Models for the masses: bringing computational resources for addressing

complex ecological problems to stakeholders

Louis J. Gross, Eric Carr and Mark Palmer

The Institute for Environmental Modeling

Departments of Ecology and Evolutionary Biology and Mathematics

University of Tennessee

ATLSS.org

Policy and management at regional spatial extent requires:

• Ecological models linked to physical process data and models

• Spatial environmental data sets that may be at a variety of spatial and temporal resolutions

• Decision support tools based upon the best available science that allow stakeholders to assess the impacts on natural systems of alternative future actions

• Capability for different stakeholders to establish their own decision criteria

• Methods to link models and data to monitoring protocols

An example: ATLSS - Across Trophic Level System Simulation for Everglades

restoration planning• Provides a general methodology for regional

assessment of natural systems by coupling physical and biotic processes in space and time using a mixture of modeling approaches.

• Utilizes the best available science and intuition of many biologists with extensive field experience to construct models for particular system components and link these at appropriate spatial and temporal resolutions

ATLSS Objectives (Con’d)

• Provide a method to compare the relative impacts of alternative management of the region on the natural systems, so different stakeholders can focus on sub-regions, species, or conditions of particular interest to them.

• Ensure that the structure of the multimodel is extensible so that as new models, data and monitoring information becomes available, it may be efficiently utilized.

Computational ecology offers opportunities to develop spatially-explicit models at a variety of levels of complexity to inform public policy on matters such as regional water management, reserve design, harvesting, biocontrol, and monitoring schemes.

Such models (which may be discrete or continuous dynamical systems, individual-based, or mixtures of these) can produce enormous amounts of spatio-temporal data, and typically include uncertainty in inputs, model structure, and parameterization.

How can we best utilize models to inform public policy and educate stakeholders?

Radio-telemetryTracking Tools

Abiotic Conditions Models

Spatially-Explicit Species Index Models

Linked Cell Models

Process Models

Age/Size Structured Models

Individual-Based Models

High Resolution HydrologyHigh Resolution Topography Disturbance

Cape Sable Seaside Sparrow

Snail Kite

Long-legged Wading Birds

Short-legged Wading Birds

White-tailed Deer

Alligators

Lower Trophic Level Components Vegetation

Fish Functional Groups Alligators Reptiles and Amphibians

White-tailed Deer

Florida Panther

Snail Kite

Wading Birds

© TIEM / University of Tennessee 1999

Cape Sable Seaside Sparrow

What is computationally challenging in this?

• Space-time linkages• GIS very limited at dynamic modeling• Different components operate on different scales

(resolution required differs between components)• Model data can be huge

• Models are complex• Large state variable dynamical systems• Large numbers of interconnected agents• Models are not independent - multimodeling

Difficulties faced in providing access to complex computational models

• Agencies do not have appropriate in-house computational facilities or support

• Agency staff wish to focus their time on analysis of appropriate information for policy input, not on carrying out simulations

• It is inefficient to have each agency carry out simulations, yet each needs the capability to obtain simulations tailored to their needs.

Agencies involved in Everglades restoration: U.S. Army Corps of Engineers Environmental Protection Agency National Park Service National Marine Fisheries Service Natural Resources Conservation Service U.S. Fish and Wildlife Service Florida Department of Agriculture and Consumer Services Florida Department of Environmental Protection Florida Game and Fresh Water Fish Commission South Florida Water Management District Miccosukee Tribe Seminole Tribe plus input from numerous NGO's and individuals.

What have we done to address these needs?

• Developed a Model Interface to provide stakeholder agencies with capability to run ATLSS models

• Utilize grid-computing to make computational resources of Univ. of Tenn. available to approved users

• Underlying methods are transparent to the user• Users are given options as to models to run,

certain model parameters to be set, and scenarios to utilize

• Provides output that users import into the ATLSS Dataviewer on their desktop to carry out their own assessments

SESI Output for Long-Legged Wading Birds in N. Taylor Slough: For 1993

LINUX PC SOLARISUNIX

•Purchase Cost•Systems Administration•User Knowledge Base•Storage Needs

Multiple Hardware Requirements

MATLAB C++, C,Fortran

ProprietaryLicensedSoftware

•Software License •Installation•Compiler•Code Control Issues

Software Needs

ATLSS MODELS

• Solaris(primarily), PC, MATLAB based models.

• Long run times from 30min to 36+ hours dependent on model and parameters.

• Output data results ranging from 10 MB to 14 GB.

• Single as well as SMP and cluster based models.

Potential ATLSS Model Users

• Primarily Windows PC based.

• Multiple locations across Florida, US, and Internationally.

• Varying degrees of computer infrastructure and Sys. Admin. Support.

• Desire to run models and not maintain systems.

ATLSS-NetSolve-IBP

A WWW implementation framework for ATLSS models under NetSolve

with IBP file management.

Netsolve

• Single Agent manages Multiple Servers on differing platforms.

• Different servers can have different versions that run same function (SMP, Cluster, linux).

• Allows access to run models on computers without the need for individual system logins or accounts.

• User has no access to actual server hardware, model code, or datafiles.

IBP: Internet Backplane Protocol

• Data Storage Utility.• Data accessed through an ASCII key, called an

EXNODE.• ExNode completely provides access information for

the Data.• Able to perform multithread file transfer for very

quick storage of large files.• HTML, C library, and other access methods.

IBP Data Storage

• The Data File (ascii or binary) is divided into pieces.

• Each piece is stored on an IBP server.

• The ExNode holds location and order information for each piece.

• The ExNode provides the information needed to retrieve and reconstitute the Data File.

DATA FLOW

Model/Func

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HTML User Interface

• Single access point for all models on all servers.• User Login control.• Allows parameter designation.• Integrates with Database for access to previous

performed runs and inclusion of new runs.• Provides email notification for set and forget

model runs.

Interface Entrance Login

HTML Model List

Alligator Model Page

Take-Home Messages• Resource management at regional extent requires spatially-explicit assessments which allow

different stakeholders to evaluate alternative scenarios based upon criteria of their choice• Multimodeling, linking models at differing spatial extents, resolutions and levels of detail,

provides flexibility in dealing with the variety of physical and ecological models and data available

• Grid-based computational technology gets models to users, allowing stakeholders to modify particular model assumptions; carry out simulations focused on species/functional groups of particular interest to them; and assess the impacts of altered hydrologic plans altered based upon their own assumptions

Funding support for ATLSS and the Grid-computing effort comes from:

The US Geological Survey through a cooperative agreement with the Cooperative Ecosystems Studies Unit at the University of Tennessee.

The National Science Foundation through ITR award DEB-0219269 to The Institute for Environmental Modeling of the University of Tennessee and award EIA-9972889 to the Computer Science Department.

www.tiem.utk.edu/gem/