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Wildlife Demography: Analysis of Sex, Age, and Count Data [Kietas viršelis]

(University of Washington, Seattle, U.S.A.), (University of Washington, Seattle, U.S.A.), (University of Missouri, School of Natural Resources, Columbia, USA)
  • Formatas: Hardback, 656 pages, aukštis x plotis: 260x184 mm, weight: 1560 g
  • Išleidimo metai: 08-Nov-2005
  • Leidėjas: Academic Press Inc
  • ISBN-10: 0120887738
  • ISBN-13: 9780120887736
Kitos knygos pagal šią temą:
  • Formatas: Hardback, 656 pages, aukštis x plotis: 260x184 mm, weight: 1560 g
  • Išleidimo metai: 08-Nov-2005
  • Leidėjas: Academic Press Inc
  • ISBN-10: 0120887738
  • ISBN-13: 9780120887736
Kitos knygos pagal šią temą:
Wildlife Demography compiles the multitude of available estimation techniques based on sex and age data, and presents these varying techniques in one organized, unified volume. Designed to guide researchers to the most appropriate estimator based upon their particular data set and the desired level of study precision, this book provides quantitative consideration, statistical models, estimator variance, assumptions and examples of use.

The authors focus on estimation techniques using sex and age ratios because this data is relatively easy to collect and commonly used by wildlife management

* Applicable to a wide array of wildlife species, including game and non-game birds and mammals
* Features more than 100 annotated examples illustrating application of statistical methods
* Includes more than 640 references of the analysis of nontagging data and the factors that may influence interpretation
* Derives historical and ad hoc demographic methods in a modern statistical framework

Recenzijos

"The author's exhaustive treatment of analytical techniques including listing assumptions, strengths and limitations, example calculations, and decision trees, makes this text an excellent reference for any advanced wildlife student or professional. It is an excellent compendium that replaces an entire file drawer of reprints I have accumulated over the past 25 years." --Robert A. Garrott, Montana State University, Bozeman

"Methodological progress in wildlife population ecology, like temporal change in taxonomic diversity, can be characterized as punctuated equilibrium”, with long periods of stasis and slow growth punctuated by short periods of rapid development. Synthetic monographs and books have catalyzed these periods of rapid development, providing updated starting points upon which extensions and new models are based. Wildlife Demography will provide such a synthetic basis for methods based on sex and age ratio data and should lead to rapid progress in approaches that combine these and other data types for improved demographic inference." --James D. Nichols, Patuxent Wildlife Research Center, USGS

"This book provides a comprehensive introduction to techniques for estimating demographic parameters with sex, age and count data. It is unique in that it focuses solely on these approaches, using data that can often be obtained very cost-effectively and that are routinely collected by many wildlife agencies. Strengths of the book include careful lists of assumptions for each method with concrete examples to illustrate their application and a final chapter that demonstrates how multiple sources of data can be effectively combined using joint-likelihoods. This book will make an excellent textbook for students of wildlife demography and will serve as a useful reference for practicing wildlife biologists and managers." --Mark S. Udevitz, USGS Alaska Science Center, Anchorage

