A conceptual guide to measuring species diversity

Three metrics of species diversity – species richness, the Shannon index and the Simpson index – are still widely used in ecology, despite decades of valid critiques leveled against them. Developing a robust diversity metric has been challenging because, unlike many variables ecologists measure, the diversity of a community often cannot be estimated in an unbiased way based on a random sample from that community. Over the past decade, ecologists have begun to incorporate two important tools for estimating diversity: coverage and Hill diversity. Coverage is a method for equalizing samples that is, on theoretical grounds, preferable to other commonly used methods such as equal-effort sampling, or rarefying datasets to equal sample size. Hill diversity comprises a spectrum of diversity metrics and is based on three key insights. First, species richness and variants of the Shannon and Simpson indices are all special cases of one general equation. Second, richness, Shannon and Simpson can be expressed on the same scale and in units of species. Third, there is no way to eliminate the effect of relative abundance from estimates of any of these diversity metrics, including species richness. Rather, a researcher must choose the relative sensitivity of the metric towards rare and common species, a concept which we describe as ‘leverage.' In this paper we explain coverage and Hill diversity, provide guidelines for how to use them together to measure species diversity, and demonstrate their use with examples from our own data. We show why researchers will obtain more robust results when they estimate the Hill diversity of equal-coverage samples, rather than using other methods such as equal-effort sampling or traditional sample rarefaction.     

Community assessment techniques and the implications for rarefaction and extrapolation with Hill numbers

Diversity estimates play a key role in ecological assessments. Species richness and abundance are commonly used to generate complex diversity indices that are dependent on the quality of these estimates. As such, there is a long‐standing interest in the development of monitoring techniques, their ability to adequately assess species diversity, and the implications for generated indices. To determine the ability of substratum community assessment methods to capture species diversity, we evaluated four methods: photo quadrat, point intercept, random subsampling, and full quadrat assessments. Species density, abundance, richness, Shannon diversity, and Simpson diversity were then calculated for each method. We then conducted a method validation at a subset of locations to serve as an indication for how well each method captured the totality of the diversity present. Density, richness, Shannon diversity, and Simpson diversity estimates varied between methods, despite assessments occurring at the same locations, with photo quadrats detecting the lowest estimates and full quadrat assessments the highest. Abundance estimates were consistent among methods. Sample‐based rarefaction and extrapolation curves indicated that differences between Hill numbers (richness, Shannon diversity, and Simpson diversity) were significant in the majority of cases, and coverage‐based rarefaction and extrapolation curves confirmed that these dissimilarities were due to differences between the methods, not the sample completeness. Method validation highlighted the inability of the tested methods to capture the totality of the diversity present, while further supporting the notion of extrapolating abundances. Our results highlight the need for consistency across research methods, the advantages of utilizing multiple diversity indices, and potential concerns and considerations when comparing data from multiple sources.     

Species turnover in lake littorals: spatial and temporal variation of benthic macroinvertebrate diversity and community composition

Aims Despite wide consensus that ecological patterns and processes should be studied at multiple spatial scales, the temporal component of diversity variation has remained poorly examined. Specifically, rare species may exhibit patterns of diversity variation profoundly different from those of dominant taxa. Location Southern Finland. Methods We used multiplicative partitioning of true diversities (species richness, Shannon diversity) to identify the most important scale(s) of variation of benthic macroinvertebrate communities across several hierarchical scales, from individual samples to multiple littorals, lakes and years. We also assessed the among‐scale variability of benthic macroinvertebrate community composition by using measures of between‐ and within‐group distances at hierarchical scales. Results On average, a single benthic sample contained 23% of the total regional macroinvertebrate species pool. For both species richness and Shannon diversity, beta‐diversity was clearly the major component of regional diversity, with within‐littoral beta‐diversity (β₁) being the largest component of gamma‐diversity. The interannual component of total diversity was small, being almost negligible for Shannon index. Among‐sample (within‐littoral) diversity was related to variation of substratum heterogeneity at the same scale. By contrast, only a small proportion of rare taxa was found in an average benthic sample. Thus, dominant species among lakes and years were about the same, whereas rare species were mostly detected in a few benthic samples in one lake (or year). For rare species, the temporal component of diversity was more important than spatial turnover at most scales. Main conclusions While individual species occurrences and abundances, particularly those of rare taxa, may vary strongly through space and time, patterns of dominance in lake littoral benthic communities are highly predictable. Consequently, many rare species will be missed in temporally restricted samples of lake littorals. In comprehensive biodiversity surveys, interannual sampling of littoral macroinvertebrate communities is therefore needed.     

