Population dynamics for conservation:
Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Oxford
Oxford University Press
2019
|
| Ausgabe: | First Edition |
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=031066872&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | xiii, 338 Seiten Diagramme |
| ISBN: | 9780198758372 9780198758365 |
Internformat
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Datensatz im Suchindex
| _version_ | 1819291055467528192 |
|---|---|
| adam_text | Population Dynamics
for Conservation
LOUIS W BOTSFORD, J WILSON WHITE,
AND ALAN HASTINGS
OXFORD
UNIVERSITY PRESS
Contents
1 Philosophical approach to population modeling 1
1 1 Simplicity versus complexity, and four characteristics of models 2
1 2 Logical basis for population modeling 6
121 Deductive reasoning and the scientific uses of modeling 6
122 Inductive reasoning and practical applications of modeling 9
123 Consequences of deductive and inductive logic for population dynamics 10
1 3 The state of a system 11
131 Models of z-states and p-states 12
132 Individual based models (IBM) 14
1 4 Uncertainty and population models 15
1 5 Levels of integration in ecology 17
1 6 State of the field 18
2 Simple population models 21
2 1 The first population model—the rabbit problem 22
2 2 Simple linear models (exponential or geometric growth) 26
2 3 Simple nonlinear models (logistic-type models) 30
231 Continuous-time logistic models 30
232 Discrete-time logistic models 34
2 4 Illustrating population concepts with simple models 37
241 Illustrating dynamic stability with simple, linear, discrete-time models 37
242 Dynamic stability of simple nonlinear models 42
243 Quasi-extinction in random environments with a discrete-time linear
simple model 45
244 What does the simple logistic model tell us about managing for sustainable
fisheries? 51
2 5 What have we learned in Chapter 2? 52
3 Linear, age-structured models and their long-term dynamics 54
3 1 The continuity equation and the M Kendrick/von Foerster model 55
311 Solving the M Kendrick/von Foerster model 61
3 2 The renewal equation—Lotka s model 64
3 3 The Leslie matrix 66
331 Solving the Leslie model ’ 69
332 The stable age distribution 71
3 4 Mathematical theory underlying the Leslie matrix 73
341 The Perron-Frobenius theorem 77
3 5 Sensitivity and elasticity of eigenvalues: the Totoaba example 77
x CONTENTS
3 6 Handling the oldest age classes: age-lumping, terminal age classes, and
post-reproductive ages 82
3 7 What have we learned in Chapter 3? 84
4 Age-structured models: Short-term transient dynamics 87
4 1 The other eigenvalues 88
411 An example of cyclic transient dynamics 90
4 2 How the dependence of reproduction on age influences these cycles 93
421 Semelparous species and imprimitive Leslie matrices 93
422 Cycle period: the mean age of reproduction and the echo effect 96
423 How age structure influences the occurrence of cycles 98
424 Convergence to the asymptotic dynamics 100
4241 Rate of convergence to the stable age distribution: the damping ratio 100
4242 The distance to the stable age distribution 101
4243 Example: adaptive management of marine protected areas 104
4 3 Transient responses to ongoing environmental variability 105
431 Determining the equilibrium of a nonlinear age-structured population 106
432 The frequency response of a population 108
433 Cohort resonance 112
4331 Analysis of cohort resonance 113
4332 Cohort resonance: effects of life history, fishing, and eigenvalues 116
434 Extreme period-T cycles: cyclic dominance in sockeye salmon 118
4 4 What have we learned in Chapter 4? 120
5 Size-structured models 122
5 1 The size-structured M Kendrick/von Foerster model 124
511 The solution to the size-structured M Kendrick/von Foerster model 126
512 Adding reproduction to obtain a complete population model 127
5 2 Stand distributions 128
5 3 Cohort distributions 134
5 4 Numerical methods 138
541 Grid-based method 138
542 The escalator-boxcar train 138
543 Integral projection models 139
5 5 What have we learned in Chapter 5? 143
6 Stage-structured models 145
6 1 Biological processes 145
6 2 History of development of stage-structured matrix models 147
621 Early development of stage models 147
622 Early successes in stage-structured modeling 149
623 Early applications 152
624 Stochastic stage-structured models 154
6 3 Problems with stage-structured models 155
6 4 Possible better alternatives to stage-structured models 159
CONTENTS xi
6 5 Replacement in stage-structured models 160
6 6 Delay equations 163
6 7 What have we learned in Chapter 6? 165
7 Age-structured models with density-dependent recruitment 166
7 1 Local stability and 2T cycles 167
711 Local stability analysis 167
712 An example: 2T cycles in Dungeness crab 172
7 2 The simplest general model of age-structured density dependence 177
7 3 Cycles in Dungeness crab: models and data 180
7 4 An intertidal barnacle, Balanus glandula 183
7 5 Cannibalism and the flour beetle, Tribolium 187
7 6 Effects of equilibrium conditions 189
