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Life Sciences - Ecology | Predictive Species and Habitat Modeling in Landscape Ecology - Concepts and Applications

Predictive Species and Habitat Modeling in Landscape Ecology

Concepts and Applications

Drew, C. Ashton, Wiersma, Yolanda F., Huettmann, Falk (Eds.)

2011, XIV, 313 p.

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  • Shows how fundamental ecological theories are being explicitly integrated into model building processes
  • Offers practical examples of the ways modelers address the complexity of ecological systems
  • Presents novel methods to identify and quantify sources of uncertainty and variability in species habitat associations in time and space
Much research in landscape ecology makes use of spatial models to define species-habitat associations. The early years of landscape ecology necessarily focused on the evolution of effective data sources, metrics, and statistical approaches that could truly capture the spatial and temporal patterns and processes of interest. Now that these tools are well established, we reflect in this volume on the ecological theories that underpin the assumptions commonly made during species distribution modeling and mapping. This is crucial for applying models to questions of global sustainability. This book will offer a unique perspective on modeling within the discipline of landscape ecology, which complements that of other recent publications. Through chapters that focus on particular aspects of modeling, illustrative case studies, and surveys of the field of modeling, this book illustrates that we can (and need to) pay attention to the foundational ecological theories and assumptions which support model development. We show how this can be done in modeling through theory, traditional inference, and predictions. Chapter authors have attempted to critically identify, evaluate, and even formally test these ecological theories and have also written thoughtful reflections on the state of landscape-scale species/habitat modeling. Predictive Species and Habitat Modeling in Landscape Ecology: Concepts and Applications is intended to be useful to researchers in landscape ecology, as well as those in conservation biology, wildlife management, population and community ecology, and general ecology. The book will be a valuable resource for graduate students incorporating landscape ecology and/or species modeling in their degree programs. About the Editors C. Ashton Drew is a postdoctoral researcher in the USGS North Carolina Cooperative Fish and Wildlife Research Unit, North Carolina State University. Her research interests focus on how models can support adaptive monitoring and management. Yolanda F. Wiersma is Assistant Professor in Biology at Memorial University (Canada). She conducts research in Boreal Landscape Ecology, with a focus on models of wildlife-habitat interactions, forestry and protected areas. Falk Huettmann is Associate Professor in the Biology and Wildlife Department, Institute of Arctic Biology, University of Alaska-Fairbanks. His research interests are in wildlife/habitat modeling, GIS and remote sensing, and data management worldwide.

Content Level » Professional/practitioner

Keywords » GIS - Landscape Ecology - adaptive management - ecological theory - mapping - modeling - prediction methods

Related subjects » Animal Sciences - Ecology - Nature Conservation & Biodiversity

Table of contents 

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*)

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