Introduction to the study of meiofauna

I. Summary Despite the fact that a substantial research effort has been directed at the analysis of species abundance patterns over the years, there are many important issues which are not sufficiently explored and understood. This review examines the conceptual and methodological frameworks of analysis in species abundance patterns, with particular emphasis on interpreting patterns in the context of community structure and organization. Historically, this discipline underwent a largely monotonous pattern of development (Section III) in that successive researchers proposed different models which were often claimed to be superior to those previously proposed, followed by seemingly piecemeal analyses of empirical data with reference to a particular model. This has resulted in a conspicuous lack of broad perspective in the study of species abundance patterns, despite a number of reviews produced. In the first place, therefore, it is important to clarify the conceptual basis of analysing species abundance patterns, including the definition of community and sample to which different models inevitably refer (Section IV). Basic characteristics of species abundance models proposed to date are briefly reviewed and recommendations for standardizing the presentation of rank-abundance graphs are given. In the context of unravelling community structure, the concept of niche is highly relevant in the analysis of species abundance patterns (Section V). Thus particular attention is given to the development of niche-oriented models with a consideration of the relationship between resource and species abundance. Furthermore, with respect to the question of how total energy or resource is divided among species in a community, the current debated issue of density-body size allometry is reviewed. Interpretation of models and patterns is a major problem in this discipline (Section VI). It is recognized that models, particularly niche-oriented ones, are useful in suggesting possibilities underlying community organization. Thus they should be regarded as an aid for interpreting patterns rather than as a precise and rigid description of mechanisms involved. Consideration is given to some important dichotomies including global versus community-specific patterns, contemporary versus evolutionary processes, species- versus process-oriented interpretation and equilibrium versus non-equilibrium communities. Apart from problems associated with interpretation, there are practical problems of testing models (Section VII). Despite empirical studies in the past, this is again a neglected area, and particular difficulties arise with stochastic species abundance models. As a way forward, a simulation method of testing stochastic-type models is introduced and the importance of making replicated observations is emphasized. Section VIII deals with topics which are closely related to the analysis of species abundance patterns, namely diversity indices, species-area relationships and application to environmental assessment. Section IX identifies aspects to be considered in future investigations and emphasizes the importance of spatial/temporal variability and of integrating the analysis of species abundance patterns and other analyses of community structure, whether observational, experimental or analytical, in order to achieve a better understanding of ecological communities.

Species Abundance Patterns and Community Structure

An overview is given of the different indices used, since their introduction in the 60's, for the determination of diversity in biological samples and communities. The most commonly used indices are based on the estimation of relative abundance of species in samples. Relative abundance can also be used for either a graphical or a mathematical representation of species-abundance relationships, from which diversity indices can be deduced as well. Most common in the literature are indices either describing the richness or species number and the evenness or partitioning of individuals over species or a combination of both. The most commonly used diversity indices can be grouped in a coherent system of diversity numbers developed by HILL (1973) that includes species richness, the Simpson index and a derivation of the Shannon-Wiener index as special cases. In this system species are different only when their abundance is different. Therefore, during the last decade a number of indices have been developed that take into account the taxonomic position, trophic status or body size of the species. There is as yet no consensus as to the use of evenness indices. We apply the condition that evenness should be independent of species richness (HElP, 1974). The number of potential evenness indices is then strongly reduced. It is *These lecture notes are in part an update of the paper "Data Processing, Evaluation and Analysis". Carlo Heip, Peter Herman & Karlien Soetaert, 1988. In: Introduction to the Study of Meiofauna (R.P. Higgins & H. Thiel eds). Smithsonian Institution Press, Washington D.C., London. Publication nr 2459 of the Netherlands Institute of Ecology.

