LEADER 05408nam 22006254a 450 001 9910784544603321 005 20220311183301.0 010 $a1-280-62849-9 010 $a9786610628490 010 $a0-08-045504-2 035 $a(CKB)1000000000364656 035 $a(EBL)269546 035 $a(OCoLC)475997780 035 $a(SSID)ssj0000213385 035 $a(PQKBManifestationID)11173708 035 $a(PQKBTitleCode)TC0000213385 035 $a(PQKBWorkID)10151098 035 $a(PQKB)10296292 035 $a(Au-PeEL)EBL269546 035 $a(CaPaEBR)ebr10138121 035 $a(CaONFJC)MIL62849 035 $a(MiAaPQ)EBC269546 035 $a(EXLCZ)991000000000364656 100 $a20050630d2006 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aOccupancy estimation and modeling$b[electronic resource] $einferring patterns and dynamics of species /$fDarryl I. MacKenzie ... [et al] 210 $aAmsterdam ;$aBoston $cElsevier$dc2006 215 $a1 online resource (343 p.) 300 $aDescription based upon print version of record. 311 $a0-12-088766-5 320 $aIncludes bibliographical references (p. 293-312). 327 $aFront 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 327 $a2.4. 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 ESTIMATORS 327 $aPROPERTIES 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 Models 327 $a4.1. 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 Antelope 327 $aMahoenui 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 DATA 327 $a5.5. ON THE IDENTIFIABILITY OF ? 330 $aOccupancy 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 insigh 606 $aAnimal populations$xEstimates 606 $aAnimal populations$xMathematical models 615 0$aAnimal populations$xEstimates. 615 0$aAnimal populations$xMathematical models. 676 $a591.7/88/015118 701 $aMacKenzie$b Darryl I$01528723 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910784544603321 996 $aOccupancy estimation and modeling$93772561 997 $aUNINA