Daugiau informacijos

The first comprehensive compilation of statistical methods for analyzis of sex, age and count data in wildlife investigations
Foreword xi
Preface xv
Introduction
1(10)
Historical Perspectives and Current Needs
1(2)
Scope of Book
3(8)
Primer on Wildlife Population Dynamics
11(38)
Introduction
11(1)
Continuous Time Models
12(2)
Discrete Time Models
14(1)
Logistic Population Growth
15(11)
Age Structure Models
26(9)
Stage Structure Models
35(2)
Harvest Management Theory
37(10)
Annual Surplus Model
39(4)
Sustained Yield Model
43(4)
Summary
47(2)
Estimating Population Sex Ratios
49(40)
Introduction
49(3)
Statistical Notation
50(1)
Alternative Definitions of Sex Ratio
51(1)
Direct Versus Indirect Methods of Estimating Sex Ratios
52(1)
Direct Sampling Techniques
52(17)
Single Sample Survey without Replacement
52(3)
Single Sample Survey with Replacement
55(4)
Multiple Samples with Replacement
59(3)
Stratified Random Sampling
62(3)
Unequal Detection Probabilities among Sexes
65(1)
Cluster Sampling Methods
66(3)
Indirect Methods of Estimating Sex Ratios
69(7)
Sampling without Replacement
70(4)
Sampling with Replacement
74(1)
Juvenile Sex Ratio ≠ 1
75(1)
Sex Ratio Projections Based on Survival and Harvest Rates
76(9)
Constant Annual Survival for All Age Classes
77(6)
Unique Juvenile Survival Probabilities
83(1)
Unique Juvenile, Subadult, and Adult Survival Probabilities
84(1)
Juvenile Sex Ratio ≠ 1 : 1
84(1)
Summary
85(4)
Estimating Productivity
89(40)
Introduction
89(5)
Standard Notation
92(1)
Alternative Definitions of Productivity Measures
92(1)
Direct Versus Indirect Methods of Estimating Productivity
93(1)
Direct Sampling Techniques
94(11)
Single Survey
94(1)
Repeated Surveys
95(2)
Productivity Adjusted for Breeding Success
97(1)
Productivity Adjustment for Renesting
98(4)
Estimating Nesting Success: Mayfield (1975) Method
102(3)
Estimating Productivity from Sex and Age Ratios
105(20)
Stokes (1954)--Hanson (1963) Method
105(4)
Generalized Stokes (1954)--Hanson (1963) Method
109(5)
Dale (1952)--Stokes (1954) Method
114(7)
Generalized Dale (1952)-Stokes (1954) Method
121(4)
Summary
125(4)
Estimating Survival
129(100)
Introduction
130(1)
Basic Concepts and Notation
130(3)
Basic Concepts
130(3)
Notation
133(1)
Survival Curve Analysis
133(17)
Kaplan-Meier (1958) or Product-Limit Estimator
133(3)
Nelson (1972)-Aalen (1978) Estimator
136(3)
Nonparametric Test for Comparing Survival Curves
139(2)
Parametric Survival Curve Analysis
141(9)
Horizontal Life Tables
150(9)
Standard Life-Table Analysis
151(4)
Constant Survival Across Age Classes
155(4)
Vertical Life Tables
159(10)
Standard Life-Table Analysis
160(8)
Estimating Survival with Truncated Age Classes
168(1)
Vertical Life Table with Constrained Survival
168(1)
Depositional Life Tables
169(8)
Standard Life-Table Analysis
170(2)
Nonstationary Populations: Udevitz and Ballachey (1998)
172(5)
lx-Series Data with Abbreviated or Pooled Age Classes
177(10)
Hayne and Eberhardt (1952)
177(2)
Modified Hayne and Eberhardt (1952) for Unequal Juvenile Survival
179(2)
Modified Hayne and Eberhardt (1952) Pooling Older Age Classes
181(2)
Modified Hayne and Eberhardt (1952) with Pooled Age Classes and Unique Juvenile Survival
183(2)
Heincke (1913) and Burgoyne (1981)
185(2)
cx-Series Data with Abbreviated or Pooled Age Classes
187(6)
cx-Series with the First Three Age Classes
187(3)
Older Age Classes Pooled
190(3)
Catch-Curve Analyses
193(12)
Estimating Survival Using All Age Classes (Chapman and Robson 1960)
193(4)
Survival Estimation with Older Age Classes Pooled (Robson and Chapman 1961)
197(2)
Estimator for Left- and Right-Truncated Data: Chapman and Robson (1960) and Robson and Chapman (1961)
199(6)
Regression Techniques
205(6)
Regression on Age-Structure Data
205(5)
Regression on Abundance Estimates
210(1)
Estimating Juvenile Survival
211(14)
Two-Sample Change-in-Ratio Methods of Hanson (1963) and Paulik and Robson (1969)
212(4)
Three-Sample Change-in-Ratio Methods of Selleck and Hart (1957) and White et al. (1996)
216(5)
Life-History Methods of Keith and Windberg (1978)
221(4)
Discussion
225(4)
Estimating Harvest and Harvest Mortality
229(60)
Introduction
229(1)
Analysis of Harvest Records
230(14)
Locker and Field Checks
231(2)
Random Sample of Hunter Responses
233(5)
Resampling for Nonresponse
238(6)
Estimating Harvest by Area
244(11)
Common Reporting and Success Probabilities (White 1993)
245(5)
Unique Reporting and Success Probabilities
250(5)
Direct Estimation of Harvest Mortality
