Integrated Population Models Theory and Ecological Applications with R and JAGS

Integrated Population Models: Theory and Ecological Applications with R and JAGS
Integrated Population Models: Theory and Ecological Applications with R and JAGS
Copyright
Contents
Foreword
Preface
WHO SHOULD READ THIS BOOK?
CONVENTIONS IN THIS BOOK
COMPUTING
THE IPMBOOK PACKAGE
BOOK WEB PAGE
Acknowledgments
SPECIAL THANKS BY MICHAEL
SPECIAL THANKS BY MARC
LITERATURE CITED
1 - INTRODUCTION
1.1 POPULATION MODELING IN POPULATION ECOLOGY AND MANAGEMENT
1.2 THE TWO-STEP APPROACH TO POPULATION MODELING
1.3 INTEGRATED POPULATION MODELS
1.4 DEVELOPING INTEGRATED POPULATION MODELS WITH THE BUGS LANGUAGE
1.5 THIS BOOK
1.5.1 WHY THIS BOOK?
1.5.2 STRUCTURE AND OVERVIEW OF THIS BOOK
1.5.3 THE IMPORTANCE OF SIMULATION
1.5.4 USE OF THIS BOOK IN COURSES AND FOR TEACHING
1 - THEORY OF INTEGRATED POPULATION MODELS
2 - BAYESIAN STATISTICAL MODELING USING JAGS
2.1 INTRODUCTION
2.2 PARAMETRIC STATISTICAL MODELING
2.2.1 DESCRIPTION OF CHANCE PROCESSES IN PROBABILITY
2.2.2 PARAMETRIC STATISTICAL MODELS FOR INFERENCE ABOUT CHANCE PROCESSES
2.3 MAXIMUM LIKELIHOOD ESTIMATION IN A NUTSHELL
2.4 BAYESIAN INFERENCE
2.5 BAYESIAN COMPUTATION
2.6 BUGS SOFTWARE: WINBUGS, OPENBUGS, JAGS, AND NIMBLE
2.7 USING JAGS TO FIT SIMPLE STATISTICAL MODELS FROM R: GENERALIZED LINEAR AND GENERALIZED LINEAR MIXED MODELS
2.7.1 POISSON GENERALIZED LINEAR MODELS
2.7.2 BERNOULLI GENERALIZED LINEAR MODELS
2.7.3 BINOMIAL GENERALIZED LINEAR MODELS
2.7.4 MULTINOMIAL GENERALIZED LINEAR MODELS
2.7.5 CATEGORICAL GENERALIZED LINEAR MODELS
2.7.6 NORMAL LINEAR REGRESSION OR GAUSSIAN GENERALIZED LINEAR MODELS
2.7.7 GENERALIZED LINEAR MODELS WITH GAUSSIAN RANDOM EFFECTS
2.8 FITTING GENERAL INTEGRATED MODELS IN JAGS
2.9 WHY WE HAVE BECOME BAYESIANS…
2.10 SUMMARY AND OUTLOOK
2.11 EXERCISES
3 - INTRODUCTION TO STAGE-STRUCTURED POPULATION MODELS
3.1 INTRODUCTION
3.2 AGE- AND STAGE-STRUCTURED POPULATION MODELS
3.2.1 FROM A LIFE-CYCLE GRAPH TO POPULATION EQUATIONS
3.2.2 AGE-STRUCTURED PRE-BIRTH-PULSE MODEL
3.2.3 STAGE-STRUCTURED PRE-BIRTH-PULSE MODEL
3.2.4 AGE-STRUCTURED POST-BIRTH-PULSE MODEL
3.2.5 STAGE-STRUCTURED POST-BIRTH-PULSE MODEL
3.3 CLASSICAL ANALYSIS OF A MATRIX POPULATION MODEL
3.3.1 ANALYSIS OF A MATRIX POPULATION MODEL WITHOUT STOCHASTICITY AND PARAMETER UNCERTAINTY
3.3.2 ANALYSIS OF A MATRIX POPULATION MODEL WITH PARAMETER UNCERTAINTY
3.3.3 ANALYSIS OF A MATRIX POPULATION MODEL WITH ENVIRONMENTAL STOCHASTICITY
3.3.4 ANALYSIS OF A MATRIX POPULATION MODEL WITH DEMOGRAPHIC STOCHASTICITY
