Occupancy Estimation and Modeling : Inferring Patterns and Dynamics of Species Occurrence.

By: MacKenzie, Darryl IContributor(s): Bailey, Larissa L | Hines, James E | Nichols, James D | Pollock, Kenneth H | Royle, J. AndrewPublisher: San Diego : Elsevier Science & Technology, 2005Copyright date: ©2006Description: 1 online resource (343 pages)Content type: text Media type: computer Carrier type: online resourceISBN: 9780080455044Subject(s): Animal populations - Mathematical modelsGenre/Form: Electronic books. Additional physical formats: Print version:: Occupancy Estimation and Modeling : Inferring Patterns and Dynamics of Species OccurrenceDDC classification: 591.7/88 LOC classification: QL752.O23 2006Online resources: Click to View
Contents:
Front cover -- Title page -- Copyright page -- Table of Contents -- Preface -- Acknowledgments -- CHAPTER 1: Introduction -- 1.1. OPERATIONAL DEFINITIONS -- 1.2. SAMPLING ANIMAL POPULATIONS AND COMMUNITIES: GENERAL PRINCIPLES -- WHY? -- WHAT? -- HOW? -- 1.3. INFERENCE ABOUT DYNAMICS AND CAUSATION -- GENERATION OF SYSTEM DYNAMICS -- STATICS AND PROCESS VS. PATTERN -- 1.4. DISCUSSION -- CHAPTER 2: Occupancy in Ecological Investigations -- 2.1. GEOGRAPHIC RANGE -- 2.2. HABITAT RELATIONSHIPS AND RESOURCE SELECTION -- 2.3. METAPOPULATION DYNAMICS -- INFERENCE BASED ON SINGLE-SEASON DATA -- INFERENCE BASED ON MULTIPLE-SEASON DATA -- 2.4. LARGE-SCALE MONITORING -- 2.5. MULTISPECIES OCCUPANCY DATA -- INFERENCE BASED ON STATIC OCCUPANCY PATTERNS -- INFERENCE BASED ON OCCUPANCY DYNAMICS -- 2.6. DISCUSSION -- CHAPTER 3: Fundamental Principles of Statistical Inference -- 3.1. DEFINITIONS AND KEY CONCEPTS -- RANDOM VARIABLES, PROBABILITY DISTRIBUTIONS, AND THE LIKELIHOOD FUNCTION -- EXPECTED VALUES -- INTRODUCTION TO METHODS OF ESTIMATION -- PROPERTIES OF POINT ESTIMATORS -- Bias -- Precision (Variance and Standard Error) -- Accuracy (Mean Squared Error) -- COMPUTER-INTENSIVE METHODS -- 3.2. MAXIMUM LIKELIHOOD ESTIMATION METHODS -- MAXIMUM LIKELIHOOD ESTIMATORS -- PROPERTIES OF MAXIMUM LIKELIHOOD ESTIMATORS -- VARIANCES, COVARIANCE (AND STANDARD ERROR) ESTIMATION -- CONFIDENCE INTERVAL ESTIMATORS -- 3.3. BAYESIAN METHODS OF ESTIMATION -- THEORY -- COMPUTING METHODS -- 3.4. MODELING AUXILIARY VARIABLES -- THE LOGIT LINK FUNCTION -- ESTIMATION -- 3.5. HYPOTHESIS TESTING -- BACKGROUND AND DEFINITIONS -- LIKELIHOOD RATIO TESTS -- GOODNESS OF FIT TESTS -- 3.6. MODEL SELECTION -- THE AKAIKE INFORMATION CRITERION (AIC) -- GOODNESS OF FIT AND OVERDISPERSION -- QUASI-AIC -- MODEL AVERAGING AND MODEL SELECTION UNCERTAINTY -- 3.7. DISCUSSION.