255(1)
Estimating Harvest Mortality from Sex Ratios
256(3)
Change-in-Ratio Methods
259(10)
Two-Sample Change-in-Ratio Methods (Paulik and Robson 1969)
259(4)
Three-Sample Change-in-Ratio Method (Selleck and Hart 1957)
263(6)
Index-Removal Method: Petrides (1949) and Eberhardt (1982)
269(4)
Catch-Effort Methods
273(10)
Successive Sex Ratios: Paloheimo and Fraser (1981)
273(5)
Age-at-Harvest Data: Paloheimo and Fraser (1981), Harris and Metzgar (1987)
278(5)
Proportion of Mortality Owing to Harvest (Gulland 1955)
283(3)
Summary
286(3)
Estimating the Rate of Population Change
289(70)
Introduction
289(2)
Basic Concepts and Definitions
291(3)
Two-Sample Methods for Estimating r and λ
294(3)
Exponential-Growth Models
297(17)
Nonlinear Regression for Estimating r or λ
297(4)
Log-Linear Regression for Estimating r
301(2)
Ratio Estimators for λ
303(3)
Time-Series Analysis of λ
306(8)
Logistic-Growth Models
314(8)
Growth Models with Removals
322(6)
Exponential-Growth Models
322(3)
Accounting for Missing Abundance Values
325(1)
Logistic-Growth Models
326(2)
Productivity-Based Estimator of λ (Kelker 1947)
328(2)
Estimating λ Using the Lotka Equation (Cole 1954)
330(15)
General Expression
330(5)
Evaluation of Average Fecundity (Henny et al. 1970)
335(3)
Special Case: Two Age Classes (Henny et al. 1970, Cowardin and Johnson 1979)
338(2)
Special Case: Two Age Classes with Harvest
340(1)
Special Case: Three Age Classes
340(3)
Special Case: Four Age Classes
343(1)
General Case
344(1)
Estimating λ from a Leslie Matrix (Bernardelli 1941, Leslie 1945, 1948)
345(10)
Summary
355(4)
Analysis of Population Indices
359(76)
Introduction
359(15)
Relationship between Indices and Abundance
361(1)
Basic Sampling Methods
362(12)
Description of Common Indices
374(21)
Pellet Counts
375(3)
Frequency Index
378(3)
Auditory Counts
381(4)
Visual Counts
385(4)
Catch-per-Unit Effort
389(4)
Trap-Line Counts
393(1)
Mark-Recapture Estimates as Indices
394(1)
Design of Index Studies
395(8)
Latin-Square Designs
396(4)
Randomized Block Designs
400(3)
Calibration of Indices
403(19)
Index-Removal Method: Petrides (1949) and Eberhardt (1982)
403(3)
Intercalibrating Two Indices
406(1)
Ratio Estimators
407(2)
Regression Estimators
409(4)
Double Sampling for Ratios
413(4)
Double Sampling for Regression
417(5)
Analysis of Index Studies
422(10)
Example: Forest Birds, New South Wales, Australia
423(3)
Example: Deer Trail Counts, Wisconsin
426(2)
Example: Dall Sheep (Ovis dalli) Aerial Counts, Arctic National Wildlife Refuge, Alaska
428(2)
Example: White-Tailed Deer Pellet Counts, George Reserve, Michigan
430(2)
Summary
432(3)
Estimating Population Abundance
435(106)
Introduction
436(1)
Visual Surveys
436(19)
Strip Transects
437(3)
Bounded Counts: Robson and Whitlock (1964), Regier and Robson (1967)
440(1)
Binomial Method-of-Moments (Overton 1969)
441(3)
Sightability Models
444(7)
Sight-Resight Method
451(4)
Line Transects
455(10)
Fixed-Distance Methods
456(5)
Right-Angle Distance Methods
461(4)
Index-Removal Method (Petrides 1949, Eberhardt 1982)
465(1)
Change-in-Ratio Methods
466(9)
Two-Class Model
467(4)
Three or More Classes
471(2)
Sequential Change-in-Ratio
473(2)
Catch-Effort Methods
475(21)
Maximum Likelihood Model
476(3)
Leslie and Davis (1939) Method
479(3)
DeLury (1947, 1951) Method
482(4)
Constant Effort Removal Technique (Zippin 1956, 1958)
486(10)
Life-History Models
496(13)
Sex-Age-Kill Model
497(5)
SAK-MLE Model
502(5)
Duck Nest Survey Model
507(2)
Age-Structured Population Reconstruction Methods
509(28)
Virtual Population Analysis (Fry 1949, 1957)
511(5)
Virtual Population Analysis (Gulland 1965)
516(6)
Cohort Analysis (Pope 1972)
522(4)
Discrete-Time Virtual Population Analysis (Fryxell et al. 1988)
526(2)
Statistical Age-at-Harvest Analysis (Gove et al. 2002)
528(9)
Summary
537(4)
Integration of Analytical Techniques
541(24)
Introduction and Purpose
541(1)
Management for Desired Sex Ratios of Elk
542(5)
Combining Field Results with Leslie Matrix Projections
547(4)
Comparing and Combining Time- and Cohort-Specific Survival Data
551(4)
A Bighorn Sheep Life-History-Based Abundance Estimator
555(5)
Partitioning Harvest and Natural Mortality
560(2)
Ring-Necked Pheasant Multisurvey Study
562(3)
Appendix A: Statistical Concepts and Theory 565(10)
Appendix B: Glossary of Symbols 575(4)
Appendix C: Program USER 579(12)
Appendix D: Mathematica Code for Calculating the Variance of the Finite Rate of Population Change, Var(λ), from a Matrix Population Model 591(8)
References 599(30)
Index 629