Multi-scale Modeling of Ecological Systems: Systems Biology in Application to Natural Resource Management

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Multi-scale Modeling of Ecological Systems: Systems Biology in Application to Natural Resource Management Louis J. Gross The Institute for Environmental Modeling Departments of Ecology and Evolutionary Biology and Mathematics University of Tennessee Supported by NSF Awards DEB-0219269, DMS-0211991, IIS-0427471 ATLSS.org

System Biology: Some History Themes of this 1979 collection of papers included: Models: defining appropriate equations and linking these to data for parameterization Hypothesis formulation: viewed as generated from complex models rather than from observations Scales: combining processes operating on different spatial and temporal scales Validation: determining appropriate methods to evaluate models to assert when they may be applicable Computation: while only early computers were available, simulation methods were paramount

We are still grappling with many of these same issues Models: we have moved well beyond the simple differential equations used in the early systems ecology, and now have a plethora of model structures to choose from (cellular automata, individual-based models, network methods, discrete dynamical systems, partial differential equations), but model detail is still constrained by data Hypothesis formulation: these are now arising from viewing systems in an evolutionary perspective with broader considerations of processes from the genome to the community

We are still grappling with many of these same issues Scales: development of genetic methods has fostered a much wider set of possible system connections, and there are many alternative approaches for spatial heterogeneity but multimodeling to combine processes operating on different spatial and temporal scales is still limited Validation: developing a general methodology to say when a model is good has not been successful - complexity arising from stochastic and chaotic components limits our ability to completely analyze potential model behaviors Computation: we can now simulate systems with many thousands of interacting processes in space and time, but obtaining insight from these complex models is still difficult (leading to data mining methods for models)

System Biology: a recent view 1. Are there still new life forms to be discovered? 2. What role does life play in the metabolism of planet Earth? 3. How do cells really work? 4. What are the engineering principles of life? 5. What is the information that defines and sustains life? 6. What determines how organisms behave in their worlds? 7. How much can we tell about the past and predict about the future by studying life on earth today? The Role of Theory in Advancing 21st-Century Biology: Catalyzing Transformative Research (NRC, 2008) www.nap.edu

Moving Forward in Systems Biology: One approach is to start with particular challenges in biology and use these to motivate new mathematical models and develop appropriate new techniques as necessary. One very general challenge is: How representative are observations and methods we develop for one biological system for applicable to other systems, at different locations, in different organisms, or at different levels of organization in the hierarchy of biology? OK OK Not OK

Overview Background on natural resource management Everglades restoration and ATLSS (Across Trophic Level System Simulation) Invasive species management Optimal control for generic focus/satellite spread Spatially-explicit management of Old World Climbing Fern Wildlife management -the black bear case Optimal control in a simple metapopulation case Individual-based models and preserve placement Some lessons from our experience

Problems in Natural Resource Management Harvest management Wildlife management including hunting regulations and preserve design Water regulation Invasive species management Disease control Wildfire management Biodiversity and conservation planning Supported by NSF Awards DMS-0110920, DEB-0219269 and IIS-0427471

IEEE Computing in Science and Engineering (2007) 9:40-48

What is challenging about natural resource management? Involves complex interactions between between humans and natural systems Often includes multiple scales of space and time Multiple stakeholders with differing objectives Monetary consequences can be considerable

How can mathematics and modeling assist in solving problems in resource management? Provide tools to project dynamic response of systems to alternative management Estimate the best way to manage systems - optimal control Provide means to account for spatial changes in systems and link models with geographic information systems (GIS) and decision support tools that natural system managers and policy makers need. Consider methods to account for multiple criteria and differing opinions of the variety of stakeholders

QuickTime and a TIFF (Uncompressed) decompressor are needed to see this picture. QuickTime and a TIFF (Uncompressed) decompressor are needed to see this picture.

QuickTime and a TIFF (Uncompressed) decompressor are needed to see this picture. Ding, W., L. J. Gross, K. Langston, S. Lenhart and L. A. Real. 2007. Rabies in raccoons: optimal control for a discrete time model on a spatial grid. Journal of Biological Dynamics 1:379-393. QuickTime and a TIFF (Uncompressed) decompressor are needed to see this picture. Asano, E., L. J.Gross, L. Lenhart and L. A. Real. 2008. Optimal control of vaccine distribution in a rabies metapopulation model. Mathematical Biosciences and Engineering (to appear)

Fox rabies in Czech Republic About 28 million vaccine baits were distributed in the Czech Republic from 1989-2006. There were 5 children treated for bat rabies in 2005.

Wildfire Control

Wet Season: May-October Dry Season: November-April Photos: South Florida Water Management District

Collaborators on ATLSS

Everglades natural system management requires decisions on short time periods about what water flows to allow where and over longer planning horizons how to modify the control structures to allow for appropriate controls to be applied. This is very difficult! The control objectives are unclear and differ with different stakeholders. Natural system components are poorly understood. The scales of operation of the physical system models are coarse.

So what have we done? Developed a multimodel (ATLSS - Across Trophic Level System Simulation) to link the physical and biotic components. Compare the dynamic impacts of alternative hydrologic plans on various biotic components spatially. Let different stakeholders make their own assessments of the appropriate ranking of alternatives. http://atlss.org

Individual-Based Models Cape Sable Seaside Sparrow Snail Kite Wading Birds White-tailed Deer Florida Panther Radio-telemetry Tracking Tools Age/Size Structured Models Fish Functional Groups Alligators Reptiles and Amphibians Linked Cell Models Process Models Lower Trophic Level Components Vegetation Spatially-Explicit Species Index Models Cape Sable Seaside Sparrow Snail Kite Long-legged Wading Birds Short-legged Wading Birds White-tailed Deer Alligators Abiotic Conditions Models High Resolution Topography High Resolution Hydrology Disturbance TIEM / University of Tennessee 1999

List and links to all papers I discussed are at: http://www.tiem.utk.edu/itr06/