Occupancy Estimation and Modeling,9780120887668

Occupancy Estimation and Modeling

by ; ; ; ; ;
ISBN13: 9780120887668
ISBN10: 0120887665
Format: Hardcover
Pub. Date: 2005-11-17
Publisher(s): Elsevier Science
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Summary

Occupancy Estimation and Modeling is the first book to examine the latest methods in analyzing presence/absence data surveys. Using four classes of models (single-species, single-season; single-species, multiple season; multiple-species, single-season; and multiple-species, multiple-season), the authors discuss the practical sampling situation, present a likelihood-based model enabling direct estimation of the occupancy-related parameters while allowing for imperfect detectability, and make recommendations for designing studies using these models. * Provides authoritative insights into the latest in estimation modeling * Discusses multiple models which lay the groundwork for future study designs * Addresses critical issues of imperfect detectibility and its effects on estimation * Explores the role of probability in estimating in detail

Table of Contents

Preface xiii
1. Introduction 1(24)
1.1. Operational Definitions
2(1)
1.2. Sampling Animal Populations and Communities General Principles
3(9)
Why?
4(1)
What?
5(2)
How?
7(5)
1.3. Inference about Dynamics and Causation
12(8)
Generation of System Dynamics
12(5)
Statics and Process vs. Pattern
17(3)
1.4. Discussion
20(5)
2. Occupancy in Ecological Investigations 25(28)
2.1. Geographic Range
27(6)
2.2. Habitat Relationships and Resource Selection
33(2)
2.3. Metapopulation Dynamics
35(6)
Inference Based on Single-season Data
36(4)
Inference Based on Multiple-season Data
40(1)
2.4. Large-scale Monitoring
41(3)
2.5. Multispecies Occupancy Data
44(5)
Inference Based on Static Occupancy Patterns
44(3)
Inference Based on Occupancy Dynamics
47(2)
2.6. Discussion
49(4)
3. Fundamental Principles of Statistical Inference 53(30)
3.1. Definitions and Key Concepts
55(9)
Random Variables, Probability Distributions, and the Likelihood Function
55(3)
Expected Values
58(2)
Introduction to Methods of Estimation
60(1)
Properties of Point Estimators
61(1)
Bias
62(1)
Precision (Variance and Standard Error)
62(1)
Accuracy (Mean Squared Error)
63(1)
Computer-Intensive Methods
63(1)
3.2. Maximum Likelihood Estimation Methods
64(3)
Maximum Likelihood Estimators
64(1)
Properties of Maximum Likelihood Estimators
65(1)
Variance, Covariance (and Standard Error) Estimation
66(1)
Confidence Interval Estimators
66(1)
3.3. Bayesian Methods of Estimation
67(4)
Theory
68(3)
Computing Methods
71(1)
3.4. Modeling Auxiliary Variables
71(4)
The Logit Link Function
71(2)
Estimation
73(2)
3.5. Hypothesis Testing
75(2)
Background and Definitions
75(1)
Likelihood Ratio Tests
76(1)
Goodness of Fit Tests
77(1)
3.6. Model Selection
77(5)
The Akiake Information Criteria (AIC)
78(2)
Goodness of Fit and Overdispersion
80(1)
Quasi-AIC
80(1)
Model Averaging and Model Selection Uncertainty
81(1)
3.7. Discussion
82(1)
4. Single-species, Single-season Occupancy Models 83(50)
4.1. The Sampling Situation
84(1)
4.2. Estimation of Occupancy If Probability of Detection Is 1 or Known Without Error
85(2)
4.3. Two-step Ad Hoc Approaches
87(5)
Geissler-Fuller Method
87(2)
Azuma-Baldwin-Noon Method
89(1)
Nichols-Karanth Method
90(2)
4.4. Model-based Approach
92(30)
Building a Model
92(2)
Estimation
94(1)
Constant Detection Probability Model
95(2)
Survey-specific Detection Probability Model
97(1)
Probability of Occupancy Given Species Not Detected at a Site
97(2)
Example: Blue-ridge Salamanders
99(2)
Missing Observations
101(2)
Covariate Modeling
103(1)
Violations of Model Assumptions
104(4)
Assessing Model Fit