3.3.5 ANALYSIS OF A MATRIX POPULATION MODEL WITH MULTIPLE SOURCES OF STOCHASTICITY AND PARAMETER UNCERTAINTY
3.3.6 MATRIX POPULATION MODELS WITH DENSITY DEPENDENCE AND DEMOGRAPHIC STOCHASTICITY
3.4 ANALYSIS OF MATRIX POPULATION MODELS WITH MARKOV CHAIN MONTE CARLO SOFTWARE
3.4.1 ANALYSIS OF A MATRIX POPULATION MODEL WITHOUT STOCHASTICITY AND PARAMETER UNCERTAINTY
3.4.2 ANALYSIS OF A MATRIX POPULATION MODEL WITH PARAMETER UNCERTAINTY
3.4.3 ANALYSIS OF A MATRIX POPULATION MODEL WITH ENVIRONMENTAL STOCHASTICITY
3.4.4 ANALYSIS OF A MATRIX POPULATION MODEL WITH DEMOGRAPHIC STOCHASTICITY
3.4.5 ANALYSIS OF A MATRIX POPULATION MODEL WITH MULTIPLE SOURCES OF STOCHASTICITY AND PARAMETER UNCERTAINTY
3.4.6 MATRIX POPULATION MODELS WITH DENSITY DEPENDENCE AND DEMOGRAPHIC STOCHASTICITY
3.5 SUMMARY AND OUTLOOK
3.6 EXERCISES
4 - COMPONENTS OF INTEGRATED POPULATION MODELS
4.1 INTRODUCTION
4.2 OVERVIEW OF THE KEY TYPES OF DATA AND ASSOCIATED MODELS THAT GO INTO AN IPM
4.2.1 LEVELS OF INFORMATION AND DATA AGGREGATION
4.2.2 OBSERVATION OR MEASUREMENT ERRORS IN OUR DATA SETS
4.2.3 LEVELS OF AGGREGATION AND MEASUREMENT ERROR IN POPULATION SIZE SURVEY DATA
4.2.4 LEVELS OF AGGREGATION AND MEASUREMENT ERROR IN PRODUCTIVITY SURVEY DATA
4.2.5 LEVELS OF AGGREGATION AND MEASUREMENT ERROR IN SURVIVAL SURVEY DATA
4.3 MODELS FOR POPULATION SIZE SURVEYS
4.3.1 GAUSSIAN STATE-SPACE MODELS
4.3.2 EFFECTS OF “EVIL” PATTERNS IN THE MEASUREMENT ERROR OF A GAUSSIAN STATE-SPACE MODEL
4.3.3 USE OF ESTIMATES FROM ANOTHER ANALYSIS IN A GAUSSIAN STATE-SPACE MODEL OR AN IPM
4.3.4 CORRECTION OF POPULATION COUNT DATA FOR COVERAGE BIAS AND DETECTION BIAS
4.3.5 TRANSITIONING FROM GAUSSIAN TO DISCRETE-VALUED STATE-SPACE MODELS FOR POPULATION COUNTS
4.3.6 THE “DEMOGRAPHIC” STATE-SPACE MODEL OF DAIL AND MADSEN
4.4 MODELS FOR PRODUCTIVITY SURVEYS
4.4.1 POISSON MODELS FOR BROOD SIZE DATA
4.4.2 ZERO INFLATION IN BROOD SIZE DATA
4.4.3 ZERO TRUNCATION IN BROOD SIZE DATA
4.4.4 CENSORING IN BROOD SIZE DATA
4.4.5 UNDERDISPERSION
4.4.6 NEST SURVIVAL MODELS
4.5 MODELS FOR SURVIVAL SURVEYS
4.5.1 CORMACK-JOLLY-SEBER MODEL FOR CAPTURE-RECAPTURE DATA
4.5.1.1 State-Space Formulation
4.5.1.2 Multinomial Formulation
4.5.2 MULTISTATE CAPTURE-RECAPTURE MODELS
4.5.2.1 State-Space Formulation
4.5.2.2 Multinomial Formulation
4.5.3 DEAD-RECOVERY DATA
4.5.3.1 State-Space Formulation
4.5.3.2 Multinomial Formulation
4.5.4 JOINT ANALYSIS OF CAPTURE-RECAPTURE AND DEAD-RECOVERY DATA
4.5.5 MULTIEVENT MODELS
4.6 INTRODUCTION TO SPATIAL CAPTURE-RECAPTURE MODELING
4.7 SUMMARY AND OUTLOOK
4.8 EXERCISES
5 - INTRODUCTION TO INTEGRATED POPULATION MODELS
5.1 INTRODUCTION
