Forecasting the consequences of land management on ecological systems requires 1) an understanding of the current state of that system and 2) understanding how that system works.  Today GIS is routinely used by professionals to formalize understandings of the former (system state).

However, understandings of system dynamics typically reside only in the minds of ecosystem managers. The power and utility of computer based modeling is rarely employed by ecologists. We humans are very good at remembering facts, understanding cause-effects, and recognizing patterns. We can use help in the understanding of the implications of our understandings, beliefs, and hypotheses - especially where cause-effect chains form feedback loops and where the this occurs across space and time.

The authors have been empowering students of ecology to capture their understandings of spatial and system dynamics within software so that they might have computational help in understanding the consequences of their understandings of ecological systems. We have taught students to use the Stella modeling software in conjunction with GIS data through the Spatial Modeling Environment (SME). Recently we have adopted the Netlogo platform for the classroom experience.

Results/Conclusions

Working quarter-time for four months, graduate students in classes during the 2008 and 2009 spring semesters at the Univ of Ill at Urbana-Champaign have successfully learned and applied the software to a variety of ecological applications. Five ecological models have emerged through classroom group efforts: Feral Hogs, Red Imported Fire Ants, Striped Newt, Invasive Cedar, and Mississippi Nutrient Cycling. (Other class models included farmer crop selection in India and food security in South America.) Some of these models have been submitted for publication in the peer-reviewed literature.  We believe that these students will, in their careers, use computers to formalize understandings of system state (via GIS) and understandings of system behavior and will be better equipped to make better decisions and to better communicate those decisions to stakeholders.