A dynamical model of communities and a new species-abundance distribution

It is known to many field biologists that biosurveys of natural communities tend to produce a J-shaped curve when the numbers of species are plotted against abundance. In other words, when the number of species of abundance k is plotted against k (running from 1 to some large number), the resulting distribution peaks at the lowest abundance, then forms a concave ramp as it approaches zero at the far end of the abundance axis. Does this distribution represent a single formula operating behind the scenes, or does it represent several formulas, appropriate for different types of community? Or does it represent no particular formula at all? The research reported here has three components: (1) The analysis of a new dynamical system that simulates multispecies communities (producing J-curves in the process) and the derivation of the "logistic-J" distribution, as the underlying community equilibrium curve; (2) the summary of a general theory of sampling as a bridge between natural communities and samples of them; (3) the evaluation of extant proposals for species-abundance distributions by application of a general theory of sampling or by cross-comparison via 100 biosurveys randomly selected from the literature.     

Estimating similarity of communities: a parametric approach to spatio‐temporal analysis of species diversity

Several stochastic models with environmental noise generate spatio‐temporal Gaussian fields of log densities for the species in a community. Combinations of such models for many species often lead to lognormal species abundance distributions. In spatio‐temporal analysis it is often realistic to assume that the same species are expected to occur at different times and/or locations because extinctions are rare events. Spatial and temporal β‐diversity can then be analyzed by studying pairs of communities at different times or locations defined by a bivariate lognormal species abundance model in which a single correlation occurs. This correlation, which is a measure of similarity between two communities, can be estimated from samples even if the sampling intensities vary and are unknown, using the bivariate Poisson lognormal distribution. The estimators are approximately unbiased, although each specific correlation may be rather uncertain when the sampling effort is low with only a small fraction of the species represented in the samples. An important characteristic of this community correlation is that it relates to the classical Jaccard‐ or the Sørensen‐indices of similarity based on the number of species present or absent in two communities. However, these indices calculated from samples of species in a community do not necessarily reflect similarity of the communities because the observed number of species depends strongly on the sampling intensities. Thus, we propose that our community correlation should be considered as an alternative to these indices when comparing similarity of communities. We illustrate the application of the correlation method by computing the similarity between temperate bird communities.     

Species abundance distributions and numerical dominance in gastrointestinal helminth communities of fish hosts

The abundances of different species in a parasite community are never similar: there is typically one or a few numerically dominant species and many species with low abundance. Here, we determine whether basic features of parasite communities are associated with strong dominance by one or a few species, among 39 component communities of gastrointestinal helminths in marine fishes from Brazil. First, we tested whether the shape of the species abundance distribution in these communities fits that predicted by several theoretical models, using a goodness-of-fit procedure. Only the canonical lognormal model could be rejected for 5 out of 39 communities; all other comparisons of observed and predicted abundance distributions showed no significant differences, although this may be due to limited statistical power. Second, we used the ratio between the abundance of the most abundant species and either the second or third most abundant species, as indices of dominance; these show, for instance, that the dominant species in a community is typically twice, but sometimes over ten times, as abundant as the next most abundant species. We found that these ratios were not influenced by either the community's species richness, the mean number of individual parasites per host, or the taxonomic identity of the dominant species. However, the abundance ratio between the first and third most abundant species in a community was significantly correlated with an independent index of species interactivity, based on the likelihood that the different parasite species in a component community co-occur in the same host individuals: the difference in abundance between the dominant and third most abundant species was greater in communities characterized by weak interactions. These findings suggest that strong interactions may lead to greater evenness in the abundance of species, and that numerical dominance is more likely to result from interspecific differences in recruitment rates.     