CHAPTER 4: Single-species, Single-season Occupancy Models -- 4.1. THE SAMPLING SITUATION -- 4.2. ESTIMATION OF OCCUPANCY IF PROBABILITY OF DETECTION IS 1 OR KNOWN WITHOUT ERROR -- 4.3. TWO-STEP AD HOC APPROACHES -- GEISSLER-FULLER METHOD -- AZUMA-BALDWIN-NOON METHOD -- NICHOLS-KARANTH METHOD -- 4.4. MODEL-BASED APPROACH -- BUILDING A MODEL -- ESTIMATION -- Constant Detection Probability Model -- Survey-specific Detection Probability Model -- Probability of Occupancy Given Species Not Detected at a Site -- EXAMPLE: BLUE-RIDGE TWO-LINED SALAMANDERS -- MISSING OBSERVATIONS -- COVARIATE MODELING -- VIOLATIONS OF MODEL ASSUMPTIONS -- ASSESSING MODEL FIT -- EXAMPLES -- Pronghorn Antelope -- Mahoenui Giant Weta -- 4.5. ESTIMATING OCCUPANCY FOR A FINITE POPULATION OR SMALL AREA -- PREDICTION OF UNOBSERVED OCCUPANCY STATE -- A BAYESIAN FORMULATION OF THE MODEL -- BLUE-RIDGE TWO-LINED SALAMANDERS REVISITED -- 4.6. DISCUSSION -- CHAPTER 5: Single-species, Single-season Models with Heterogeneous Detection Probabilities -- 5.1. SITE OCCUPANCY MODELS WITH HETEROGENEOUS DETECTION -- GENERAL FORMULATION -- FINITE MIXTURES -- CONTINUOUS MIXTURES -- ABUNDANCE MODELS -- MODEL FIT -- 5.2. EXAMPLE: BREEDING BIRD POINT COUNT DATA -- 5.3. GENERALIZATIONS: COVARIATE EFFECTS -- 5.4. EXAMPLE: ANURAN CALLING SURVEY DATA -- 5.5. ON THE IDENTIFIABILITY OF ψ -- 5.6. DISCUSSION -- CHAPTER 6: Design of Single-season Occupancy Studies -- 6.1. DEFINING A "SITE" -- 6.2. SITE SELECTION -- 6.3. DEFINING A "SEASON" -- 6.4. CONDUCTING REPEAT SURVEYS -- 6.5. ALLOCATION OF EFFORT: NUMBER OF SITES VS. NUMBER OF SURVEYS -- STANDARD DESIGN -- No Consideration of Cost -- Including Survey Cost -- DOUBLE SAMPLING DESIGN -- REMOVAL SAMPLING DESIGN -- MORE SITES VS. MORE SURVEYS -- 6.6. DISCUSSION -- CHAPTER 7: Single-species, Multiple-season Occupancy Models -- 7.1. BASIC SAMPLING SCHEME.
