The species–abundance distribution (SAD) describes the abundances of all species within a community. Many different models have been proposed to describe observed SADs. Best known are the logseries, the lognormal, and a variety of niche division models. They are most often visualized using either species richness – log abundance class (Preston) plots or abundance – species rank order (Whittaker) plots. Because many of the models predict very similar shapes, model distinction and testing become problematic. However, the variety of models can be classified into three basic types: one that predicts a double S‐shape in Whittaker plots and a unimodal distribution in Preston plots (the lognormal type), a second that lacks the mode in Preston plots (the logseries type), and a third that predicts power functions in both plotting types (the power law type). Despite the interest of ecologists in SADs no formal meta‐analysis of models and plotting types has been undertaken so far. Here we use a compilation of 558 species–abundance distributions from 306 published papers to infer the frequency of the three SAD shapes in dependence of environmental variables and type of plotting. Our results highlight the importance of distinguishing between fully censused and incompletely sampled communities in the study of SADs. We show that completely censused terrestrial or freshwater animal communities tend to follow lognormal type SADs more often than logseries or power law types irrespective of species richness, spatial scale, and geographic position. However, marine communities tend to follow the logseries type, while plant communities tend to follow the power law. In incomplete sets the power law fitted best in Whittaker plots, and the logseries in Preston plots. Finally our study favors the use of Whittaker over Preston plots.

Recently, three different models have been proposed to explain the distribution of abundances in natural communities: the self-similarity model; the zero-sum ecological drift model; and the occasional-frequent species model of Magurran and Henderson. Here we study patterns of relative abundance in a large community of forest Hymenoptera and show that it is indeed possible to divide the community into a group of frequent species and a group of occasional species. In accordance with the third model, frequent species followed a lognormal distribution. Relative abundances of the occasional species could be described by the self-similarity model, but did not follow a log-series as proposed by the occasional-frequent model. The zero-sum ecological drift model makes no explicit predictions about frequent and occasional species but the abundance distributions of the hymenopteran species did not show the excess of rare species predicted by this model. Separate fits of this model to the frequent and to the occasional species were worse than the respective fits of the lognormal and the self-similarity model.

The present study demonstrates the possibility of estimating species numbers of animal or plant communities from samples using relative abundance distributions. We use log-abundance-species-rank order plots and derive two new estimators that are based on log-series and lognormal distributions. At small to moderate sample sizes these estimators appear to be more precise than previous parametric and nonparametric estimators. We test our estimators using samples from 171 published medium-sized to large animal and plant communities taken from the literature. By this we show that our new estimators define also limits of precision.

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The chemical characteristics of the surface sediment (0-5 cm) in a lake which formed in an opencast sulphur mine in Southern Poland have been analysed. Generally, the concentration of major elements (N, P, S, Ca, K, Mg, Cl, Fe, Si, and Al) and trace elements (Ag, As, Ba, Cd, Co, Cr, Cu, Ga, Hg, I, Mn, Mo, Ni, Pb, Rb, Sr, Ti, Y, and Zn) in the lake sediment reflected the natural regional background. The sediment was characterised by low amounts of organic matter (LOI ca. 5%). MANOVA indicated that the concentrations of 60% of the elements differed significantly between transects and 32% with respect to depths, whereas seasonal differentiations were not found. The relationships between the studied elements calculated using factor analysis and correlation matrix are discussed. The bottom sediment show considerable heterogeneity, which is probably connected to their allochthonous origins and the young age of the lake.