Heterogeneous communities with lognormal species abundance distribution: Species-area curves and sustainability

Heterogeneous species abundance models are models in which the dynamics differ between species, described by variation among parameters defining the dynamics. Using a dynamic and heterogeneous species abundance model generating the lognormal species abundance distribution it is first shown that different degrees of heterogeneity may result in equivalent species abundance distributions. An alternative to Preston's canonical lognormal model is defined by assuming that reduction in resources, for example reduction in available area, increases the density regulation of each species. This leads to species-individual curves and species-area curves that are approximately linear in a double logarithmic plot. Preston's canonical parameter gamma varies little along these curves and takes values in the neighborhood of one. Quite remarkably, the curves, which define the sensitivity of the community to area reductions, are independent of the heterogeneity among species for this model. As a consequence, the curves can be estimated from a single sample from the community using the Poisson lognormal distribution. It is shown how to perform sensitivity analysis with respect to over-dispersion in sampling relative to the Poisson distribution as well as sampling intensity, that is, the fraction of the community sampled. The method is exemplified by analyzing three simulated data sets.     

A comparative analysis of alternative approaches to fitting species-abundance models

Aims Fits of species-abundance distributions to empirical data are increasingly used to evaluate models of diversity maintenance and community structure and to infer properties of communities, such as species richness. Two distributions predicted by several models are the Poisson lognormal (PLN) and the negative binomial (NB) distribution; however, at least three different ways to parameterize the PLN have been proposed, which differ in whether unobserved species contribute to the likelihood and in whether the likelihood is conditional upon the total number of individuals in the sample. Each of these has an analogue for the NB. Here, we propose a new formulation of the PLN and NB that includes the number of unobserved species as one of the estimated parameters. We investigate the performance of parameter estimates obtained from this reformulation, as well as the existing alternatives, for drawing inferences about the shape of species abundance distributions and estimation of species richness.Methods We simulate the random sampling of a fixed number of individuals from lognormal and gamma community relative abundance distributions, using a previously developed 'individual-based' bootstrap algorithm. We use a range of sample sizes, community species richness levels and shape parameters for the species abundance distributions that span much of the realistic range for empirical data, generating 1?000 simulated data sets for each parameter combination. We then fit each of the alternative likelihoods to each of the simulated data sets, and we assess the bias, sampling variance and estimation error for each method.Important findings Parameter estimates behave reasonably well for most parameter values, exhibiting modest levels of median error. However, for the NB, median error becomes extremely large as the NB approaches either of two limiting cases. For both the NB and PLN,>90% of the variation in the error in model parameters across parameter sets is explained by three quantities that corresponded to the proportion of species not observed in the sample, the expected number of species observed in the sample and the discrepancy between the true NB or PLN distribution and a Poisson distribution with the same mean. There are relatively few systematic differences between the four alternative likelihoods. In particular, failing to condition the likelihood on the total sample sizes does not appear to systematically increase the bias in parameter estimates. Indeed, overall, the classical likelihood performs slightly better than the alternatives. However, our reparameterized likelihood, for which species richness is a fitted parameter, has important advantages over existing approaches for estimating species richness from fitted species-abundance models.     

Competition and species diversity: removal of dominant species increases diversity in Costa Rican butterfly communities

Biological communities are usually dominated by a few species and show characteristically skewed species abundance distributions. Although niche apportionment and resource competition are sometimes implicated in such patterns, few experimental studies have shown direct links between resource limitation, competition with dominant species and their impacts on the overall diversity and composition of large natural communities. Here I report the results of an experiment in which I first studied species diversity and composition in two Costa Rican nectar-feeding butterfly communities numerically dominated by two species of Anartia butterflies. Then I removed Anartia from these communities to study changes in resource availability, species abundance relationships, community diversity and composition as an outcome of the removal of the dominant competitors. In the face of competition with Anartia , nectar was scarce, species abundance distributions were highly skewed, and species diversity was low in both communities. Within two weeks after the removal of Anartia , there were parallel changes in both communities: competition for nectar reduced and the nectar quantity increased substantially, which facilitated increase in community diversity and resulted in significantly less skewed species abundance distributions. Higher nectar quantity also enabled the distribution of body size and proboscis length of constituent species in the communities to expand at both ends. This study thus experimentally showed that resource competition with the dominant species was excluding many species from the communities, lowering their diversity and skewing relative species abundance relationships. These findings are of fundamental importance for competition theory and community ecology because they indicate ways in which diverse communities may be affected by and recover from competition with dominant species.     