A comparison of species diversity estimators

Although having been much criticized, diversity indices are still widely used in animal and plant ecology to evaluate, survey, and conserve ecosystems. It is possible to quantify biodiversity by using estimators for which statistical characteristics and performance are, as yet, poorly defined. In the present study, four of the most frequently used diversity indices were compared: the Shannon index, the Simpson index, the Camargo eveness index, and the Pielou regularity index. Comparisons were performed by simulating the Zipf–Mandelbrot parametric model and estimating three statistics of these indices, i.e., the relative bias, the coefficient of variation, and the relative root-mean-squared error. Analysis of variance was used to determine which of the factors contributed most to the observed variation in the four diversity estimators: abundance distribution model or sample size. The results have revealed that the Camargo eveness index tends to demonstrate a high bias and a large relative root-mean-squared error whereas the Simpson index is least biased and the Shannon index shows a smaller relative root-mean-squared error, regardless of the abundance distribution model used and even when sample size is small. Shannon and Pielou estimators are sensitive to changes in species abundance pattern and present a nonnegligible bias for small sample sizes (<1000 individuals). Received: May 8, 1998 / Accepted: May 6, 1999     

天童国家森林公园树种多样性的加性分配

根据物种丰富度、Shannon指数和Simpson指数建立的物种多样性分配方法,提出分异度系数,对天童森林公园内不同森林类型的树种多样性进行了分析.结果表明,基于物种丰富度指数,总体的多样性只有小部分归功于样方内多样性,而多样性大多分配在样方间、亚群丛间或群丛间,例如在木荷-栲树群丛中,样方内只贡献了20.3%的物种丰富度.而在Shannon指数和Simpson指数中,多样性大多分配在样方内.这种差异主要是由于后两种指数不仅考虑了物种的存在与否,也考虑了其在样方内的多度.同时比较分析了加性分配与传统方法的结果.     

新薛河底栖动物物种多样性与功能多样性研究

研究功能多样性与物种多样性关系及其随环境梯度的变化规律,有助于理解生物在群落中的共存机制;然而,二者间关系的研究在淡水生态学中尚鲜见报道。通过对新薛河典型河段(A缓流河段、B断流河段、C有机污染河段、D对照河段、E人为干扰河段)底栖动物季节性调查,就物种多样性和功能多样性时空动态及关系进行了研究。结果表明:在空间序列上,物种多样性指数在B河段均最低,表明间歇性断流对物种多样性影响重大。功能丰富度在D河段最高,A河段最低;功能均匀度在A河段高于其他河段;功能分离度在A、B河段最高,D河段最低。在时间序列上,物种丰富度和Shannon指数均值在10月份最低,4月份最高;均匀度指数在12月份最低,10月份最高。3个功能多样性指数于各季节间差异显著、相互独立,主要受水文条件和底栖动物生活史影响。相关分析表明,功能多样性指数间无显著相关性;功能丰富度同物种丰富度和Shannon指数相关显著,功能均匀度同物种均匀度相关显著。逐步回归分析发现,功能丰富度受物种丰富度和Shannon指数影响显著,功能均匀度受物种均匀度影响显著;功能多样性和物种多样性指数间拟合度总体不高。研究结果进一步表明:相对物种多样性,功能多样性对生境梯度变化响应更加全面。     

