Stochastic abundance models, with emphasis on biological communities and species diversity

I: Theoretical Treatement.- 1. Introduction.- 1.1 Abundance models.- 1.2 Some distributions used in the statistical analysis of abundance and diversity.- 1.3 Description of fixed populations.- 1.4 Description of random populations.- 2. Sampling from a Population of Classes.- 2.1 Introduction.- 2.2 The limitation of inference drawn from one sample.- 2.3 Sampling from a finite population.- 2.4 Sampling from an infinite population.- 2.5 Quadrat sampling : presence absence data.- 2.6 Species-area curves.- 2.7 Good's (empirical) Bayesian approach.- 3. Abundance Models.- 3.1 General introduction.- 3.2 Maximum liklihood theory applied to symmetric models.- 3.3 Fisher's logarithmic series model.- 3.4 The negative binomial model.- 3.5 The geometric series model.- 3.6 The Poisson lognormal model.- 3.7 Zipf's model.- 3.8 Some other models.- 3.9 Some concluding remarks.- 4. Sample Coverage.- 4.1 Introduction.- 4.2 Finite populations.- 4.3 Infinite populations.- 4.4 Some results for the negative binomial model.- 5. Indices of Diversity and Equitability.- 5.1 Introduction.- 5.2 Finite populations.- 5.3 Infinite populations.- 5.4 Parameter transformation.- II: Ecological Applications.- 6. Abundance Models in Ecology.- 6.1 Introduction.- 6.2 Some historical remarks.- 6.3 Interpretations of fixed and random models in ecology.- 6.4 The stability of population parameters.- 7. Abundance Models in Ecology-Examples.- 7.1 Discussion of assumptions.- 7.2 Judging goodness of fit.- 7.3 Quadrat sampling.- 7.4 Higher order classification.- 7.5 Species diversity of chironomid communities- an example.- References.- Appendix A: The Structural Distribution for the Model dealt with in Example 2.4.- Appendix B: Tables.- Author Index.