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E-raamat: Measuring Abundance: Methods for the Estimation of Population Size and Species Richness

  • Formaat: 229 pages
  • Sari: Data in the Wild
  • Ilmumisaeg: 12-Oct-2020
  • Kirjastus: Pelagic Publishing
  • Keel: eng
  • ISBN-13: 9781784272340
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  • Formaat: 229 pages
  • Sari: Data in the Wild
  • Ilmumisaeg: 12-Oct-2020
  • Kirjastus: Pelagic Publishing
  • Keel: eng
  • ISBN-13: 9781784272340

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Measuring the abundance of individuals and the diversity of species are core components of most ecological research projects and conservation monitoring. This book brings together in one place, for the first time, the methods used to estimate the abundance of individuals in nature.





The statistical basis of each method is detailed along with practical considerations for survey design and data collection. Methods are illustrated using data ranging from Alaskan shrubs to Yellowstone grizzly bears, not forgetting Costa Rican ants and Prince Edward Island lobsters. Where necessary, example code for use with the open source software R is supplied. When appropriate, reference is made to other widely used programs.





After opening with a brief synopsis of relevant statistical methods, the first section deals with the abundance of stationary items such as trees, shrubs, coral, etc. Following a discussion of the use of quadrats and transects in the contexts of forestry sampling and the assessment of plant cover, there are chapters addressing line-intercept sampling, the use of nearest-neighbour distances, and variable sized plots.





The second section deals with individuals that move, such as birds, mammals, reptiles, fish, etc. Approaches discussed include double-observer sampling, removal sampling, capture-recapture methods and distance sampling.





The final section deals with the measurement of species richness; species diversity; species-abundance distributions; and other aspects of diversity such as evenness, similarity, turnover and rarity.





This is an essential reference for anyone involved in advanced undergraduate or postgraduate ecological research and teaching, or those planning and carrying out data analysis as part of conservation survey and monitoring programmes.

Arvustused

A real strength of Measuring Abundance is the simplicity of the writing. One highlight that helps to transform the book into something more than a true reference manual is the advice and sampling tips scattered throughout -- Jo A. Werba * Quarterly Review of Biology * An excellent resource for ecologists, ornithologists, wildlife researchers and environmentalists...and an excellent addition to any librarys collection. -- Kuldeep Kumar * Journal of the Royal Statistical Society: Statistics in Society * Measuring Abundance is an excellent tool for agency and nongovernmental biologists looking to better understand baseline population sizes or develop longterm monitoring programs. Furthermore, for many graduate students, this book may be a useful resource for reviewing and covering a range of methods available to measure abundance. -- Molly McDevitt, The Journal of Wildlife Management

Preface viii
Acknowledgements x
Part I Background
1 Statistical ideas
2(20)
1.1 Sampling
2(1)
1.2 Sample statistics
3(3)
1.3 Common continuous distributions
6(1)
1.4 Common discrete probability distributions
7(4)
1.5 Compound Poisson distributions
11(1)
1.6 Estimation and inference
12(3)
1.7 Types of model
15(1)
1.8 Testing the goodness of fit of a model
16(1)
1.9 AIC and related measures
17(1)
1.10 Quantile-quantile plots
18(4)
Part II Stationary individuals
2 Quadrats and transects
22(29)
2.1 What shape quadrats?
22(1)
2.2 How many quadrats?
23(3)
2.3 Quadrat placement
26(2)
2.4 Forestry sampling
28(5)
2.5 Quadrats for estimating frequency
33(4)
2.6 Nested quadrats
37(4)
2.7 Quadrats for estimating cover
41(8)
2.8 `Variation between and within quadrats'
49(2)
3 Points and lines
51(8)
3.1 The point quadrat frame
51(1)
3.2 Line-intercept sampling (LIS)
51(3)
3.3 Point-count transect sampling
54(5)
4 Distance methods
59(20)
4.1 Spatial patterns
59(1)
4.2 Locations for sampling points
60(1)
4.3 Simple point-to-plant measures
61(1)
4.4 Using the distance to the fcth nearest plant
62(5)
4.5 The point-centred quarter method (PCQM)
67(2)
4.6 Angle-order estimators
69(1)
4.7 Nearest-neighbour distances
70(1)
4.8 Combined point-to-plant and nearest-neighbour measures
71(3)
4.9 Wandering methods
74(2)
4.10 Handling mixtures of species
76(2)
4.11 Recommendations
78(1)
5 Variable sized plots
79(11)
5.1 Variable area transect (VAT)
79(4)
5.2 3P sampling
83(1)
5.3 Bitterlich sampling
83(3)
5.4 Perpendicular distance sampling (PDS)
86(4)
Part III Mobile individuals
6 Quadrats, transects, points, and lines-revisited
90(25)
6.1 Box quadrats
90(1)
6.2 Strip transects
90(2)
6.3 Using frequency to estimate abundance
92(3)
6.4 Point counts (point transects)
95(7)
6.5 Double-observer sampling
102(5)
6.6 Double sampling
107(1)
6.7 Removal sampling
107(8)
7 Capture-recapture methods
115(27)
7.1 Capture-recapture models for a closed population
116(14)
7.2 Capture-recapture models for an open population
130(5)
7.3 Pollock's robust design
135(2)
7.4 Spatial capture-recapture models
137(3)
7.5 Mark-resight estimation
140(2)
8 Distance methods
142(18)
8.1 The underlying idea
142(1)
8.2 Detection functions
143(1)
8.3 Point transects
144(5)
8.4 Using imprecise distance data
149(1)
8.5 Introducing covariates
150(1)
8.6 Multiple species
151(2)
8.7 Sightings of groups
153(1)
8.8 Line transects
153(7)
Part IV Species
9 Species richness
160(15)
9.1 Richness indices
161(1)
9.2 Rarefaction
162(2)
9.3 The dependence of richness on area
164(5)
9.4 Estimating the unobserved
169(4)
9.5 The limitation of using richness as a measure of diversity
173(1)
9.6 An occupation-detection model
173(2)
10 Diversity
175(13)
10.1 Berger-Parker dominance
175(2)
10.2 Shannon entropy
177(1)
10.3 Simpson's index
178(1)
10.4 Effective numbers
178(1)
10.5 Fisher's a
179(2)
10.6 Taking account of differences between species
181(2)
10.7 Measuring /S-diversity
183(5)
11 Species abundance distributions (SADS)
188(7)
11.1 Illustrating abundance distributions
188(2)
11.2 The log-series distribution
190(1)
11.3 Truncated Poisson-lognormal distribution
190(2)
11.4 The gambin model
192(1)
11.5 Testing the goodness of fit of a model to a set of octave counts
193(1)
11.6 Determining the drivers for species abundance distributions
194(1)
12 Other aspects of diversity
195(6)
12.1 Evenness
195(1)
12.2 Similarity and complementarity
196(2)
12.3 Turnover
198(1)
12.4 Rarity
198(3)
Appendix 201(2)
Notes 203(3)
Further reading 206(3)
References 209(13)
Index of Examples 222(1)
General Index 223
Graham Upton is a retired Professor of Applied Statistics with an interest in the natural world. He volunteers on citizen science projects such as the Breeding Bird Survey and other projects run by the British Trust for Ornithology and the Wider Countryside Butterfly Survey. He is author or co-author of eight books, including as lead author of the Oxford Dictionary of Statistics, and has published over 100 papers.