Body size and measurement of species diversity in large grazing mammals

Species are by definition different from each other. This fact favours ranking rather than additive indices. However, ecologists have measured species diversity in terms of species richness, or by combining species richness with the relative abundance of species within an area. Both methods raise problems: species richness treats all species equally, while relative abundance is not a fixed property of species but varies widely temporally and spatially, and requires a massive sampling effort. The functional aspect of species diversity measurement may be strengthened by incorporating differences between species such as body size as a component of diversity. An index of diversity derived from a measure of variation in body size among species is proposed for large grazing mammals. The proposed diversity index related positively to species abundance, indicating that the use of body size as a surrogate for diversity is adequate. Because the proposed index is based on presence or absence data, the expensive and time consuming counting of individuals per species in each sampling unit is not necessary.     

Nonparametric Lower Bounds for Species Richness and Shared Species Richness under Sampling without Replacement

Summary A number of species richness estimators have been developed under the model that individuals (or sampling units) are sampled with replacement. However, if sampling is done without replacement so that no sampled unit can be repeatedly observed, then the traditional estimators for sampling with replacement tend to overestimate richness for relatively high-sampling fractions (ratio of sample size to the total number of sampling units) and do not converge to the true species richness when the sampling fraction approaches one. Based on abundance data or replicated incidence data, we propose a nonparametric lower bound for species richness in a single community and also a lower bound for the number of species shared by multiple communities. Our proposed lower bounds are derived under very general sampling models. They are universally valid for all types of species abundance distributions and species detection probabilities. For abundance data, individuals' detectabilities are allowed to be heterogeneous among species. For replicated incidence data, the selected sampling units (e.g., quadrats) need not be fully censused and species can be spatially aggregated. All bounds converge correctly to the true parameters when the sampling fraction approaches one. Real data sets are used for illustration. We also test the proposed bounds by using subsamples generated from large real surveys or censuses, and their performance is compared with that of some previous estimators.     

Accounting for imperfect detection of groups and individuals when estimating abundance

If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities <1. Common estimators include double‐observer models, distance sampling models and combined double‐observer and distance sampling models (known as mark‐recapture‐distance‐sampling models; MRDS). When animals reside in groups, however, the assumption of independent detection is violated. In this case, the standard approach is to account for imperfect detection of groups, while assuming that individuals within groups are detected perfectly. However, this assumption is often unsupported. We introduce an abundance estimator for grouped animals when detection of groups is imperfect and group size may be under‐counted, but not over‐counted. The estimator combines an MRDS model with an N‐mixture model to account for imperfect detection of individuals. The new MRDS‐Nmix model requires the same data as an MRDS model (independent detection histories, an estimate of distance to transect, and an estimate of group size), plus a second estimate of group size provided by the second observer. We extend the model to situations in which detection of individuals within groups declines with distance. We simulated 12 data sets and used Bayesian methods to compare the performance of the new MRDS‐Nmix model to an MRDS model. Abundance estimates generated by the MRDS‐Nmix model exhibited minimal bias and nominal coverage levels. In contrast, MRDS abundance estimates were biased low and exhibited poor coverage. Many species of conservation interest reside in groups and could benefit from an estimator that better accounts for imperfect detection. Furthermore, the ability to relax the assumption of perfect detection of individuals within detected groups may allow surveyors to re‐allocate resources toward detection of new groups instead of extensive surveys of known groups. We believe the proposed estimator is feasible because the only additional field data required are a second estimate of group size.     