放牧干扰下高寒草甸物种多样性指数评价与选择

在青藏高原东北缘高寒草甸设置6个放牧强度样地,连续4年研究10个多样性指数(Richness和Abundance 2个实测指数,优势度指数、均匀度指数、丰富度指数和综合指数各2个)对放牧强度和年限影响植物群落的解释能力.结果表明: 相对于重要值,利用多度计算的多样性指数对放牧干扰更敏感.优势度指数(Berger-Parker、Dominance)与放牧强度和年限均无关,不能将放牧干扰对群落优势种的影响有效区分.均匀度指数(Equitability、Evenness)均与放牧强度无关,但Evenness指数与放牧年限呈显著负相关,不受偶见种影响且与物种多度的变异系数呈显著正相关,在基于时间尺度的均匀度比较中可以选择Evenness指数.丰富度指数(Menhinick、Margalef)均与放牧年限无关,但Margalef指数与放牧强度呈显著正相关,且不受偶见种影响.综合指数(Shannon、Simpson)均与放牧强度无关,但Shannon指数与物种丰富度和多度呈显著正相关,且随放牧年限增加而显著升高,不受偶见种影响,Shannon指数可用于在长时间尺度下比较物种多样性变化.在所有多样性指数中,只有实测物种丰富度和多度均与放牧强度呈显著负相关,与放牧年限呈显著正相关,且不受偶见种影响,故实测物种丰富度和多度相结合可作为放牧干扰下多样性比较的首选指标.此外,多样性指数选择须考虑放牧干扰的强度与时间特征、多样性组分和研究目的.     

不同母质温带草地植物群落多样性对人为干扰的响应

本研究以赛罕乌拉保护区2种不同土壤母质(黄土和沙母质)与3种利用方式(围栏打草、季节性放牧和自由放牧)草地为对象,基于群落组成调查数据,计算人为干扰指数与物种多样性指数,研究草地植物群落物种多样性与草地退化程度间的关系。结果表明: 土壤母质与人为利用方式的差异使草地处于不同的退化状态,黄土与沙母质类型草地退化程度均随人为利用强度的增加而上升,且当人为利用方式相同时,黄土母质草地人为干扰指数(均值1.21)比沙母质草地(均值1.48)低。各样地物种多样性指数总体随土壤母质的砂质化和人为利用强度的增加而下降,其中Margalef丰富度指数为1.57～4.27,Shannon多样性指数为1.16～2.39,Simpson优势度指数为0.76～0.87,Pielou均匀度指数为0.71～0.80。随着人为干扰指数增加,丰富度指数、多样性指数和优势度指数均下降,而均匀度指数有上升趋势。过度放牧对2种土壤母质草地均会造成严重威胁,黄土与沙母质草地最适宜的利用方式分别为围封打草和季节性放牧。在今后生物多样性保护的实施过程中,需兼顾草地不同土壤母质与人为利用方式的影响,针对不同土壤母质条件规划不同的草地利用方式,实现因地制宜的草地恢复与管理。     

The Role of Landscape Patterns of Habitat Types on Plant Species Diversity of a Tropical Forest in Mexico

The relationships among landscape characteristics and plant diversity in tropical forests may be used to predict biodiversity. To identify and characterize them, the number of species, as well as Shannon and Simpson diversity indices were calculated from 157 sampling quadrats (17,941 individuals sampled) while the vegetation classes were obtained from multi-spectral satellite image classification in four landscapes located in the southeast of Quintana Roo, Mexico. The mean number of species of trees, shrubs and vines as well as the mean value of the total number of species and the other two diversity indices were calculated for four vegetation classes in every one of the four landscapes. In addition, the relationships between landscape patterns metrics of patch types and diversity indices were explored. The multiple statistical analyses revealed significant predictor variables for the three diversity indices. Moreover, the shape, similarity and edge contrast metrics of patch types might serve as useful indicators for the number of species and the other two diversity variables at the landscape scale. Although the association between the three diversity indices and patch types metrics showed similar behavior, some differences were appreciated. The Shannon diversity index, with its greater sensitivity to rare species, should be considered as having a greater importance in interpretation analysis than Simpson index.     