108(5)
Examples
113(1)
Pronghorn Antelope
113(3)
Mahoenui Giant Weta
116(6)
4.5. Estimating Occupancy for a Finite Population or Small Area
122(9)
Prediction of Unobserved Occupancy State
123(2)
A Bayesian Formulation of the Model
125(4)
Blue-ridge Two-lined Salamanders Revisted
129(2)
4.6. Discussion
131(2)
5. Single-species, Single-season Models with Heterogeneous Detection Probabilities 133(22)
5.1. Site Occupancy Models with Heterogeneous Detection
135(7)
General Formulation
135(2)
Finite Mixtures
137(2)
Continuous Mixtures
139(1)
Abundance Models
140(1)
Model Fit
141(1)
5.2. Example: Breeding Bird Point Count Data
142(2)
5.3. Generalizations: Covariate Effects
144(2)
5.4. Example: Anuran Calling Survey Data
146(2)
5.5. On the Indentifiability of ψ
148(3)
5.6. Discussion
151(4)
6. Design of Single-season Occupancy Studies 155(28)
6.1. Defining a "Site"
157(1)
6.2. Site Selection
158(2)
6.3. Defining a "Season"
160(1)
6.4. Conducting Repeat Surveys
161(4)
6.5. Allocation of Effort: Number of Sites vs. Number of Surveys
165(14)
Standard Design
167(1)
No Consideration of Cost
167(3)
Including Survey Cost
170(3)
Double Sampling Design
173(2)
Removal Sampling Design
175(4)
More Sites vs. More Repeat Surveys
179(1)
6.6. Discussion
179(4)
7. Single-species, Multiple-season Occupancy Models 183(42)
7.1. Basic Sampling Scheme
184(2)
7.2. An Implicit Dynamics Model
186(1)
7.3. Modeling Dynamic Changes Explicitly
187(16)
Modeling Dynamic Processes When Detection Probability Is 1
189(3)
Conditional Modeling of Dynamic Processes
192(1)
Unconditional Modeling of Dynamic Processes
192(3)
Missing Observations
195(2)
Including Covariate Information
197(1)
Alternative Parameterizations
198(3)
Example: House Finch Expansion in North America
201(2)
7.4. Investigating Occupancy Dynamics
203(9)
Markovian, Random, and No Changes in Occupancy
205(3)
Equilibrium
208(1)
Example: Northern Spotted Owl
209(3)
7.5. Violations of Model Assumptions
212(2)
7.6. Modeling Heterogeneous Detection Probabilities
214(1)
7.7. Study Design
215(7)
Time Interval Between Seasons
216(2)
Same vs. Different Sites Each Season
218(1)
More Sites vs. More Seasons
219(2)
More on Site Selection
221(1)
7.8. Discussion
222(3)
8. Occupancy Data for Multiple Species: Species Interactions 225(24)
8.1. Detection Probability and Inference about Species Co-occurrence
226(5)
8.2. A Single-season Model
231(8)
General Sampling Situation
231(1)
Statistical Model
232(2)
Reparameterizing the Model
234(3)
Incorporating Covariate Information
237(1)
Missing Observations
238(1)
8.3. Addressing Biological Hypotheses
239(1)
8.4. Example: Terrestrial Salamanders in Great Smoky Mountain National Park
240(2)
8.5. Study Design Issues
242(2)
8.6. Extension to Multiple Seasons
244(3)
8.7. Discussion
247(2)
9. Occupancy in Community-level Studies 249(18)
9.1. Investigating the Community at a Single Site
250(4)
Fraction of Species Present in a Single Season
252(1)
Changes in the Fraction of Species Present over Time
253(1)
9.2. Investigating the Community at Multiple Sites
254(10)
Single-season Studies: Modeling Occupancy and Detection
255(1)
Single-season Studies: Species Richness Estimation
256(4)
Example: Avian Point Count Data
260(2)
Multiple-season Studies
262(2)
9.3. Discussion
264(3)
10. Future Directions 267(18)
10.1. Multiple Occupancy States
268(5)
10.2. Integrated Modeling of Habitat and Occupancy
273(6)
10.3. Incorporating Information on Marked Animals
279(1)
10.4. Incorporating Count and Other Data
280(1)
10.5. Relationship Between Occupancy and Abundance
281(1)
10.6. Discussion
282(3)
Appendix: Some Important Mathematical Concepts 285(8)
References 293(20)
Index 313

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