5.2 FEEDING DEMOGRAPHIC DATA INTO THE ANALYSIS OF A MATRIX POPULATION MODEL
5.2.1 USING CAPTURE-RECAPTURE DATA IN A MATRIX POPULATION MODEL
5.2.2 COMBINING CAPTURE-RECAPTURE AND PRODUCTIVITY DATA IN A MATRIX POPULATION MODEL
5.3 OUR FIRST INTEGRATED POPULATION MODEL
5.4 THE THREE-STEP APPROACH TO INTEGRATED POPULATION MODELING
5.4.1 DEVELOPMENT OF A MODEL THAT LINKS DEMOGRAPHIC DATA WITH POPULATION SIZE
5.4.2 FORMULATION OF THE LIKELIHOOD FOR EACH AVAILABLE DATA SET SEPARATELY
5.4.3 FORMULATION OF THE JOINT LIKELIHOOD
5.4.4 WRITING THE BUGS CODE FOR THE INTEGRATED POPULATION MODEL
5.5 SIMULATION ASSESSMENT OF A SIMPLE INTEGRATED POPULATION MODEL
5.5.1 SIMULATING DATA UNDER AN INTEGRATED POPULATION MODEL
5.5.2 SIMULATION RESULTS
5.6 OUTLOOK AND SUMMARY
5.7 EXERCISES
6 - BENEFITS OF INTEGRATED POPULATION MODELING
6.1 INTRODUCTION
6.2 PARAMETER ESTIMATES WITH INCREASED PRECISION
6.2.1 EXPERIENCING A GAIN IN PRECISION IN A SIMPLE SIMULATION
6.2.2 WHERE DOES THE INFORMATION COME FROM?
6.3 ESTIMATION OF DEMOGRAPHIC PARAMETERS FOR WHICH THERE ARE NO EXPLICIT DATA
6.4 ESTIMATION OF PROCESS CORRELATION AMONG DEMOGRAPHIC PARAMETERS
6.5 ESTIMATION OF POPULATION STRUCTURE
6.6 FLEXIBILITY
6.6.1 DIVERSITY OF DATA TYPES COMBINED IN AN IPM
6.6.2 UNEQUAL TEMPORAL COVERAGE OF DATA SETS—MISSING VALUES IN CERTAIN YEARS
6.6.3 TIME POINTS OF DATA COLLECTION DO NOT MATCH
6.6.4 USING ESTIMATED INDICES INSTEAD OF COUNTS FOR POPULATION-LEVEL DATA
6.6.5 OBSERVATION MODELS FOR POPULATION-LEVEL DATA
6.6.6 INFORMATIVE PRIORS AND SEQUENTIAL ANALYSES
6.7 SUMMARY AND OUTLOOK
6.8 EXERCISES
7 - ASSESSMENT OF INTEGRATED POPULATION MODELS
7.1 INTRODUCTION
7.2 ASSUMPTIONS OF INTEGRATED POPULATION MODELS
7.2.1 ASSUMPTIONS MADE FOR COMPONENT DATA LIKELIHOODS
7.2.1.1 Principle of Posterior Predictive Checks
7.2.1.2 Application of Posterior Predictive Checks
7.2.1.3 Sensitivity of Posterior Predictive Checks to Diagnose Misspecified IPMs
7.2.1.4 Posterior Predictive Checks for IPMs With a Hidden Parameter
7.2.2 THE INDEPENDENCE ASSUMPTION
7.2.3 THE COMMON DEMOGRAPHY ASSUMPTION
7.2.4 CONCLUSIONS ABOUT INTEGRATED POPULATION MODEL ASSUMPTIONS
7.3 UNDER- AND OVERFITTING
7.4 EFFECTS OF A MISSPECIFIED OBSERVATION MODEL
7.5 OUTLOOK AND SUMMARY
7.6 EXERCISES
8 - INTEGRATED POPULATION MODELS WITH DENSITY DEPENDENCE
8.1 INTRODUCTION
8.2 DENSITY DEPENDENCE IN RED-BACKED SHRIKES
8.2.1 GENERAL POPULATION MODEL
8.2.2 MODELING DENSITY DEPENDENCE IN SURVIVAL AND PRODUCTIVITY
8.2.3 ASSESSING DENSITY DEPENDENCE AT THE POPULATION LEVEL
8.2.4 MODELING DENSITY DEPENDENCE IN IMMIGRATION
8.3 ADVANTAGES OF IPMS FOR THE STUDY OF DENSITY DEPENDENCE