吉林蛟河阔叶红松林物种多度分布模型研究

以吉林蛟河阔叶红松林的木本植物为研究对象,将30hm²的样地面积划分为5m×5m,10m×10m,20m×20m,25m×25m的连续取样单元,在4个不同尺度下分别统计各物种在每个取样单元中的有无,得到每个物种在不同尺度下的取样单元数。利用随机分布模型和负二项分布模型分析物种的多度分布,对比预测多度与观测多度讨论两个模型的科学性与实用性。结果表明：对于阔叶红松林而言,负二项分布模型在所有研究尺度上的预测精度都要优于随机分布模型。随机分布和负二项分布的模型预测误差随着研究尺度的增大而增大,因此选取较小的取样单元可以切实提高物种多度的预测精度。利用随机分布和负二项分布模型对多度较小的物种进行预测的效果要优于多度较大的物种。负二项分布模型适合用来模拟阔叶红松林的物种多度分布格局,并且模型的拟合效果受取样单元大小影响。     

Combining counts and incidence data: an efficient approach for estimating the log-normal species abundance distribution and diversity indices

Obtaining accurate estimates of diversity indices is difficult because the number of species encountered in a sample increases with sampling intensity. We introduce a novel method that requires that the presence of species in a sample to be assessed while the counts of the number of individuals per species are only required for just a small part of the sample. To account for species included as incidence data in the species abundance distribution, we modify the likelihood function of the classical Poisson log-normal distribution. Using simulated community assemblages, we contrast diversity estimates based on a community sample, a subsample randomly extracted from the community sample, and a mixture sample where incidence data are added to a subsample. We show that the mixture sampling approach provides more accurate estimates than the subsample and at little extra cost. Diversity indices estimated from a freshwater zooplankton community sampled using the mixture approach show the same pattern of results as the simulation study. Our method efficiently increases the accuracy of diversity estimates and comprehension of the left tail of the species abundance distribution. We show how to choose the scale of sample size needed for a compromise between information gained, accuracy of the estimates and cost expended when assessing biological diversity. The sample size estimates are obtained from key community characteristics, such as the expected number of species in the community, the expected number of individuals in a sample and the evenness of the community.     

Models and estimators linking individual-based and sample-based rarefaction,extrapolation and comparison of assemblages

Aims In ecology and conservation biology, the number of species counted in a biodiversity study is a key metric but is usually a biased underestimate of total species richness because many rare species are not detected. Moreover, comparing species richness among sites or samples is a statistical challenge because the observed number of species is sensitive to the number of individuals counted or the area sampled. For individual-based data, we treat a single, empirical sample of species abundances from an investigator-defined species assemblage or community as a reference point for two estimation objectives under two sampling models: estimating the expected number of species (and its unconditional variance) in a random sample of (i) a smaller number of individuals (multinomial model) or a smaller area sampled (Poisson model) and (ii) a larger number of individuals or a larger area sampled. For sample-based incidence (presence–absence) data, under a Bernoulli product model, we treat a single set of species incidence frequencies as the reference point to estimate richness for smaller and larger numbers of sampling units.Methods The first objective is a problem in interpolation that we address with classical rarefaction (multinomial model) and Coleman rarefaction (Poisson model) for individual-based data and with sample-based rarefaction (Bernoulli product model) for incidence frequencies. The second is a problem in extrapolation that we address with sampling-theoretic predictors for the number of species in a larger sample (multinomial model), a larger area (Poisson model) or a larger number of sampling units (Bernoulli product model), based on an estimate of asymptotic species richness. Although published methods exist for many of these objectives, we bring them together here with some new estimators under a unified statistical and notational framework. This novel integration of mathematically distinct approaches allowed us to link interpolated (rarefaction) curves and extrapolated curves to plot a unified species accumulation curve for empirical examples. We provide new, unconditional variance estimators for classical, individual-based rarefaction and for Coleman rarefaction, long missing from the toolkit of biodiversity measurement. We illustrate these methods with datasets for tropical beetles, tropical trees and tropical ants.Important findings Surprisingly, for all datasets we examined, the interpolation (rarefaction) curve and the extrapolation curve meet smoothly at the reference sample, yielding a single curve. Moreover, curves representing 95% confidence intervals for interpolated and extrapolated richness estimates also meet smoothly, allowing rigorous statistical comparison of samples not only for rarefaction but also for extrapolated richness values. The confidence intervals widen as the extrapolation moves further beyond the reference sample, but the method gives reasonable results for extrapolations up to about double or triple the original abundance or area of the reference sample. We found that the multinomial and Poisson models produced indistinguishable results, in units of estimated species, for all estimators and datasets. For sample-based abundance data, which allows the comparison of all three models, the Bernoulli product model generally yields lower richness estimates for rarefied data than either the multinomial or the Poisson models because of the ubiquity of non-random spatial distributions in nature.     