7.2. AN IMPLICIT DYNAMICS MODEL -- 7.3. MODELING DYNAMIC CHANGES EXPLICITLY -- MODELING DYNAMIC PROCESSES WHEN DETECTION PROBABILITY IS 1 -- CONDITIONAL MODELING OF DYNAMIC PROCESSES -- UNCONDITIONAL MODELING OF DYNAMIC PROCESSES -- MISSING OBSERVATIONS -- INCLUDING COVARIATE INFORMATION -- ALTERNATIVE PARAMETERIZATIONS -- EXAMPLE: HOUSE FINCH EXPANSION IN NORTH AMERICA -- 7.4. INVESTIGATING OCCUPANCY DYNAMICS -- MARKOVIAN, RANDOM AND NO CHANGES IN OCCUPANCY -- EQUILIBRIUM -- EXAMPLE: NORTHERN SPOTTED OWL -- 7.5. VIOLATIONS OF MODEL ASSUMPTIONS -- 7.6. MODELING HETEROGENEOUS DETECTION PROBABILITIES -- 7.7. STUDY DESIGN -- TIME INTERVAL BETWEEN "SEASONS" -- SAME VS. DIFFERENT SITES EACH SEASON -- MORE SITES VS. MORE SEASONS -- MORE ON SITE SELECTION -- 7.8. DISCUSSION -- CHAPTER 8: Occupancy Data for Multiple Species: Species Interactions -- 8.1. DETECTION PROBABILITY AND INFERENCES ABOUT SPECIES CO-OCCURRENCE -- 8.2. A SINGLE-SEASON MODEL -- GENERAL SAMPLING SITUATION -- STATISTICAL MODEL -- REPARAMETERIZING THE MODEL -- INCORPORATING COVARIATE INFORMATION -- MISSING OBSERVATIONS -- 8.3. ADDRESSING BIOLOGICAL HYPOTHESES -- 8.4. EXAMPLE: TERRESTRIAL SALAMANDERS IN GREAT SMOKY MOUNTAINS NATIONAL PARK -- 8.5. STUDY DESIGN ISSUES -- 8.6. EXTENSION TO MULTIPLE SEASONS -- 8.7. DISCUSSION -- CHAPTER 9: Occupancy in Community-level Studies -- 9.1. INVESTIGATING THE COMMUNITY AT A SINGLE SITE -- FRACTION OF SPECIES PRESENT IN A SINGLE SEASON -- CHANGES IN THE FRACTION OF SPECIES PRESENT OVER TIME -- 9.2. INVESTIGATING THE COMMUNITY AT MULTIPLE SITES -- SINGLE-SEASON STUDIES: MODELING OCCUPANCY AND DETECTION -- SINGLE-SEASON STUDIES: SPECIES RICHNESS ESTIMATION -- EXAMPLE: AVIAN POINT COUNT DATA -- MULTIPLE-SEASON STUDIES -- 9.3. DISCUSSION -- CHAPTER 10: Future Directions -- 10.1. MULTIPLE OCCUPANCY STATES -- 10.2. INTEGRATED MODELING OF HABITAT AND OCCUPANCY.
10.3. INCORPORATING INFORMATION ON MARKED ANIMALS -- 10.4. INCORPORATING COUNT AND OTHER DATA -- 10.5. RELATIONSHIP BETWEEN OCCUPANCY AND ABUNDANCE -- 10.6. DISCUSSION -- APPENDIX: Some Important Mathematical Concepts -- References -- Index.
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.
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Front cover -- Title page -- Copyright page -- Table of Contents -- Preface -- Acknowledgments -- CHAPTER 1: Introduction -- 1.1. OPERATIONAL DEFINITIONS -- 1.2. SAMPLING ANIMAL POPULATIONS AND COMMUNITIES: GENERAL PRINCIPLES -- WHY? -- WHAT? -- HOW? -- 1.3. INFERENCE ABOUT DYNAMICS AND CAUSATION -- GENERATION OF SYSTEM DYNAMICS -- STATICS AND PROCESS VS. PATTERN -- 1.4. DISCUSSION -- CHAPTER 2: Occupancy in Ecological Investigations -- 2.1. GEOGRAPHIC RANGE -- 2.2. HABITAT RELATIONSHIPS AND RESOURCE SELECTION -- 2.3. METAPOPULATION DYNAMICS -- INFERENCE BASED ON SINGLE-SEASON DATA -- INFERENCE BASED ON MULTIPLE-SEASON DATA -- 2.4. LARGE-SCALE MONITORING -- 2.5. MULTISPECIES OCCUPANCY DATA -- INFERENCE BASED ON STATIC OCCUPANCY PATTERNS -- INFERENCE BASED ON OCCUPANCY DYNAMICS -- 2.6. DISCUSSION -- CHAPTER 3: Fundamental Principles of Statistical Inference -- 3.1. DEFINITIONS AND KEY CONCEPTS -- RANDOM VARIABLES, PROBABILITY DISTRIBUTIONS, AND THE LIKELIHOOD FUNCTION -- EXPECTED VALUES -- INTRODUCTION TO METHODS OF ESTIMATION -- PROPERTIES OF POINT ESTIMATORS -- Bias -- Precision (Variance and Standard Error) -- Accuracy (Mean Squared Error) -- COMPUTER-INTENSIVE METHODS -- 3.2. MAXIMUM LIKELIHOOD ESTIMATION METHODS -- MAXIMUM LIKELIHOOD ESTIMATORS -- PROPERTIES OF MAXIMUM LIKELIHOOD ESTIMATORS -- VARIANCES, COVARIANCE (AND STANDARD ERROR) ESTIMATION -- CONFIDENCE INTERVAL ESTIMATORS -- 3.3. BAYESIAN METHODS OF ESTIMATION -- THEORY -- COMPUTING METHODS -- 3.4. MODELING AUXILIARY VARIABLES -- THE LOGIT LINK FUNCTION -- ESTIMATION -- 3.5. HYPOTHESIS TESTING -- BACKGROUND AND DEFINITIONS -- LIKELIHOOD RATIO TESTS -- GOODNESS OF FIT TESTS -- 3.6. MODEL SELECTION -- THE AKAIKE INFORMATION CRITERION (AIC) -- GOODNESS OF FIT AND OVERDISPERSION -- QUASI-AIC -- MODEL AVERAGING AND MODEL SELECTION UNCERTAINTY -- 3.7. DISCUSSION.

CHAPTER 4: Single-species, Single-season Occupancy Models -- 4.1. THE SAMPLING SITUATION -- 4.2. ESTIMATION OF OCCUPANCY IF PROBABILITY OF DETECTION IS 1 OR KNOWN WITHOUT ERROR -- 4.3. TWO-STEP AD HOC APPROACHES -- GEISSLER-FULLER METHOD -- AZUMA-BALDWIN-NOON METHOD -- NICHOLS-KARANTH METHOD -- 4.4. MODEL-BASED APPROACH -- BUILDING A MODEL -- ESTIMATION -- Constant Detection Probability Model -- Survey-specific Detection Probability Model -- Probability of Occupancy Given Species Not Detected at a Site -- EXAMPLE: BLUE-RIDGE TWO-LINED SALAMANDERS -- MISSING OBSERVATIONS -- COVARIATE MODELING -- VIOLATIONS OF MODEL ASSUMPTIONS -- ASSESSING MODEL FIT -- EXAMPLES -- Pronghorn Antelope -- Mahoenui Giant Weta -- 4.5. ESTIMATING OCCUPANCY FOR A FINITE POPULATION OR SMALL AREA -- PREDICTION OF UNOBSERVED OCCUPANCY STATE -- A BAYESIAN FORMULATION OF THE MODEL -- BLUE-RIDGE TWO-LINED SALAMANDERS REVISITED -- 4.6. DISCUSSION -- CHAPTER 5: Single-species, Single-season Models with Heterogeneous Detection Probabilities -- 5.1. SITE OCCUPANCY MODELS WITH HETEROGENEOUS DETECTION -- GENERAL FORMULATION -- FINITE MIXTURES -- CONTINUOUS MIXTURES -- ABUNDANCE MODELS -- MODEL FIT -- 5.2. EXAMPLE: BREEDING BIRD POINT COUNT DATA -- 5.3. GENERALIZATIONS: COVARIATE EFFECTS -- 5.4. EXAMPLE: ANURAN CALLING SURVEY DATA -- 5.5. ON THE IDENTIFIABILITY OF ψ -- 5.6. DISCUSSION -- CHAPTER 6: Design of Single-season Occupancy Studies -- 6.1. DEFINING A "SITE" -- 6.2. SITE SELECTION -- 6.3. DEFINING A "SEASON" -- 6.4. CONDUCTING REPEAT SURVEYS -- 6.5. ALLOCATION OF EFFORT: NUMBER OF SITES VS. NUMBER OF SURVEYS -- STANDARD DESIGN -- No Consideration of Cost -- Including Survey Cost -- DOUBLE SAMPLING DESIGN -- REMOVAL SAMPLING DESIGN -- MORE SITES VS. MORE SURVEYS -- 6.6. DISCUSSION -- CHAPTER 7: Single-species, Multiple-season Occupancy Models -- 7.1. BASIC SAMPLING SCHEME.