8.4 SUMMARY AND OUTLOOK
8.5 EXERCISES
9 - RETROSPECTIVE POPULATION ANALYSES
9.1 INTRODUCTION
9.2 CORRELATIONS BETWEEN DEMOGRAPHIC RATES AND POPULATION GROWTH
9.3 LIFE-TABLE RESPONSE EXPERIMENTS
9.4 TRANSIENT LIFE-TABLE RESPONSE EXPERIMENTS
9.5 SUMMARY AND OUTLOOK
9.6 EXERCISES
10 - POPULATION VIABILITY ANALYSIS
10.1 INTRODUCTION
10.2 CHALLENGES FOR DEMOGRAPHIC POPULATION VIABILITY ANALYSIS
10.3 BAYESIAN POPULATION VIABILITY ANALYSIS
10.4 USE OF AN INTEGRATED POPULATION MODEL IN POPULATION VIABILITY ANALYSIS
10.5 A POPULATION VIABILITY ANALYSIS FOR SIMULATED WOODCHAT SHRIKE DATA
10.5.1 ESTIMATION OF EXTINCTION PROBABILITY AND RELATED QUANTITIES
10.5.2 COMPARISON OF DIFFERENT MANAGEMENT OPTIONS
10.6 POPULATION VIABILITY ANALYSIS OF A POPULATION WITH IMMIGRATION
10.7 SUMMARY AND OUTLOOK
10.8 EXERCISES
2 - INTEGRATED POPULATION MODELS IN PRACTICE
11 - WOODCHAT SHRIKE
11.1 INTRODUCTION
11.2 DATA SETS
11.3 POPULATION MODEL
11.4 COMPONENT DATA LIKELIHOODS
11.4.1 POPULATION COUNT DATA
11.4.2 PRODUCTIVITY DATA
11.4.3 CAPTURE-RECAPTURE DATA
11.5 THE INTEGRATED POPULATION MODEL
11.6 RESULTS
11.7 MORE PARSIMONIOUS MODELS
11.8 DISCUSSION
12 - PEREGRINE FALCON
12.1 INTRODUCTION
12.2 DATA SETS
12.3 POPULATION MODEL
12.4 COMPONENT DATA LIKELIHOODS
12.4.1 POPULATION COUNT DATA
12.4.2 PRODUCTIVITY DATA
12.4.3 DEAD-RECOVERY DATA
12.5 THE INTEGRATED POPULATION MODEL
12.6 RESULTS
12.7 DISCUSSION
Dedication
13 - HORSESHOE BAT
13.1 INTRODUCTION
13.2 DATA SETS
13.3 POPULATION MODEL
13.4 SINGLE DATA LIKELIHOODS
13.4.1 CAPTURE-RECAPTURE DATA
13.4.2 JUVENILE AND POPULATION COUNT DATA
13.5 THE INTEGRATED POPULATION MODELS
13.6 RESULTS
13.7 PRIOR SENSITIVITY ANALYSIS
13.8 DISCUSSION
14 - HOOPOE
14.1 INTRODUCTION
14.2 DATA SETS
14.3 POPULATION MODEL
14.4 COMPONENT DATA LIKELIHOODS
14.4.1 POPULATION COUNT DATA
14.4.2 CAPTURE-RECAPTURE DATA
14.4.3 PRODUCTIVITY DATA
14.5 INTEGRATED POPULATION MODEL
14.6 RESULTS
14.7 DISCUSSION
15 - BLACK GROUSE
15.1 INTRODUCTION
15.2 DATA SETS
15.3 POPULATION MODEL
15.4 COMPONENT DATA LIKELIHOODS
15.4.1 POPULATION COUNT DATA
15.4.2 RADIO TRACKING DATA
15.4.3 MODELING PRODUCTIVITY AND CHICK SEX RATIO
15.5 INTEGRATED POPULATION MODEL
15.6 RESULTS
15.7 DISCUSSION
16 - BARN SWALLOW
16.1 INTRODUCTION
16.2 DATA SETS
16.3 POPULATION MODEL
16.4 COMPONENT DATA LIKELIHOODS
16.4.1 POPULATION COUNT DATA
16.4.2 PRODUCTIVITY DATA
16.4.3 CAPTURE-RECAPTURE DATA
16.5 THE INTEGRATED POPULATION MODEL
16.6 RESULTS
16.7 DISCUSSION
17 - ELK
17.1 INTRODUCTION
17.2 ELK IN IDAHO
17.3 POPULATION MODEL
17.4 COMPONENT DATA LIKELIHOODS
17.4.1 AGE-AT-HARVEST DATA
17.4.2 HUNTER SURVEY DATA