湖南八大公山25 ha常绿落叶阔叶混交林动态监测样地群落组成与空间结构

湖南八大公山国家级自然保护区位于武陵山系北缘, 区内分布有大面积的常绿落叶阔叶混交林, 物种多样性丰富, 群落结构复杂。中国科学院武汉植物园按CTFS (Center for Tropical Forest Sciences)建设规范于2010-2011年在保护区内建设了一个25 ha的动态监测样地, 为亚热带山地森林群落多样性长期动态监测提供了理想的平台。本文初步分析了八大公山25 ha样地的群落组成与空间结构。结果表明: 群落内共有木本植物存活个体186,575株, 隶属于53科114属232种; 个体数超过1,000株的有38个物种(贡献87%的个体数), 个体数最多的物种为黄丹木姜子(Litsea elongata); 样地内稀有种(≤ 25株)种数占样地总物种数的44%, 而个体数仅为样地总个体数的0.4%。样地内个体平均胸径为5.41 cm, 其中68.4%的个体DBH ≤ 5 cm, DBH ≥ 20 cm的个体数(7,474株)仅约占总个体数的4%; 个体胸径直方图呈倒“J”形, 表明样地处于良好更新与正常生长状态。样地的种-面积关系图显示物种数随样地面积的增加而同步增加, 其增长速度由迅速增长逐渐趋于稳定, 取样面积10 ha时可以涵盖90%以上的物种; 1 ha小样地个体数平均为7,261.8 ± 974.8 (SD), 物种数平均为128.2 ± 8.2 (SD), Shannon-Wiener指数平均为3.56 ± 0.11 (SD), Pielou均匀度指数变异最小, 平均为1.69 ± 0.06 (SD); 个体数与各多样性指数均无显著相关, 表明在该样地中物种多样性的取样效应不明显, 物种数量增加的原因可能来自于其他因素的控制。     

Intra-annual variations in abundance and species composition of carabid beetles in a temperate forest in Northeast China

In most habitats in temperate zones, species show clear intra-annual shifts in abundance and species composition. Here we aimed to present a comprehensive picture of community composition and seasonal dynamics of carabid beetles (Coleoptera: Carabidae) in broad-leaved Korean pine mixed forest in Northeast China, which harbors a large diversity. We sampled 23,336 individuals from 14 genera and 39 species with pitfall traps over more than 1 year in a 25-ha plot. The six most abundant species accounted for 76.65 % of all individuals. Species estimations for the 25 ha plot ranged from 40 to 45 species. Overall abundance, species diversity, community composition, and abundance of individual species varied seasonally. Most of the abundant species showed an activity pattern of single peak, and were most active between July and early September. Few species showed a bimodal seasonal activity pattern. Both temperature and precipitation significantly influenced the carabid community within a year. Hierarchical clustering indicated that carabid communities of ten consecutive sampling periods could be partitioned into three time-windows, respectively, corresponding with warm temperature-high rainfall season, warm temperature-low rainfall season, and cool and cold season. By using the extended method of indicator species analysis, 11 indicator species were identified for the three time-groups and their combinations, suggesting the existence of temporal niche partitioning among carabid species. We suggest that intra-annual patterns of carabid abundance and species composition can be explained by species responses to seasonal changes in hydrothermal conditions. Cost-effective sampling effort to assess native carabid diversity and assemblage was also discussed in this study.     