761 Single-sex harvest 189
762 Multiple equilibria 190
7 7 What have we learned in Chapter 7? 191
8 Age-structured models in a random environment 194
8 1 The small fluctuation approximation (SFA) 196
8 2 The first crossing solution 197
83A more general version of the growth of variability 199
8 4 Does the SFA/diffusion approximation work? Totoaba as an example 201
8 5 Color of the random environmental variability 203
8 6 Application of SFA to population data 205
8 7 State of the science quantifying extinction risk at the turn of the century 207
8 8 Perils of using stage models to characterize extinction risk 210
8 9 What have we learned in Chapter 8? 212
9 Spatial population dynamics 214
9 1 Modeling the spread of a population 216
911 The reaction-diffusion model 217
912 The asymptotic rate of spread 219
913 Leptokurtic dispersal 223
914 When diffusion is not a good representation of movement 224
9 2 Population persistence in aquatic habitats 225
921 The KISS model: persistence of a patch of plankton 225
922 The drift paradox 226
9 3 Metapopulations 230
931 The Levins model 230
932 Incidence function models 231
933 Patch value in the incidence function model 232
9 4 Models with internal patch dynamics: structure in space and age 235
941 Metapopulation persistence: replacement over space 236
xii CONTENTS
942 Population persistence in heterogeneous space 238
9 5 Spatial variability across populations 242
9 6 What have we learned in Chapter 9? 244
10 Applications to conservation biology 247
10 1 Lessons from earlier chapters 248
10 2 Probabilities of extinction: the problem of measurement uncertainty 250
10 3 Probabilities of extinction: the importance of environmental spectra 252
10 4 Replacement as an extinction metric 253
10 5 An example with abundance, replacement, and measurement error 254
10 6 Comparative studies: Pacific salmon 255
10 7 Addressing exogenous variability: drivers and errors 259
10 8 Population diversity 261
10 9 What have we learned in Chapter 10? 264
11 Population dynamics in marine conservation 266
11 1 Three models from the 1950s 267
11 1 1 The logistic fishery model 267
11 1 2 The single cohort model (also known as the dynamic pool model,
yield-per-recruit model) 270
11 1 3 The stock and recruitment model 275
11 1 4 Complete age-structured models: linking cohorts with a
stock-recruit curve 276
11 2 Replacement in fully age-structured fishery models 276
11 2 1 Stock-recruit curves, lifetime egg production (LEP), and spawning per
recruit (SPR) 277
11 2 2 Replacement and optimal fishery yield 280
11 3 The precautionary approach and modern fishery management 281
11 3 1 Precautionary management and reference points 281
11 3 2 Managing to avoid overfishing 282
11 4 Spatial management: marine protected areas 286
11 4 1 Strategic models of MPAs 286
11 4 2 Tactical models of marine protected area design 292
11 4 3 Other types of models used in MPA design 296
11 4 4 Adaptive management of MPAs 297
11 5 What have we learned in Chapter 11? 301
12 Thinking about populations 303
12 1 Modeling philosophy and approach 304
12 2 Replacement, an organizing principle 305
12 3 Population responses to time scales of environmental variability 307
CONTENTS xiii
12 4 Applying the lessons of population dynamics 308
12 5 What next? 309
Glossary 311
References 315
Index 337
|
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| id | DE-604.BV045683331 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T18:33:22Z |
| institution | BVB |
| isbn | 9780198758372 9780198758365 |
| language | English |
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| owner_facet | DE-20 DE-11 |
| physical | xiii, 338 Seiten Diagramme |
| publishDate | 2019 |
| publishDateSearch | 2019 |
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| publisher | Oxford University Press |
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| spellingShingle | Botsford, Louis W. White, J. Wilson Hastings, Alan 1953- Population dynamics for conservation Demökologie (DE-588)4149059-9 gnd Artenschutz (DE-588)4112598-8 gnd |
| subject_GND | (DE-588)4149059-9 (DE-588)4112598-8 |
| title | Population dynamics for conservation |
| title_auth | Population dynamics for conservation |
| title_exact_search | Population dynamics for conservation |
| title_full | Population dynamics for conservation Louis W. Botsford, J. Wilson White, and Alan Hastings |
| title_fullStr | Population dynamics for conservation Louis W. Botsford, J. Wilson White, and Alan Hastings |
| title_full_unstemmed | Population dynamics for conservation Louis W. Botsford, J. Wilson White, and Alan Hastings |
| title_short | Population dynamics for conservation |
| title_sort | population dynamics for conservation |
| topic | Demökologie (DE-588)4149059-9 gnd Artenschutz (DE-588)4112598-8 gnd |
| topic_facet | Demökologie Artenschutz |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=031066872&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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