长江口潮下带春季大型底栖动物的群落结构

2005年4月对长江口全区域潮下带共10个采样站位的大型底栖动物进行了调查。调查采获大型底栖动物38种,分属5个生态类型,种类数较少,河口外缘站位种类数多于口内站位。各站位大型底栖动物的平均丰度为32.9个/m2、平均生物量为5.035g/m2(湿重);与20世纪七八十年代相比,平均生物量显著降低;口外缘站位的总丰度和总生物量均高于口内站位。环境因子相关分析表明,盐度是决定长江口大型底栖动物种类分布最重要的环境因子。群落聚类、标序分析显示,春季长江口潮下带大型底栖动物群落结构空间分异明显,完全符合目前长江口支、港、槽“三级分汊”的空间格局。其中,北支的大型底栖动物以混合高盐水种类为主,而南支则以淡水和半咸水种类为主。南支的南北槽分界处内外站位的群落差异也由盐度决定,因为靠近口内的群落均受长江冲淡水影响较大;而口外站位群落则受咸淡水影响。南支的南北港分界点内外的群落差异则主要受长江来水的影响,原因在于处在港分界点以内的群落所在区域,直接受长江来水的冲刷,底质环境极不稳定;而港、槽分界点之间的群落所在区域由于河口上段的诸多明暗沙体的阻挡,水势较为稳定,所以底质环境较稳定,从而使得港、槽分界点之间的群落出现了更多的沙蚕等底质环境类型种类。     

Interpreting ecological diversity indices applied to terminal restriction fragment length polymorphism data: insights from simulated microbial communities

Ecological diversity indices are frequently applied to molecular profiling methods, such as terminal restriction fragment length polymorphism (T-RFLP), in order to compare diversity among microbial communities. We performed simulations to determine whether diversity indices calculated from T-RFLP profiles could reflect the true diversity of the underlying communities despite potential analytical artifacts. These include multiple taxa generating the same terminal restriction fragment (TRF) and rare TRFs being excluded by a relative abundance (fluorescence) threshold. True community diversity was simulated using the lognormal species abundance distribution. Simulated T-RFLP profiles were generated by assigning each species a TRF size based on an empirical or modeled TRF size distribution. With a typical threshold (1%), the only consistently useful relationship was between Smith and Wilson evenness applied to T-RFLP data (TRF-E(var)) and true Shannon diversity (H'), with correlations between 0.71 and 0.81. TRF-H' and true H' were well correlated in the simulations using the lowest number of species, but this correlation declined substantially in simulations using greater numbers of species, to the point where TRF-H' cannot be considered a useful statistic. The relationships between TRF diversity indices and true indices were sensitive to the relative abundance threshold, with greatly improved correlations observed using a 0.1% threshold, which was investigated for comparative purposes but is not possible to consistently achieve with current technology. In general, the use of diversity indices on T-RFLP data provides inaccurate estimates of true diversity in microbial communities (with the possible exception of TRF-E(var)). We suggest that, where significant differences in T-RFLP diversity indices were found in previous work, these should be reinterpreted as a reflection of differences in community composition rather than a true difference in community diversity.     

Extinction cascades and the distribution of species interactions

The distribution of interaction strengths among community members has important consequences for assembly processes and community responses to perturbations. Species deletion from communities can trigger cascading extinction events, with strong evidence from empirical and theoretical work. I examined model competitive communities, sequentially assembled using species drawn from a global pool with interaction strengths described by different distribution shapes (uniform or beta), with the same mean and variance. As community size increased, it became harder to assemble communities drawn from a uniform distribution compared to a beta distribution. The distribution of interaction values in the assembled communities differed from the shape of the initial distribution. The distribution shape and the relative abundance of the deleted species also had strong impacts on the probability of extinction cascades following primary species removal. Extinction cascades occurred in communities with a higher mean and variance of interaction strengths before the primary extinction. Those species lost had negative equilibrium densities and tended to be the least abundant, when assessed following the reorganisation that occurred after the primary and subsequent extinctions. Knowledge of the shape of the distribution of interaction strengths from real communities will allow us to make better predictions about which species are most at risk in extinction cascades under natural circumstances.     