Spatial and temporal pattern of colonization of Nabidae (Heteroptera) in alfalfa (Medicago sativa)

Abstract: Six species of Nabidae (Heteroptera) were collected by standardized sweep net sampling in alfalfa fields in Thuringia, Germany, from 1993 to 1995: Nabis pseudoferus , N. ferus , N. brevis , N. major , Nabicula flavomarginata and Aptus mirmicoides . Colonization of a newly cultivated field was studied over a 3-year period. The density of all the studied nabid species was low (less than five individuals per 100 sweeps) and not related to time since colonization started, or to the distance from the margin of the field. Macropterous species were able to colonize the whole field within one season. The density of one macropterous species, N. pseudoferus , varied between the years of study and was mainly affected by the harvest regime. The brachypterous species reached the margin within one season but for density it took three seasons to reach satiated values also in the centre of the field. The abundance of the brachypterous N. brevis was significantly different both between years and sampling sites. This indicates the importance of the surroundings on the succession of this species. Nabis major , a fully winged species, showed a migration pattern intermediate to macropterous and brachypterous nabids. These results suggest that the total abundance of nabid predators cannot be predicted by time or distance from the expansion source (shelter belts). The abundance of brachypterous nabid individuals can be predicted from time since colonization but is best analysed at the species level.     

Developing methods for quantifying the apparent abundance of fiddler crabs (Ocypodidae: Uca) in mangrove habitats

Counting the number of individuals emerging from burrows is the most practical method for estimating the apparent abundance of Australian Uca species living in mangrove habitats. Experiments were conducted to investigate the effect on counts of quadrat design, distance of observer, quadrat size, recovery time and observational technique. Significant differences in the apparent abundance of one species were found when the subjects were within 2 m of the observer, and when a conspicuous quadrat was used. The largest quadrat tested provided the least variability in counts but an intermediate size (0.56 m²) was more practical. Most Uca active within a 30-min period emerged during the first 10 min regardless of site, species, sex or season. There was a linear correlation between scanning and continuous observation indicating that the former method could be useful when sampling time was limited. Temporal changes in the apparent abundance of Uca suggest that long-term sampling and more detailed studies will be worthwhile.     

Abundance patterns and coexistence processes in communities of fleas parasitic on small mammals

The abundance of a given species in a community is likely to depend on both the total abundance and diversity of other species making up that community. A large number of co-occurring individuals or co-occurring species may decrease the abundance of any given species via diffuse competition; however, indirect interactions among many co-occurring species can have positive effects on a focal species. The existence of diffuse competition and facilitation remain difficult to demonstrate in natural communities. Here, we use data on communities of fleas ectoparasitic on small mammals from 27 distinct geographical regions to test whether the abundance of any given flea species in a community is affected by either the total abundance of all other co-occurring flea species, or the species richness and/or taxonomic diversity of the flea community. At all scales of analysis, i.e. whether we compared the same flea species on different host species, or different flea species, two consistent results emerged. First, the abundance of a given flea species correlates positively with the total abundance of all other co-occurring flea species in the community. Second, the abundance of any given flea species correlates negatively with either the species richness or taxonomic diversity of the flea community. The results do not support the existence of diffuse competition in these assemblages, because the more individuals of other flea species are present on a host population, the more individuals of the focal species are there as well. Instead, we propose explanations involving either apparent facilitation among flea species via suppression of host immune defenses, or niche filtering processes acting to restrict the taxonomic composition and abundance of flea assemblages.     

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.     

A counting method for the number of Sternolophus rufipes and Hydrochara affinis in a noisy trap image

A quantitative survey of water scavenger beetles Sternolophus rufipes and Hydrochara affinis in paddy fields is essential not only for evaluating the impact of climate change on ecosystems but also for quantifying the stability of paddy fields. Many researchers classify insects in insect traps visually and manually count the number of individuals in each species. This manual survey method is time-consuming, fatiguing, and tedious. In this paper, we present a simple method to classify and count beetles in noisy trap images. The proposed method uses the beetles' body size and spots made by the light reflecting off the backs of beetles. We verify the method using images of beetles attached to the insect trap. The results demonstrate that the number of individuals in each species as counted by the proposed method and the manually counted number are statistically identical, which means that our method is sufficient to replace the existing manual counting method. Additionally, we briefly discuss the limitations of this counting method and ideas that could complement them.     