/pdf/indices-of-diversity-and-evenness-cy8ehdfy36.pdf

Indices of diversity and evenness

Distribution of species along pollution-induced diversity gradients in benthic communities in Norwegian fjords

Summary
1.Environmental heterogeneity influences biodiversity patterns such as species richness and community composition, but we do not know how it shapes community structure in terms of the number of rare and abundant species. This question is particularly relevant to modified landscapes such as agro-ecosystems, where intensive management creates highly homogeneous landscapes,
which often lead to loss of rare taxa and dominance by a few aggressive species.
2. It can be difficult to evaluate the effects of management on communities in different localities
due to regional differences in species richness and composition. Because species abundance distributions
(SADs) express assemblage structure in comparable units, they can be used to characterize communities irrespective of species composition, and for this reason provide a novel means of assessing the effects of management.
3. We analysed the SADs of weed communities across a gradient of environmental heterogeneity generated by different management treatments. We tested the hypothesis that environmental heterogeneity promotes multimodality in SADs by comparing observed patterns with those
predicted for simulated random samples from homogeneous communities.
4. Observed SADs from a homogeneous environment did not deviate from predictions. By contrast, SADs from increasingly heterogeneous environments were progressively and consistently multimodal.
5. These results demonstrate that environmental heterogeneity, resulting from variation in management treatments, leaves a signature on the SAD.
6. Synthesis and applications.
Our study shows that Species Abundance Distributions are informative indicators of environmental heterogeneity in modified landscapes. Weed communities include
both rare species, which are often of conservation interest and pose little threat to crops, and abundant species, which can be problematic. Our analysis suggests that creating environmental heterogeneity by varying management treatments across the landscape can be an effective way of
promoting biodiversity and decreasing the abundance of problematic species.

https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2664.2009.01640.x

Species abundance distributions reveal environmental heterogeneity in modified landscapes

In contrast to Shaw et al. (1983) I believe the lognormal distribution of individuals among species is an adequate description of most benthic communities, given that no community should ever be expected to be in complete equilibrium and give a perfect fit. Under organic enrichment departures from a log-normal distribution have been shown to give a consistent pattern and are not highly confusing as Shaw et a l , contend. The trends must be treated cautiously however, since pollution is not the only factor leading to a lack-of-fit to a log-normal. In the preceding paper, Shaw et al. (1983) suggest that (1) there is little evidence to substantiate the belief that benthic marine communities fit the log-normal distribution of individuals among species; (2) the plotting method of detecting deviation from a log-normal distribution is of dubious value; (3) a simple dominance index is a more practical method of assessing pollution induced changes. In attempting to refute the generality of the lognormal distribution Shaw et al. (1983) use data from Gray and Mirza (1979) and to this plot a log-normal line which they claim has the same standard deviation and mean as the data. The log-normal is not a singlefixed distribution, and for a given number of species and individuals there are many possible log-normal distributions. If one transforms their data (their Fig. 3) to probits and fits a linear regression, the line obtained (R2 = 0.934) is I submit, a good fit to a log-normal as claimed in our original paper. Shaw et al.'s plot clearly has divergent mean (50 % point) and standard deviation (84 % to 50 % points) than our data, and bears little relation to the data. I believe this evidence shows that Station A in Oslofjord does fit the log-normal (Fig. l ) . The original model fitted to the distribution of individuals among species was R. A. Fisher's log-series which is characterized by having the highest number of species in the class with 1 individual per species. Later it was found that more usually the class with 2 to O Inter-Research/Printed in F. R. Germany 3 individuals per species was the dominant class and a new model, the log-normal distribution, was derived by Preston (1948). Yet if the sample is not large the mode will often lie in the l-individual-per-species class (a log series) but as the sample size is increased the mode moves along to the 2 to 3 individual class or higher giving a log-normal. Preston (1962) has an excellent example showing this when sample size was increased from 3 mo data to 6 mo to 12 mo. Thus the

/pdf/use-and-misuse-of-the-log-normal-plotting-method-for-31hsbjonej.pdf

Use and misuse of the log-normal plotting method for detection of effects of pollution - a reply to Shaw et al. (1983)

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Use and misuse of the log-normal plotting method for detection of effects of pollution - a reply to Shaw et al. (1983)