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9780412047114

Statistical Ecology

by ;
  • ISBN13:

    9780412047114

  • ISBN10:

    041204711X

  • Format: Hardcover
  • Copyright: 1998-04-01
  • Publisher: Kluwer Academic Pub

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Supplemental Materials

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Summary

Covering a wide range of disciplines, this book explains the formulae, techniques, and methods used in field ecology. By providing an awareness of the statistical foundation for existing methods, the book will make biologists more aware of the strengths and possible weaknesses of procedures employed, and statisticians more appreciative of the needs of the field ecologist. Unique to this book is a focus on ecological data for single-species populations, from sampling through modeling. Examples come from real situations in pest management, forestry, wildlife biology, plant protection, and environmental studies, as well as from classical ecology. All those using this book will acquire a strong foundation in the statistical methods of modern ecological research. This textbook is for late undergraduate and graduate students, and for professionals. Readers may download free from a web site the ECOSTAT software developed by the authors: http://www.ianr.unl.edu/ianr/biometry/faculty/linda/lyoung.html

Table of Contents

Preface xiii(2)
Acknowledgments xv
Chapter 1: Probability Distributions
1(41)
Introduction
1(1)
Discrete Distributions
2(6)
Negative Binomial Distribution
7(1)
Expected Frequencies
8(6)
Geometric Distribution
13(1)
Expected Frequencies
14(4)
Binomial Distribution
17(1)
Expected Frequencies
18(5)
Poisson Distribution
22(2)
Expected Frequencies
23(1)
Confidence Intervals
24(2)
Continuous Distributions
26(1)
Normal Distribution
27(6)
Lognormal Distribution
33(1)
Exponential Distribution
34(1)
Gamma Distribution
35(2)
Weibull Distribution
37(1)
Summary
38(1)
Exercises
39(3)
Chapter 2: Goodness-of-Fit Tests
42(33)
Introduction
42(2)
Pearson's Chi-Squared Test
44(6)
Likelihood Ratio Test
50(2)
Freeman-Tukey Chi-Squared Test
52(2)
Power Divergence Statistic
54(1)
Nass Test
55(3)
Kolmogrov-Smirnov Test
58(7)
Summary
65(1)
Exercises
66(4)
Appendix
70(5)
Chapter 3: Models and Sampling
75(24)
Introduction
75(1)
Binomial Models
75(1)
Poisson Models
76(1)
Negative Binomial Models
76(2)
Bose-Einstein Versus Maxwell-Boltzmann Statistics
78(4)
Stochastic Immigration Model
82(2)
Modeling Within Field Movement
84(1)
Restrictions on Carrying Capacity
85(2)
Sampling Concepts
87(5)
Simple Random Sampling
93(3)
Stratified Random Sampling
93(3)
Systematic Sampling
96(1)
Ratio Estimation
97(1)
Summary
97(2)
Chapter 4: Sequential Estimation
99(54)
Introduction
99(1)
Sample Sizes Required to Control CV (X)
100(5)
Sample Sizes Required to Set Confidence Intervals
105(5)
Length Proportional to the Parameter of Interest
106(2)
Length Fixed
108(2)
Sequential Estimation
110(2)
Sequential Estimation for the Negative Binomial
112(17)
Parameter k Unknown
112(2)
Estimating Parameter k
114(9)
Parameter k Known
123(6)
Sequential Estimation for the Geometric
129(2)
Sequential Estimation for the Poisson
131(2)
Sequential Estimation for the Binomial
133(3)
Sequential Estimation Based on Iwao's Patchiness Regression
136(8)
Sequential Sampling Based on Taylor's Power Law
144(4)
Summary
148(1)
Exercises
149(4)
Chapter 5: Sequential Hypothesis Testing
153(38)
Introduction
153(1)
Wald's Sequential Probability Ratio Test
153(6)
SPRT for the Negative Binomial Distribution
159(3)
SPRT for the Poisson Distribution
162(3)
SPRT for the Binomial Distribution
165(2)
Operating Characteristic and Average Sample Number Functions
167(6)
The 2-SPRT
173(13)
Summary