Quantifying functional gene populations: comparing gene abundance and corresponding enzymatic activity using denitrification and nitrogen fixation in pulp and paper mill effluent treatment systems.

The relationship between the abundance of three functional genes and their corresponding biochemical reaction rates was investigated in several activated sludge and mill effluent microbial communities. Gene probes were prepared for two key denitrification genes (nirS and nirK) and for one nitrogen-fixation gene (nifH) and were validated using a variety of strains of known nir and nif genotype. ATP-based measures of viable cell numbers were used to provide total population sizes. In certain microbial communities (activated sludge enrichment cultures and multiple samples taken from the same mill primary clarifier), a strong correlation was observed between gene abundance and biochemical activity rates. However, when comparing several different nonenriched activated sludge bioreactors and separate primary clarifier microbial communities, the ratio of specific gene abundance to biochemical activity rates varied widely. These results suggest that in cases where a microbial community is not fully induced for a given biochemical activity or when very different communities are compared, quantitative gene probing can give a better measure of a community's potential to carry out the encoded function than can the relevant biochemical assay. However, the gene quantitation method employed here probably underestimated the true number of probed genes present in the microbial communities due to nirS and nifH genes in the communities having reduced DNA sequence similarity with the probes used.     

Robust estimation of microbial diversity in theory and in practice

Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao''s estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics (‘Hill diversities''), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao''s estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.     

Fish Species and Community Distributions as Proxies for Seafloor Habitat Distributions: The Stellwagen Bank National Marine Sanctuary Example (Northwest Atlantic, Gulf Of Maine)

Defining the habitats of fishes and associated fauna on outer continental shelves is problematic given the paucity of data on the actual types and distributions of seafloor habitats. However many regions have good data on the distributions of fishes from resource surveys or catch statistics because of the economic importance of the fisheries. Fish distribution data (species or communities) have been used as a proxy for the distribution of habitats to develop precautionary conservation strategies for habitat protection (e.g., marine protected areas, fishing gear restrictions). In this study we assessed the relationships between the distributions of fish communities and species derived from trawl survey data with the spatial distribution of sediment types determined by sampling and acoustic reflectance derived from multibeam sonar surveys in Stellwagen Bank National Marine Sanctuary. Fish communities were correlated with reflectance values but all communities did not occur in unique sediment types. This suggests that use of community distributions as proxies for habitats should include the caveat that a greater number of communities within an area could indicate a greater range of habitat types. Single species distributions showed relationships between abundance and reflectance values. Trawl catches with low abundances had wide variations in reflectance values while those with high abundances had narrower ranges indicating habitat affinities. Significant non-random frequency-dependent relationships were observed for 17 of 20 species although only 12 of 20 species had significant relationships based on rank correlation. These results suggest that species distributions based on trawl survey data can be used as proxies for the distribution of seafloor habitats. Species with known habitat associations can be used to infer habitat requirements of co-occurring species and can be used to identify a range of habitat types.     

A statistical theory for sampling species abundances

The pattern of species abundances is central to ecology. But direct measurements of species abundances at ecologically relevant scales are typically unfeasible. This limitation has motivated a long-standing interest in the relationship between the abundance distribution in a large, regional community and the distribution observed in a small sample from the community. Here, we develop a statistical sampling theory to describe how observed patterns of species abundances are influenced by the spatial distributions of populations. For a wide range of regional-scale abundance distributions we derive exact expressions for the sampled abundance distributions, as a function of sample size and the degree of conspecific spatial aggregation. We show that if populations are randomly distributed in space then the sampled and regional-scale species-abundance distribution typically have the same functional form: sampling can be expressed by a simple scaling relationship. In the case of aggregated spatial distributions, however, the shape of a sampled species-abundance distribution diverges from the regional-scale distribution. Conspecific aggregation results in sampled distributions that are skewed towards both rare and common species. We discuss our findings in light of recent results from neutral community theory, and in the context of estimating biodiversity.     

