Foreword (Jianguo Liu*)
Introduction (Ashton Drew*, Falk Huettmann*, Yolanda Wiersma*)
Current State of Knowledge
1. Statistical, ecological and data models (Nicolette Cagle, Mike Austin)
2. The state of spatio-temporal statistical modeling in ecology (Mevin Hooten*)
Integration of Ecological Theory into Modeling Practice
3. Linking ecological theory with species-habitat modeling (Alexandre Hirzel*)
4. The role of assumption in predictions of habitat availability and quality (Ed Laurent*)
5. Habitat quality and ecological theory: the importance of variation in space and time
(Robert Fletcher*)
6. Data management as the scientific foundation for modeling (Falk Huettmann* and
Benjamin Zuckerberg*)
Simplicity, Complexity, and Uncertainty in Applied Models
7. Variation, use, and mis-use of statistical models: effects on the interpretation of research
results (Yolanda Wiersma*)
8. Modeling landcover pattern and change using Random Forest (Jeffrey Evans)
9. Focused assessment of scale-dependent vegetation pattern (Todd Lookingbill)
10. Understanding year-to-year inconsistency in bird-landscape relations: the influence of
life-history traits and model selection uncertainty (Sam Riffel)
11. Boreal toad (Bufo boreas boreas) population connectivity in Yellowstone National Park:
quantifying matrix resistance and model uncertainty using landscape genetics (Melanie
Murphy*)
12. Assessment of how fine-scale expert opinion improves large-scale regional species
distribution models (Ashton Drew*)
Designing Models for Increased Utility
13. Integrating and improving GAP wildlife habitat models with IFMAP, Michigan's forest
management decision support environment (Jay Roberts*)
14. Linking modeling to adaptive management (Tom Nudds)
15. Linking spatially explicit predictions with models in strategic conservation planning,
forecasting and cumulative impact assessments (Joshua Lawler*, Falk Huettmann*,
Yolanda Wiersma*)
Conclusion and Outlook (Ashton Drew*, Falk Huettmann*, Yolanda Wiersma*)