186(2)
Exercises
188(3)
Chapter 6: Sequentially Testing Three Hypotheses
191(24)
Introduction
191(1)
Ecologists' Sequential Test
192(7)
Sobel and Wald's Method
199(5)
Armitage's Method
204(5)
Testing Composite Hypotheses
209(4)
Iwao's Method
209(3)
Armitage's Methods
212(1)
Summary
213(1)
Exercises
213(2)
Chapter 7: Aggregation and Spatial Correlation
215(57)
Introduction
215(1)
Measures of Aggregation
216(6)
Variance-to-Mean Ratio and Index of Dispersion
217(1)
Index of Clumping
217(1)
Mean Crowding and Mean Patchiness
218(1)
Comparison of Indices
219(3)
Spatial Correlation
222(9)
Moran's I and Geary's c
224(7)
Geostatistics
231(37)
Intrinsic Stationarity
243(1)
Median Polishing
244(6)
The Semivariogram
250(8)
Summary
268(1)
Exercises
269(3)
Chapter 8: Spatial Point Patterns
272(25)
Introduction
272(1)
Complete Spatial Randomness
273(3)
K(h) amd L(h) Functions
276(8)
Monte Carlo Tests
284(4)
Nearest Neighbor Techniques
288(4)
Summary
292(1)
Exercises
293(2)
Appendix
295(2)
Chapter 9: Capture-Recapture: Closed Populations
297(60)
Introduction
297(1)
Lincoln-Petersen Model
298(12)
Confidence Intervals
300(3)
Sample Size Considerations
303(2)
Assumptions
305(5)
Multiple Recapture Models
310(25)
Model M(o): Constant Capture Probabilities
314(1)
Model M(t): Capture Probabilities Vary With Time Tests for the Model
315(2)
Tests for the Model
317(1)
Model M(b): Behavioral Response to Capture
318(2)
Tests for the Model
320(2)
Model M(h): Heterogeneity of Capture Probabilities
322(2)
Tests for the Model
324(1)
Model M(bh): Heterogeneity of Capture Probabilities and Trap Response
325(1)
Tests for the Model
326(1)
Models M(bt), M(ht), M(bht)
327(3)
Model Selection Confidence Intervals
330(4)
Confidence Intervals
331(4)
Removal and Catch Effort Models
335(3)
Change-in-Ratio or Selective Removal Models
338(9)
Density Estimation
347(1)
Summary
347(1)
Exercises
348(9)
Chapter 10: Capture-Recapture: Open Populations
357(33)
Introduction
357(1)
Jolly-Seber Model
358(17)
Adult Band and Tag Recovery Models
375(8)
Summary
383(1)
Exercises
384(6)
Chapter 11: Transect Sampling
390(31)
Introduction
390(1)
Strip Transects and Circular Plots
391(6)
Line and Point Transects
397(19)
Ungrouped Data
407(5)
Grouped Data
412(2)
Clustered Populations
414(2)
Design
416(1)
Summary
417(1)
Exercises
417(4)
Chapter 12: Degree-Day Models
421(19)
Introduction
421(2)
Assumptions
423(3)
Calculating Degree-Days
426(7)
Summary
433(1)
Exercises
433(7)
Chapter 13: Life-Stage Analysis
440(66)
Introduction
440(3)
Life Tables
443(3)
Key Factor Analysis
446(14)
Varley and Gradwell's Method
447(4)
Regression of K against kj Values
451(2)
Manly Method
453(7)
Multi-Cohort Stage-Frequency Data
460(23)
Kiritani-Nakasuji-Manly Method
462(10)
KNM Iterative Method
472(8)
Kempton Method
480(2)
Bellows and Birley Model
482(1)
Single Cohort Stage-Frequency Data
483(7)
Analysis Using Multi-Cohort Methods
483(3)
Nonparametric Estimation
486(4)
Matrix Models for Reproducing Populations
490(3)
Bernardelli-Leslie-Lewis Model
490(1)
Lefkovitch Model
491(1)
Usher Model
492(1)
Summary
493(1)
Exercises
494(12)
Chapter 14: Probit and Survival Analysis
506(18)
Introduction
506(1)
Probit Analysis
507(7)
Nest Survival Analysis
514(5)
Mayfield Method
514(3)
Pollock Method
517(2)
Analysis of Radiotelemetry Data
519(3)
Trent and Rongstad Method
519(1)
Survival Analysis Model
520(2)
Summary
522(1)
Exercises
522(2)
Chapter 15: Chaos
524(7)
Introduction
524(1)
Population Models
524(4)
Chaos
528(2)
Summary
530(1)
References 531(24)
Index 555

Supplemental Materials

What is included with this book?

The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.

The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.

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