Long-term variation in the winter resident bird community of Guánica Forest, Puerto Rico: lessons for measuring and monitoring species richness

ABSTRACT.   Because the winter season is potentially limiting for migratory birds, understanding their nonbreeding distributional patterns is essential. At a given site, patterns of species occurrence and abundance may vary over time and, within a species, wintering strategies may vary with regard to the degree that individuals are site-faithful both within and between winters. We examined long-term patterns in the composition of a winter resident bird community to determine how long a site must be studied to understand the wintering community. Over a 34-yr period of constant-effort mist netting at a site in Guánica, Puerto Rico, we captured 21 species of winter resident birds, with mean total captures varying from 8.3 to 18.9 individuals per net line and 6–14 species captured per year. Species richness capture/recapture models generated numbers similar to actual capture rates. Capture and recapture data allowed us to categorize winter residents into three groups: sporadic winter residents (14 species), regular winter residents (four species captured nearly every year), and dominant winter residents (three species captured each year with high rates of recapture). Our results suggest that sampling for at least three consecutive winters is needed to accurately characterize the bird community at a site. However, sampling for 5 yr is better, and 10-yr samples generate patterns similar to those based on our entire 34-yr sample. A 1-yr sample provides minimal information about the composition and characteristics of a winter resident bird community.     

Estimating species – area relationships by modeling abundance and frequency subject to incomplete sampling

Models and data used to describe species–area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species–area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species‐level Poisson processes and estimate patch‐level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early‐successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species–area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density–area relationships and occurrence probability–area relationships can alter the form of species–area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.     

Phylogenetic community structure metrics and null models: a review with new methods and software

Competitive exclusion and habitat filtering influence community assembly, but ecologists and evolutionary biologists have not reached consensus on how to quantify patterns that would reveal the action of these processes. Currently, at least 22 α‐diversity and 10 β‐diversity metrics of community phylogenetic structure can be combined with nine null models (eight for β‐diversity metrics), providing 278 potentially distinct approaches to test for phylogenetic clustering and overdispersion. Selecting the appropriate approach for a study is daunting. First, we describe similarities among metrics and null models across variance in phylogeny size and shape, species abundance, and species richness. Second, we develop spatially explicit, individual‐based simulations of neutral, competitive exclusion, or habitat filtering community assembly, and quantify the performance (type I and II error rates) of all 278 metric and null model combinations against each assembly process. Many α‐diversity metrics and null models are at least functionally equivalent, reducing the number of truly unique metrics to 12 and the number of unique metric + null model combinations to 72. An even smaller subset of metric and null model combinations showed robust statistical performance. For α‐diversity metrics, phylogenetic diversity and mean nearest taxon distance were best able to detect habitat filtering, while mean pairwise phylogenetic distance‐based metrics were best able to detect competitive exclusion. Overall, β‐diversity metrics tended to have greater power to detect habitat filtering and competitive exclusion than α‐diversity metrics, but had higher type 1 error in some cases. Across both α‐ and β‐diversity metrics, null model selection affected type I error rates more than metric selection. A null model that maintained species richness, and approximately maintained species occurrence frequency and abundance across sites, exhibited low type I and II error rates. This regional null model simulates neutral dispersal of individuals into local communities by sampling from a regional species pool. We introduce a flexible new R package, metricTester, to facilitate robust analyses of method performance.     