7.2. AN IMPLICIT DYNAMICS MODEL -- 7.3. MODELING DYNAMIC CHANGES EXPLICITLY -- MODELING DYNAMIC PROCESSES WHEN DETECTION PROBABILITY IS 1 -- CONDITIONAL MODELING OF DYNAMIC PROCESSES -- UNCONDITIONAL MODELING OF DYNAMIC PROCESSES -- MISSING OBSERVATIONS -- INCLUDING COVARIATE INFORMATION -- ALTERNATIVE PARAMETERIZATIONS -- EXAMPLE: HOUSE FINCH EXPANSION IN NORTH AMERICA -- 7.4. INVESTIGATING OCCUPANCY DYNAMICS -- MARKOVIAN, RANDOM AND NO CHANGES IN OCCUPANCY -- EQUILIBRIUM -- EXAMPLE: NORTHERN SPOTTED OWL -- 7.5. VIOLATIONS OF MODEL ASSUMPTIONS -- 7.6. MODELING HETEROGENEOUS DETECTION PROBABILITIES -- 7.7. STUDY DESIGN -- TIME INTERVAL BETWEEN "SEASONS" -- SAME VS. DIFFERENT SITES EACH SEASON -- MORE SITES VS. MORE SEASONS -- MORE ON SITE SELECTION -- 7.8. DISCUSSION -- CHAPTER 8: Occupancy Data for Multiple Species: Species Interactions -- 8.1. DETECTION PROBABILITY AND INFERENCES ABOUT SPECIES CO-OCCURRENCE -- 8.2. A SINGLE-SEASON MODEL -- GENERAL SAMPLING SITUATION -- STATISTICAL MODEL -- REPARAMETERIZING THE MODEL -- INCORPORATING COVARIATE INFORMATION -- MISSING OBSERVATIONS -- 8.3. ADDRESSING BIOLOGICAL HYPOTHESES -- 8.4. EXAMPLE: TERRESTRIAL SALAMANDERS IN GREAT SMOKY MOUNTAINS NATIONAL PARK -- 8.5. STUDY DESIGN ISSUES -- 8.6. EXTENSION TO MULTIPLE SEASONS -- 8.7. DISCUSSION -- CHAPTER 9: Occupancy in Community-level Studies -- 9.1. INVESTIGATING THE COMMUNITY AT A SINGLE SITE -- FRACTION OF SPECIES PRESENT IN A SINGLE SEASON -- CHANGES IN THE FRACTION OF SPECIES PRESENT OVER TIME -- 9.2. INVESTIGATING THE COMMUNITY AT MULTIPLE SITES -- SINGLE-SEASON STUDIES: MODELING OCCUPANCY AND DETECTION -- SINGLE-SEASON STUDIES: SPECIES RICHNESS ESTIMATION -- EXAMPLE: AVIAN POINT COUNT DATA -- MULTIPLE-SEASON STUDIES -- 9.3. DISCUSSION -- CHAPTER 10: Future Directions -- 10.1. MULTIPLE OCCUPANCY STATES -- 10.2. INTEGRATED MODELING OF HABITAT AND OCCUPANCY.

10.3. INCORPORATING INFORMATION ON MARKED ANIMALS -- 10.4. INCORPORATING COUNT AND OTHER DATA -- 10.5. RELATIONSHIP BETWEEN OCCUPANCY AND ABUNDANCE -- 10.6. DISCUSSION -- APPENDIX: Some Important Mathematical Concepts -- References -- Index.

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.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2019. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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