Biodiversity of vespid wasps in spatial and temporal dimensions in northern Zanjan Province of Iran

Vespidae is one of the major families of Hymenoptera with more than 115000 described species. In the present paper, Simpson and Shannon-Wiener diversity indices, Simpson,Camargo, Smith and Wilson, and modified Nee evenness indices, and richness index based on rarefaction method were adopted to study the biodiversity of vespid wasps in spatial and temporal dimensions in northern Zanjan Province of Iran. In spatial dimension, Zanjan and Gilvan showed the highest and the lowest species diversity, evenness, and richness, respectively; while in tem-poral dimension, 16 July-6 August showed the highest species diversity and richness, and 18 May -27 May and 23 August -2 September showed the highest and the lowest species evenness,respectively. Significant differences in species abundance between localities of study area were observed by Kruskal-Wallis nonparametric test.     

Occurrence and distribution of zoosporic organisms in water bodies from Brazilian Cerrado

Zoosporic organisms are commonly found in different aquatic ecosystems; however little is known about the influence of environmental factors and seasonal fluctuations on their occurrence and distribution. This study investigated patterns of abundance, frequency and diversity of these organisms and their relationship with some abiotic factors and seasonality in a cerrado remnant in Sao Paulo, Brazil. Water samples were collected at four dates in two areas of this remnant during the rainy and dry seasons, and 13 abiotic factors were analyzed. From 48 samples collected, 32 taxa were isolated with the multiple baiting technique. The community structure of the zoosporic organisms showed some changes in response to different spatial distribution and seasonal fluctuations, probably influenced by distinct abiotic characteristics of each area or climatic period. Still, the similarity between areas and seasons indicated by S?rensen index and diversity (richness, evenness, Shannon and Simpson indices) were high.     

Stressor prioritisation in riverine ecosystems: Which environmental factors shape benthic invertebrate assemblage metrics?

Aquatic ecosystems are amongst the most heavily altered ecosystems and exhibit a disproportional loss of biodiversity. Numerous stressors, such as nutrient enrichment, contaminant pollution, sedimentation and alterations in stream hydrology and habitat structure, account for these losses. Understanding these forces is of utmost importance to prevent riverine ecosystems from further deterioration and to provide helpful insights for restoration practices. In the present study, we analyse the response of biological indicators to a large number of environmental factors. For this, benthic invertebrate assemblages from 83 sites in Germany were described based on 25 metrics from four different metric types. The condition of the sites was described using 27 environmental factors: 13 for water quality, 4 for land use in the catchment and 10 for local scale habitat structure. The relative importance of single environmental predictors or predictor combinations for benthic invertebrate assemblages was analysed with single and multiple linear regression models. The results for the latter models were statistically supported via a bootstrap approach. The models revealed the importance of water quality and catchment-scale land use in explaining benthic invertebrate assemblages; in particular, chloride, oxygen, total organic carbon and the amounts of artificial surfaces and arable land were the most important predictors. Models including solely structural variables such as plan form, bank structures and substrate diversity had lower goodness of fit values than those for other variables. Regarding the four different assemblage metric types, functional metrics had on average lower goodness of fit values than composition/abundance, richness/diversity and sensitivity/tolerance metrics. Among the richness/diversity metrics, however, the model results for the Shannon–Wiener and Simpson diversity indices and evenness were poor. Our results show that catchment-related factors and water quality were of overriding importance in shaping biodiversity patterns and causing species loss. In contrast, structural degradation at a local scale was not the most significant stressor. This finding might explain why structural restoration at a reach scale often yields a low benefit–cost ratio and may be considered to represent inappropriate investment prioritisation.     