Limited versus unlimited membership in microbial communities: evaluation and experimental tests of some paradigms

Recent developments in community ecology have allowed for the synthesis of community models based on principles of limited and unlimited membership. In this discussion, these developments are used as a framework for evaluating the validity of three paradigms that have constrained research on aquatic microbial communities. Because microbes are considered to possess global distributions, species availability is not generally considered to be an important factor determining microbial community composition in most habitats. Requirements for the global distribution of a species are not the same as those for unlimited availability. Rates of propagule transport to isolated and newly formed aquatic systems ( 4 years old) are low enough to have a strong effect on microbial community composition. Natural aquatic systems may require several years to accumulate a full complement of species adapted to environmental conditions at a particular time. Except under extreme circumstances, environmental conditions are not considered to constrain membership in aquatic microbial communities. Most evidence for this contention is based on an inability to detect simple relationships between species distributions and levels of individual environmental parameters. Environmental measurements are often made at a spatial scale much greater than that of the local environment of microbes. Biotic interactions, such as competition, are generally considered to be the predominant force structuring aquatic microbial communities. Although there is an extensive laboratory database to suggest the importance of different types of species interactions, there have been few field studies to confirm this. A general research protocol is described to test predictions derived from current theory of microbial community organization. A mesocosm approach is advocated in order to incorporate crucial aspects of environmental realism into experimental designs while maintaining some of the control found in the laboratory.     

Species diversity in vertical, horizontal, and temporal dimensions of a fruit-feeding butterfly community in an Ecuadorian rainforest

To test the hypotheses that fruit-feeding nymphalid butterflies are randomly distributed in space and time, a community of fruit-feeding nymphalid butterflies was sampled at monthly intervals for one year by trapping 6690 individuals of 130 species in the canopy and understory of four forest habitats: primary, higraded, secondary, and edge. The overall species abundance distribution was well described by a lognormal distribution. Total species diversity (γ-diversity) was partitioned into additive components within and among community subdivisions (α-diversity and β-diversity) in vertical, horizontal and temporal dimensions. Although community subdivisions showed high similarity (1 —β-diversity/γ-diversity), significant β-diversity existed in each dimension. Individual abundance and observed species richness was lower in the canopy than in the understory. However, rarefaction analysis and species accumulation curves revealed that canopy had higher species richness than understory. Observed species richness was roughly equal in all habitats, but individual abundance was much greater in edge, largely due to a single, specialist species. Rarefaction analysis and species accumulation curves showed that edge had significantly lower species richness than all other habitats. Samples from a single habitat, height and time contained only a small fraction of the total community species richness. This study demonstrates the feasibility, and necessity, of large-scale, long-term sampling in multiple dimensions for accurately measuring species richness and diversity in tropical forest communities. We discuss the importance of such studies in conservation biology.     

盐城滨海滩涂湿地典型植物群落土壤微生物组成与结构特征

土壤微生物是生态系统维持正常结构与功能的重要组成部分,为探究盐城滩涂典型湿地土壤微生物群落结构特征,以江苏盐城滩涂互花米草、藨草、盐地碱蓬、芦苇及淤泥质光滩5种典型群落为对象,采用16S rRNA高通量测序技术分析0—10 cm(表层)、10—30 cm(中层)、30—60 cm(深层)土壤微生物多样性及群落结构。结果表明：(1)几种植物群落间,土壤微生物群落结构差异较大,主要体现在细菌群落结构的差异性,古菌群落结构差异相对较小。光滩与植物群落间,在土壤细菌种类及相对丰度上差异相对较大,互花米草群落与本土植物群落间,在微生物群落的细菌种类组成上存在较大差异;藨草群落土壤表层微生物群落结构与互花米草群落相似,深层与盐地碱蓬、芦苇群落相似。(2)同一群落不同层次土壤微生物群落结构相似,差异小于不同群落间土壤微生物群落的结构差异性;不同群落对应层次间,表深层土壤中五种群落土壤微生物多样性存在显著差异,中层土壤中五种群落微生物多样性差异不显著。总体上,植物群落类型对土壤微生物群落结构的影响大于土壤深度;与本土植物群落相比,互花米草群落土壤主要优势门微生物种类差异较小,但部分优势门微生物相对丰度...     

