x
C O N T E N T S
Detection of Causes of Population Change
201
Key Factor Analysis
201
Experimental Manipulation
205
Conclusions
208
Literature Cited
209
Chapter 7: Monitoring Populations
James P. Gibbs
213
Index–Abundance Relationships
214
Types of Indices
214
Index–Abundance Functions
215
Variability of Index–Abundance Functions
217
Improving Index Surveys
220
Spatial Aspects of Measuring Changes in Indices
221
Monitoring Indices Over Time
222
Power Estimation for Monitoring Programs
223
Variability of Indices of Animal Abundance
224
Sampling Requirements for Robust Monitoring Programs
227
Setting Objectives for a Monitoring Program
228
Conclusions
229
Acknowledgments
232
Appendix 7.1
233
Literature Cited
247
Chapter 8: Modeling Predator–Prey Dynamics
Mark S. Boyce
253
Modeling Approaches for Predator–Prey Systems
254
Noninteractive Models
255
True Predator–Prey Models
260
Stochastic Models
269
Autoregressive Models
270
Fitting the Model to Data
273
Bayesian Statistics
273
Best Guess Followed by Adaptive Management
273
Choosing a Good Model
275
How Much Detail?
275
Model Validation
277
Recommendations
279
Remember the Audience
279
C O N T E N T S
Detection of Causes of Population Change
201
Key Factor Analysis
201
Experimental Manipulation
205
Conclusions
208
Literature Cited
209
Chapter 7: Monitoring Populations
James P. Gibbs
213
Index–Abundance Relationships
214
Types of Indices
214
Index–Abundance Functions
215
Variability of Index–Abundance Functions
217
Improving Index Surveys
220
Spatial Aspects of Measuring Changes in Indices
221
Monitoring Indices Over Time
222
Power Estimation for Monitoring Programs
223
Variability of Indices of Animal Abundance
224
Sampling Requirements for Robust Monitoring Programs
227
Setting Objectives for a Monitoring Program
228
Conclusions
229
Acknowledgments
232
Appendix 7.1
233
Literature Cited
247
Chapter 8: Modeling Predator–Prey Dynamics
Mark S. Boyce
253
Modeling Approaches for Predator–Prey Systems
254
Noninteractive Models
255
True Predator–Prey Models
260
Stochastic Models
269
Autoregressive Models
270
Fitting the Model to Data
273
Bayesian Statistics
273
Best Guess Followed by Adaptive Management
273
Choosing a Good Model
275
How Much Detail?
275
Model Validation
277
Recommendations
279
Remember the Audience
279