Desirable mathematical properties of indicators for biodiversity change

Numerous indicator approaches are found in the scientific literature to describe changes in biodiversity. It is however far from clear which indicators are most appropriate and which are less suitable to summarize trends in biodiversity. One reason for this lack of clarity is that so far the mathematical properties of indicator approaches have had little attention. In this paper, we derive a number of desirable mathematical properties of indicators from economic price-index theory and apply these in the form of tests to 10 metrics to summarize changes in biodiversity. The metrics species richness, Simpson index, Shannon index, Buckland's modified Shannon index and Sørensen's similarity coefficient violate the monotonicity and proportionality test. The percentage of increasing minus declining species also fails the proportionality test, and in the case where trends are assessed relative to the preceding year, this metric also violates the identity test. Most of these indicators are sensitive to spatial scale. The arithmetic and geometric mean of population indices and the mean abundance have better mathematical performance, but the first two are sensitive to appearing and disappearing species in the system surveyed. The metric mean abundance however can only be applied under particular conditions and has some undesirable properties. Unlike the arithmetic mean, the geometric mean is not sensitive to the base year chosen and has the most favourable mathematical properties of the indicators evaluated. The geometric mean can be straightforwardly extended to take into account unequal values of species if desired.     

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.     

Only Simpson Diversity can be Estimated Accurately from Microbial Community Fingerprints

Lalande et al. (Microb. Ecol. 66(3):647–658, 2013) introduced a promising approach to quantify microbial diversity from fingerprinting profiles. Their analysis is based on extrapolating the abundance of the phylotypes detectable in a fingerprint towards the rare phylotypes of the community. By considering a set of reconstructed communities, Lalande et al. obtained a range of estimates for phylotype richness, Shannon diversity and Simpson diversity. They reported narrow ranges indicating accurate estimation, especially for Shannon and Simpson diversities. Here, we show that a much larger set of reconstructed communities than the one considered by Lalande et al. is consistent with the fingerprint. We find that the estimates for phylotype richness and Shannon diversity vary over orders of magnitude, but that the estimates for Simpson diversity are restricted to a narrow range (around 10 %). We conclude that only Simpson diversity can be estimated accurately from fingerprints.     

Finding the Minimum Sample Richness (MSR) for multivariate analyses: implications for palaeoecology

Many techniques have been developed to estimate species richness and beta diversity. Those techniques, dependent on sampling, require abundance or presence/absence data. Palaeontological data is by nature incomplete, and presence/absence data is often the only type of data that can be used to provide an estimate of ancient biodiversity. We used a simulation approach to investigate the behaviour of commonly used similarity indices, and the reliability of classifications derived from these indices, when working with incomplete data. We drew samples, of varying number and richness, from artificial species lists, which represented original life assemblages, and calculated error rates for classifications of the parent lists and samples. Using these results, we estimated the Minimum Sample Richness (MSR) needed to achieve 95% classification accuracy. Results were compared for classifications derived from several commonly used similarity indexes (Dice, Jaccard, Simpson and Raup–Crick). MSR was similar for the Dice, Jaccard and Simpson indices. MSR for the Raup–Crick index was often much lower, suggesting that it is preferable for classifying patchy data, however the performance of this index was less stable than the other three in the simulations, which required an even lower MSR. MSR can be found for all presence/absence data from the contour graphs and equations as long as the absolute species richness and the beta diversity can be estimated.     

