05408nam 22006254a 450 991078454460332120220311183301.01-280-62849-997866106284900-08-045504-2(CKB)1000000000364656(EBL)269546(OCoLC)475997780(SSID)ssj0000213385(PQKBManifestationID)11173708(PQKBTitleCode)TC0000213385(PQKBWorkID)10151098(PQKB)10296292(Au-PeEL)EBL269546(CaPaEBR)ebr10138121(CaONFJC)MIL62849(MiAaPQ)EBC269546(EXLCZ)99100000000036465620050630d2006 uy 0engur|n|---|||||txtccrOccupancy estimation and modeling[electronic resource] inferring patterns and dynamics of species /Darryl I. MacKenzie ... [et al]Amsterdam ;Boston Elsevierc20061 online resource (343 p.)Description based upon print version of record.0-12-088766-5 Includes bibliographical references (p. 293-312).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 DATA2.4. LARGE-SCALE MONITORING2.5. 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 ESTIMATORSPROPERTIES OF MAXIMUM LIKELIHOOD ESTIMATORSVARIANCES, 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 Models4.1. THE SAMPLING SITUATION4.2. 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 AntelopeMahoenui Giant Weta4.5. 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 DATA5.5. ON THE IDENTIFIABILITY OF ?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 insighAnimal populationsEstimatesAnimal populationsMathematical modelsAnimal populationsEstimates.Animal populationsMathematical models.591.7/88/015118MacKenzie Darryl I1528723MiAaPQMiAaPQMiAaPQBOOK9910784544603321Occupancy estimation and modeling3772561UNINA