Relating species abundance distributions to species-area curves in two Mediterranean-type shrublands

Abstract. Based on both theoretical and empirical studies there is evidence that different species abundance distributions underlie different species‐area relationships. Here I show that Australian and Californian shrubland communities (at the scale from 1 to 1000 m²) exhibit different species‐area relationships and different species abundance patterns. The species‐area relationship in Australian heathlands best fits an exponential model and species abundance (based on both density and cover) follows a narrow log normal distribution. In contrast, the species‐area relationship in Californian shrublands is best fit with the power model and, although species abundance appears to fit a log normal distribution, the distribution is much broader than in Australian heathlands. I hypothesize that the primary driver of these differences is the abundance of small‐stature annual species in California and the lack of annuals in Australian heathlands. Species‐area is best fit by an exponential model in Australian heathlands because the bulk of the species are common and thus the species‐area curves initially rise rapidly between 1 and 100 m². Annuals in Californian shrublands generate very broad species abundance distributions with many uncommon or rare species. The power function is a better model in these communities because richness increases slowly from 1 to 100 m² but more rapidly between 100 and 1000 m² due to the abundance of rare or uncommon species that are more likely to be encountered at coarser spatial scales. The implications of this study are that both the exponential and power function models are legitimate representations of species‐area relationships in different plant communities. Also, structural differences in community organization, arising from different species abundance distributions, may lead to different species‐area curves, and this may be tied to patterns of life form distribution.     

Measuring soil microbial community diversity using polar lipid fatty acid and denaturing gradient gel electrophoresis data

The possibility of calculating useful microbial community diversity indices from environmental polar lipid fatty acid and 16S rDNA PCR-DGGE data was investigated. First, the behavior of the species richness, Shannon's, and Simpson's diversity indices were determined on polar lipid fatty acid profiles of 115 pure cultures, communities constructed from those profiles with different numbers of species, and constructed communities with different distributions of species. Differences in the species richness of these artificial communities was detected by all three diversity indices, but they were insensitive to the evenness of the distribution of species. Second, data from a field experiment with substrate addition to soil was used to compare the methods developed for lipid- and DNA-based diversity indices. Very good agreement was found between indices calculated from environmental polar lipid fatty acid profiles and denaturing gradient gel electrophoresis profiles from matched samples (Pearson's correlation coefficient r=0.95-0.96). A method for data pre-treatment for diversity calculations is described.     

Modeling Taxa-Abundance Distributions in Microbial Communities using Environmental Sequence Data

We show that inferring the taxa-abundance distribution of a microbial community from small environmental samples alone is difficult. The difficulty stems from the disparity in scale between the number of genetic sequences that can be characterized and the number of individuals in communities that microbial ecologists aspire to describe. One solution is to calibrate and validate a mathematical model of microbial community assembly using the small samples and use the model to extrapolate to the taxa-abundance distribution for the population that is deemed to constitute a community. We demonstrate this approach by using a simple neutral community assembly model in which random immigrations, births, and deaths determine the relative abundance of taxa in a community. In doing so, we further develop a neutral theory to produce a taxa-abundance distribution for large communities that are typical of microbial communities. In addition, we highlight that the sampling uncertainties conspire to make the immigration rate calibrated on the basis of small samples very much higher than the true immigration rate. This scale dependence of model parameters is not unique to neutral theories; it is a generic problem in ecology that is particularly acute in microbial ecology. We argue that to overcome this, so that microbial ecologists can characterize large microbial communities from small samples, mathematical models that encapsulate sampling effects are required.