On the estimation of species richness based on the accumulation of previously unrecorded species

Estimation of species richness of local communities has become an important topic in community ecology and monitoring. Investigators can seldom enumerate all the species present in the area of interest during sampling sessions. If the location of interest is sampled repeatedly within a short time period, the number of new species recorded is typically largest in the initial sample and decreases as sampling proceeds, but new species may be detected if sampling sessions are added. The question is how to estimate the total number of species. The data collected by sampling the area of interest repeatedly can be used to build species accumulation curves: the cumulative number of species recorded as a function of the number of sampling sessions (which we refer to as “species accumulation data”). A classic approach used to compute total species richness is to fit curves to the data on species accumulation with sampling effort. This approach does not rest on direct estimation of the probability of detecting species during sampling sessions and has no underlying basis regarding the sampling process that gave rise to the data. Here we recommend a probabilistic, nonparametric estimator for species richness for use with species accumulation data. We use estimators of population size that were developed for capture‐recapture data, but that can be used to estimate the size of species assemblages using species accumulation data. Models of detection probability account for the underlying sampling process. They permit variation in detection probability among species. We illustrate this approach using data from the North American Breeding Bird Survey (BBS). We describe other situations where species accumulation data are collected under different designs (e.g., over longer periods of time, or over spatial replicates) and that lend themselves to of use capture‐recapture models for estimating the size of the community of interest. We discuss the assumptions and interpretations corresponding to each situation.     

Relaxing the zero-sum assumption in neutral biodiversity theory

The zero-sum assumption is one of the ingredients of the standard neutral model of biodiversity by Hubbell. It states that the community is saturated all the time, which in this model means that the total number of individuals in the community is constant over time, and therefore introduces a coupling between species abundances. It was shown recently that a neutral model with independent species, and thus without any coupling between species abundances, has the same sampling formula (given a fixed number of individuals in the sample) as the standard model [Etienne, R.S., Alonso, D., McKane, A.J., 2007. The zero-sum assumption in neutral biodiversity theory. J. Theor. Biol. 248, 522-536]. The equilibria of both models are therefore equivalent from a practical point of view. Here we show that this equivalence can be extended to a class of neutral models with density-dependence on the community-level. This result can be interpreted as robustness of the model, i.e. insensitivity of the model to the precise interaction of the species in a neutral community. It can also be interpreted as a lack of resolution, as different mechanisms of interactions between neutral species cannot be distinguished using only a single snapshot of species abundance data.     

The spatial pattern of Enchytraeidae (Oligochaeta)

Summary Spatial pattern of enchytraeids (Oligochaeta: Enchytraeidae) was studied in an experimental plot in an apple orchard near Bavorov, South Bohemia, Czechoslovakia. A total of 450 soil cores were taken in 1982, all individuals were determined (juveniles to genus, mature individuals to species) and counted. In total, 17 species of 4 genera were found. Both juveniles and mature individuals exhibited a distinctly aggregated spatial pattern. The distribution of the number of individuals in a sampling unit may be effectively fitted by the negative binomial distribution. The fit of Neyman type A distribution was considerably poorer. Comparing juveniles and mature individuals of the same genus using Lloyd's index of patchiness we found mature individuals to be slightly more aggregated than juveniles. Comparing the observed distribution of species number with that expected under the assumption of independence we may conclude that individuals appear in multispecies aggregation centres. These two conclusions support the hypothesis that aggregations are environmentally conditioned (abiotic factors and/or food availability) rather than caused by the type of reproduction.     

The implicit assumption of symmetry and the species abundance distribution

Species abundance distributions (SADs) have played a historical role in the development of community ecology. They summarize information about the number and the relative abundance of the species encountered in a sample from a given community. For years ecologists have developed theory to characterize species abundance patterns, and the study of these patterns has received special attention in recent years. In particular, ecologists have developed statistical sampling theories to predict the SAD expected in a sample taken from a region. Here, we emphasize an important limitation of all current sampling theories: they ignore species identity. We present an alternative formulation of statistical sampling theory that incorporates species asymmetries in sampling and dynamics, and relate, in a general way, the community-level SAD to the distribution of population abundances of the species integrating the community. We illustrate the theory on a stochastic community model that can accommodate species asymmetry. Finally, we discuss the potentially important role of species asymmetries in shaping recently observed multi-humped SADs and in comparisons of the relative success of niche and neutral theories at predicting SADs.