An informatics revolution is underway in ecosystem science and natural resources policy and management. Many key research areas-climate change, water, earth hazards, forest/stream processes, ocean ecosystems-are limited by common informatics problems. The problems include: accurately representing biophysical processes in mathematical terms; obtaining, storing, retrieving, and analyzing multiple datasets; testing hypotheses using various models and model versions; assessing uncertainty in predictions; and scaling or extrapolating findings among systems.
These problems are at the core of Ecosystem Informatics (EI), a novel, interdisciplinary approach to education and research that provides a unifying framework for studying complex problems in natural and managed ecosystems. EI is at the intersection of:
- Computer science (bringing algorithms and representations for manipulation, modeling, and prediction based on large data sets and complex models)
- Mathematics (bringing a cohesive analytic framework)
- Ecosystem science (bringing complex systems rich in interactions, changing contexts, and challenging links into the natural resource management and policy arena). Therefore, EI is essential for sustaining long-term ecological research
At the H.J. Andrews LTER, the Ecosystem Informatics Summer Institute provides opportunities for students from ecology, computer science, and mathematics to work in interdisciplinary teams on ecosystem science topics in old-growth forest and stream ecosystems. In the summers of 2009 and 2010, 15 students will spend 10 weeks at the H.J. Andrews LTER and Oregon State University (Corvallis) working with interdisciplinary faculty teams. The program will present students with new career opportunities, a chance to acquire collaborative skills, hands-on field experience, preparation for graduate research, and exposure to contemporary natural resource management issues. The EISI program includes course credits, lodging, stipend, and travel assistance.
The Summer 2009 projects include:
Moths, meadows, and metapopulations: Students will study the ecology of moth species and their responses to climate change and habitat loss using machine learning and visualization to understand how moth distributions respond to environmental change and by developing and applying mathematical models of metapopulation dynamics.
Wood in rivers: Students will study the ecology of wood in rivers and how wood responds to natural disturbances and logging, using machine learning and visualization to understand wood distributions and dynamics, and by developing and testing mathematical models of wood and its effects on streams.
Eco-hydrology and stream networks: Students will study how water use by oldgrowth forest ecosystems responds to climate variability and logging using visualization to understand the complex interactions among climate and water, by developing mathematical models of stochastic hydrologic processes, and by scaling these up to large landscapes.
Wireless technology for forest-atmosphere interactions: Students will study fluxes of carbon and water between forests and the atmosphere using new wireless technology, apply machine learning and visualization techniques to display complex airflow patterns, and develop and apply mathematical models of airflow dynamics in steep forested terrain.
Vegetation mapping and change: Students will study vegetation dynamics in an old-growth forest landscape integrating satellite remote sensing, vegetation plot data, and models of vegetation succession. Applications must be submitted by February 16, 2009. Information and application details are at http://eco-informatics.engr.oregonstate.edu/