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Preface | ||
Mathematical Symbols | ||
Pt. I | Theory | |
1 | Introduction | 3 |
1.1 | At the Sources | 3 |
1.2 | General Philosophy of the Approach | 6 |
2 | Population Dynamics from First Principles | 17 |
2.1 | Introduction | 17 |
2.2 | Exponential Growth | 19 |
2.3 | Self-Limitation | 26 |
2.4 | Consumer-Resource Oscillations | 30 |
2.5 | Process Order | 36 |
2.6 | Synthesis | 44 |
3 | Single-Species Populations | 47 |
3.1 | Models without Population Structure | 47 |
3.2 | Exogenous Drivers | 58 |
3.3 | Age- and Stage-Structured Models | 64 |
3.4 | Second-Order Models | 70 |
3.5 | Synthesis | 76 |
4 | Trophic Interactions | 78 |
4.1 | Responses to Predators to Fluctuations in Prey Density | 79 |
4.2 | Continuous-Time Models | 93 |
4.3 | Discrete-Time Models: Parasitoids | 108 |
4.4 | Grazing Systems | 112 |
4.5 | Pathogens and Parasites | 127 |
4.6 | Tritrophic Models | 133 |
4.7 | Synthesis | 136 |
5 | Connecting Mathematical Theory to Empirical Dynamics | 137 |
5.1 | Introduction | 137 |
5.2 | Qualitative Types of Deterministic Dynamics | 139 |
5.3 | Population Dynamics in the Presence of Noise | 146 |
5.4 | Population Regulation | 154 |
Pt. II | Data | |
6 | Empirical Approaches: An Overview | 163 |
6.1 | Introduction | 163 |
6.2 | Analysis of Population Fluctuations | 164 |
6.3 | Experimental Approaches | 168 |
7 | Phenomenological Time-Series Analysis | 173 |
7.1 | Basics | 173 |
7.2 | Fitting Models to Data | 183 |
7.3 | Synthesis | 195 |
8 | Fitting Mechanistic Models | 197 |
8.1 | Model Selection | 198 |
8.2 | Analysis of Ancillary Data | 200 |
8.3 | One-Step-Ahead Prediction | 201 |
8.4 | Trajectory Matching | 203 |
8.5 | Fitting by Nonlinear Forecasting | 205 |
Pt. III | Case Studies | |
9 | Larch Budmoth | 213 |
9.1 | Introduction | 213 |
9.2 | Analysis of Time-Series Data | 217 |
9.3 | Hypotheses and Models | 220 |
9.4 | Synthesis | 237 |
10 | Southern Pine Beetle | 239 |
10.1 | Introduction | 239 |
10.2 | Analysis of Time-Series Data | 240 |
10.3 | Hypotheses and Models | 243 |
10.4 | An Experimental Test of the Predation Hypothesis | 259 |
10.5 | Synthesis | 271 |
11 | Red Grouse | 272 |
11.1 | Numerical Patterns | 273 |
11.2 | Hypotheses and Models | 281 |
11.3 | Experiments | 289 |
11.4 | Synthesis | 294 |
12 | Voles and Other Rodents | 296 |
12.1 | Introduction | 296 |
12.2 | Analysis of Time-Series Data | 297 |
12.3 | Hypotheses and Models | 310 |
12.4 | Fitting the Predation Model by NLF | 321 |
12.5 | Lemmings | 325 |
12.6 | Synthesis | 335 |
13 | Snowshoe Hare | 344 |
13.1 | Introduction | 344 |
13.2 | Numerical Patterns | 345 |
13.3 | Models | 349 |
13.4 | Experiments | 356 |
13.5 | Synthesis | 362 |
14 | Ungulates | 365 |
14.1 | Introduction | 365 |
14.2 | Interaction with Food | 368 |
14.3 | Interaction with Predators | 371 |
14.4 | Numerical Dynamics | 376 |
14.5 | Synthesis | 381 |
15 | General Conclusions | 383 |
15.1 | What Mechanisms Drive Oscillations in Nature? | 383 |
15.2 | Structure of Density Dependence | 386 |
15.3 | What about Chaos? | 390 |
15.4 | Population Ecology: A Mature Science | 392 |
Glossary | 397 | |
References | 405 | |
Index | 437 |
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Add Complex Population Dynamics: A Theoretical/Empirical Synthesis (MPB-35), Why do organisms become extremely abundant one year and then seem to disappear a few years later? Why do population outbreaks in particular species happen more or less regularly in certain locations, but only irregularly (or never at all) in other locatio, Complex Population Dynamics: A Theoretical/Empirical Synthesis (MPB-35) to your collection on WonderClub |