17.4.3 RADIO TRACKING DATA
17.5 THE INTEGRATED POPULATION MODEL
17.6 RESULTS ON ELK POPULATION DYNAMICS
17.7 PRIOR SENSITIVITY ANALYSIS
17.8 SPECIFICATION OF THE SURVIVAL PROCESS WITH HAZARD RATES
17.9 DISCUSSION
18 - CORMORANT
18.1 INTRODUCTION
18.2 DATA SETS
18.3 POPULATION MODEL
18.4 COMPONENT DATA LIKELIHOODS
18.4.1 POPULATION COUNT DATA
18.4.2 MULTISTATE CAPTURE-RECAPTURE DATA
18.5 THE INTEGRATED POPULATION MODEL
18.6 RESULTS
18.7 DISCUSSION
19 - GRAY CATBIRD
19.1 INTRODUCTION
19.2 DATA SETS
19.3 POPULATION MODEL
19.4 COMPONENT DATA LIKELIHOODS
19.4.1 POPULATION COUNT DATA (BBS DATA)
19.4.2 CAPTURE-RECAPTURE DATA (MAPS DATA)
19.5 THE INTEGRATED POPULATION MODEL
19.6 RESULTS
19.7 DISCUSSION
20 - KESTREL
20.1 INTRODUCTION
20.2 DATA SETS
20.3 POPULATION MODEL
20.4 COMPONENT DATA LIKELIHOODS
20.4.1 MONITORING HÄUFIGE BRUTVÖGEL POPULATION COUNT DATA
20.4.2 ATLAS POPULATION COUNT DATA
20.4.3 DEAD-RECOVERY DATA
20.4.4 BASIS FUNCTION APPROACH TO THE MODELING OF SPATIAL AUTOCORRELATION
20.4.5 SCALING THE MODELED POPULATION SIZE TO THE NOMINAL 1KM2 AREA
20.5 THE INTEGRATED POPULATION MODEL
20.6 RESULTS
20.7 DISCUSSION
20.7.1 THE PATH TO LANDSCAPE DEMOGRAPHY
20.7.2 THE SPATIAL FIELD APPROACH FOR AN INTEGRATED POPULATION MODEL USING LARGE-SCALE MONITORING DATA
20.7.3 COMPARISON OF DIFFERENT SPATIAL INTEGRATED POPULATION MODELS
20.7.4 PROCESS-BASED SPATIAL INTEGRATED POPULATION MODELS
20.7.5 ALTERNATIVE MODELS FOR THE KESTRELS
20.7.6 COMMENTS ON USE OF THE DAIL-MADSEN MODEL AS THE CORE OF A SPATIAL IPM
20.7.7 FURTHER POSSIBLE WORK WITH THE KESTREL IPM
21 - BLACK BEAR
21.1 INTRODUCTION
21.2 DATA SETS
21.3 POPULATION MODEL
21.4 COMPONENT DATA LIKELIHOODS
21.4.1 SPATIAL CAPTURE-RECAPTURE DATA
21.4.2 OCCUPANCY DATA
21.5 THE INTEGRATED POPULATION MODEL
21.6 RESULTS
21.7 DISCUSSION
22 - CONCLUSIONS
22.1 FITTING INTEGRATED POPULATION MODELS: A STEEP MOUNTAIN … BUT ONE THAT'S REALLY WORTH THE CLIMB!
22.2 SHOULD WE ALWAYS INTEGRATE?
22.3 THE GREAT IMPORTANCE OF LONG-TERM ECOLOGICAL RESEARCH
22.4 FUTURE DIRECTIONS IN INTEGRATED POPULATION MODELING
22.4.1 INCREASED SPATIALIZATION OF INTEGRATED POPULATION MODELS
22.4.2 BETTER REPRESENTATION OF INDIVIDUAL HETEROGENEITY
22.4.3 FINER TEMPORAL SCALES
22.4.4 MULTIPLE SPECIES
22.4.5 BETTER OBSERVATION MODELS FOR POPULATION COUNT DATA
22.4.6 IMPROVING SAMPLING DESIGNS FOR INTEGRATED POPULATION MODELS
22.4.7 STATISTICAL AND COMPUTATIONAL ADVANCES
22.5 CONCLUDING REMARKS
References
Author Index
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
R
S
T
U
V
W
Y
Z
Subject Index
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
R
S
T
U
V
W
Z