Patterns of functional and taxonomic organization of stream fishes: inferences based on α, β, and γ diversities

The primary objective of this study was to determine whether total biodiversity (γ) is partitioned into within‐community (α) and among‐community (β) components differently for taxonomic and functional organization. I hypothesized that α diversity will contribute more to the functional organization of γ diversity and that β diversity will contribute more to the taxonomic organization of γ diversity. A secondary objective was to determine whether the relationship between taxonomic and functional diversity is scale dependent. Species abundance data was obtained from fisheries surveys conducted by the Texas Parks and Wildlife Dept that focused on least disturbed streams from 11 different ecoregions of Texas, including 62 localities from 18 drainages. Functional and taxonomic organization of assemblages was quantified with two different measures of biodiversity, including richness and the numbers equivalent of Shannon diversity. Scale‐dependent effects on these indices were assessed by multiplicatively partitioning γ into α and β components. The contribution of α and β components to γ diversity differed between functional and taxonomic organization and among different measures of biodiversity. Among‐community components were more influential in structuring the taxonomic organization of stream‐fish assemblages, whereas within‐community components were more important in structuring the functional organization of assemblages. The relationship between taxonomic and functional diversity differed between α and β components and between spatial scales. Indeed, ecological patterns not only change with spatial scale, but how they change is dependent on which aspect of biodiversity is considered.     

Do generalized scaling laws exist for species abundance distribution in mountains?

Knowing the global pattern of species diversity is a central goal of the science of ecology, and scaling laws can be useful for analysis of cross-scale biodiversity patterns. An elevational gradient in a warm temperate zone of the Donglingshan mountains (China) is used to test the scaling laws of species abundance distribution using multifractal analysis. We show that the power law scaling relationship holds for not just the classical SAR (species–area relationship for richness), but also for Shannon and Simpson diversity. In fact, we find power-laws in the generalized species abundance distribution at all stratal levels of the forest (trees, shrubs and herbs). The fact that these laws exist across a heterogeneous landscape representing a strong bioclimatic gradient suggests that biodiversity scaling laws may be more robust than previously thought.     

中国暖温带若干灌丛群落多样性问题的研究

 暖温带灌丛的生物多样性的研究表明：1．灌丛群落的均一度指数同优势度指数的相关性较丰富度指数同变化度指数的相关性为高;在众多的多样性指数中,D4(Shannon信息度指数)和D6(Gini指数)因最大限度地包含了其它各类多样性指数的信息而被采用。2．灌丛群落的物种多样性指数值随着演替的进行,没有表现出降低的趋势。3．生物多样性较高的荆条灌丛和辽东栎萌丛的物种多度分布是对数分布,而生物多样性较低的鬼见愁灌丛和毛榛灌丛的物种多度分布是几何分布,处于中间的三桠绣线菊灌丛的物种多度分布是Broken-Stick分布;没有正态对数分布类型。     

N90 index: A new approach to biodiversity based on similarity and sensitive to direct and indirect fishing impact

An important effort has been made to develop diversity indices suitable to monitor the loss of biodiversity due to anthropogenic impacts in an accurate and comprehensible way. Here, N₉₀, a diversity index based on the species’ contribution to the similarity between samples in a group, is presented. N₉₀ uses the results of the classic Similarity Percentage analysis and a jack-knife routine to calculate the average and a dispersion value of the number of species contributing up to the ninety percent of the similarity in a group of samples. N₉₀ is applied to two groups of samples subjected to contrasting levels of bottom trawl fishing pressure using time series of experimental bottom trawl surveys of the Balearic Islands. The results are compared to those obtained using more ‘traditional’ diversity indices such as species richness, Shannon–Wienner, Simpson, Pielou, and Margalef diversity indices. The N₉₀ diversity index displayed a clear response to fishing pressure with significantly lower values in impacted communities, while the ‘traditional’ diversity indices showed almost null sensitivity to fishing pressure. In addition, N₉₀ also detects indirect fishing impacts by fluctuating in response to environmental variation in impacted areas, making this index sensitive to the synergies between climate and fishing impact at community level. The application of the N₉₀ diversity index to the case study shows that it may be an alternative to ‘traditional’ diversity indices when trying to monitor fishing impacts and the effects of environmental changes. Its units, number of species, and the corresponding summary list of species facilitate the interpretability of the results, improving the communication to managers and stakeholders.