ecological landscapes.

An on-going collaboration between the Department of Land Resources and Environmental Sciences and the Computer Science Department is exploring new challenging techniques and algorithms to model and represent complex ecosystem processes such as nitrogen cycling in streams.

Many opportunities exist for ecologists and computer scientists.  In particular, we are interested in:

  • Visualization techniques of complex, multi-dimensional flow networks
  • Dependency tracking algorithms
  • Efficient multi-threading models
  • Multi-scale representation of ecological data


The following is a visual representation of a hydrological landscape.  It shows a simple network of various (multi-dimensional) currencies fluxing through intrconnected nodes.


A flux Network

An Introduction to NEO

Network Exchange Objects (NEO) is a new software framework designed to facilitate simulation modeling of ecosystems, where the ecosystem is represented as a Scape, through which Resources (e.g., water, heat, nutrients, and energy) are fluxing.

A current example of a NEO-based model is the Water Resources Exchange Network model (WREN), which is designed for modeling river floodplain ecosystems.  First, water movement and exchanges are simulated through surface and subsurface flows.  This water movement is organized into exchanges among a network of storage cells, where each cell represents specific location upon or within the floodplain.  Second, additional resource networks link carbon, nitrogen, and oxygen movement to the water movement, because water tends to be the dominant media for resource movement in rivers.  Biological processing of these resources is also simulated in these networks, where carbon, nitrogen, and oxygen in the water are consumed or produced by biochemical reactions in river microbial communities.  In this way, combined resource simulation within the WREN model provides a holistic view of water quality and quantity across a floodplain, benefitting both managerial and scientific pursuits regarding rivers.

Carbon, nitrogen, and oxygen are strong influences on water quality and subsequently influence the ecosystem services a river can provide, such as: general recreation; drinking water supply; or recreational and commercial fisheries.  Scientists use models such as WREN as a highly detailed definition of how we think the physics and life within the system support these services.  The scientific goal is to find locations or times that the model does not work, and use this information to design experiments that eventually lead to model enhancements.  Meanwhile, managers may use the same models to assist with decisions about river systems.  For example, WREN may be used to determine how controlled changes to water flow (perhaps from a dam outlet), might affect the quality and quantity of water across a downstream floodplain.  Of course, managers and scientists need to communicate about scenarios where or when a given model is not likely to work, in order to know where or when that model is useful for making sound decisions.

Because these models are highly detailed and often need to be executed thousands or tens of thousands of times, their application requires substantial computational power.  For example, though WREN is usually applied to individual floodplains (perhaps ~5 km long and ~1 km wide), it simulates resource behavior at sufficient detail to require processing power similar to global-scale water supply models.  We are currently using the RMSC and WREN to simulate the Nyack floodplain near Glacier National Park and Flathead Lake in northwest Montana.  Our current model executions focus on simulating floodplain response to changes in river flow expected from multiple climate change scenarios.  The goal of this work is to understand what aspects of water quality and quantity may change in the upcoming decades, and thus provide information on what aspects of this change are most likely to influence management decisions.  This effort is likely to require a sensitivity analysis, where multiple concurrent executions across parallel processors will explore which combinations of inputs have the largest effect on model output.  For example, a sensitivity analysis may provide information on which aspects of climate change are most likely to change the amount of water, carbon, nitrogen, and oxygen across the floodplain.  The RMSC provides parallel computing power that would otherwise be unavailable to execute these simulations, thus greatly improving the efficiency of this work.

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Updated: 3/26/2010


Research News

Article  in the Exponent

CERG is actively using supercomputing capabilities from:

Rocky Mountain Super Computing

Article  in the Butte Standard


Modeling Ecosystems with Network Exchange Objects (NEO)

Modeling interactions between surface and subsurface temperature dynamics in floodplains

Ecological Systems as CAHNs

Fluvial Landscape Laboratory




Montana State University 2006

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