Compositional dissimilarity as a robust measure of ecological distance

The robustness of quantitative measures of compositional dissimilarity between sites was evaluated using extensive computer simulations of species' abundance patterns over one and two dimensional configurations of sample sites in ecological space. Robustness was equated with the strength over a range of models, of the linear and monotonic (rank-order) relationship between the compositional dissimilarities and the corresponding Euclidean distances between sites measured in the ecological space. The range of models reflected different assumptions about species' response curve shape, sampling pattern of sites, noise level of the data, species' interactions, trends in total site abundance, and beta diversity of gradients.The Kulczynski, Bray-Curtis and Relativized Manhattan measures were found to have not only a robust monotonic relationship with ecological distance, but also a robust linear (proportional) relationship until ecological distances became large. Less robust measures included Chord distance, Kendall's coefficient, Chisquared distance, Manhattan distance, and Euclidean distance.A new ordination method, hybrid multidimensional scaling (HMDS), is introduced that combines metric and nonmetric criteria, and so takes advantage of the particular properties of robust dissimilarity measures such as the Kulczynski measure.We thank M. P. Austin for encouraging this study, and I. C. Prentice, E. Van der Maarel, and an anonymous reviewer for helpful comments. E. M. Adomeit provided technical assistance.     

Mapping landscape beta diversity of plants across KwaZulu-Natal,South Africa,for aiding conservation planning

Collective properties of biodiversity, such as beta diversity, are suggested as complementary measures of species richness to guide the prioritisation and selection of important biodiversity areas in regional conservation planning. We assessed variation in the rate of plant species turnover along and between environmental gradients in KwaZulu-Natal, South Africa using generalised dissimilarity modelling, in order to map landscape levels of floristic beta diversity. Our dataset consisted of 434 plots (1000 m²) containing 997 grassland and savanna matrix species. Our model explained 79 % of the null deviance observed in floristic dissimilarities. Variable rates of turnover existed along the major environmental gradients of mean annual temperature, median rainfall in February, and soil cation exchange capacity, as well as along gradients of geographical distance. Beta diversity was highest in relatively warm, drier summer regions and on dystrophic soils. Areas of high beta diversity identify areas that should be included in conservation plans to maximise representation of diversity and highlight areas best suited to protected area expansion. Biome transition areas in high beta diversity areas may be susceptible to climate variability. Including beta diversity turnover rates in regional conservation plans will help to preserve evolutionary and ecological processes that create and maintain diversity.     

A guide through a family of phylogenetic dissimilarity measures among sites

Ecological studies have now gone beyond measures of species turnover towards measures of phylogenetic and functional dissimilarity. This change of perspective has a main objective: disentangling the processes that drive species distributions from local to broad scales. A fundamental difference between phylogenetic and functional analyses is that phylogeny is intrinsically dependent on a tree‐like structure whereas functional data can, most of time, only be forced to adhere a tree structure, not without some loss of information. When the branches of a phylogenetic tree have lengths, then each evolutionary unit on these branches can be considered as a basic entity on which dissimilarities among sites should be measured. Several of the recent measures of phylogenetic dissimilarities among sites thus are traditional dissimilarity indices where species are replaced by evolutionary units. The resulting indices were named PD‐dissimilarity indices, in reference to early work on the phylogenetic diversity (PD) measure. Here I review and compare indices and ordination approaches that, although first developed to analyse the differences in the species compositions of sites, can be adapted to describe PD‐dissimilarities among sites. Using simulations of species distributions along environmental gradients, I compare indices, associated with permutation tests and null models, in their ability to reveal existing phylogenetic patterns along the gradients. As an illustration, I show that the amount of bat PD‐dissimilarities along a disturbance gradient in Selva Lacandona of Chiapas, Mexico is dependent on whether species' abundance is considered, and on the PD‐dissimilarity index used. Overall, the family of PD‐dissimilarity indices has a critical potential for future analyses of phylogenetic diversity as it benefits from decades of research on the measure of species dissimilarity. I provide clues to help to choose among many potential indices, identifying which indices satisfy minimal basic properties, and analysing their sensitivity to abundance, size, diversity and joint absences.     

Modelling niche and neutral dynamics: on the ecological interpretation of variation partitioning results

Many studies have attempted to disentangle the effects of neutral and niche‐mediated processes on community composition using partial Mantel tests and variance partitioning on dissimilarity matrices. Recently, doubts about the reliability of these methods have emerged. Here we explore how the results are affected by three confounding factors that may affect ecological data to different degrees: spatial autocorrelation of the environmental variables, length of the compositional gradient, and sampling noise. We document that the statistical hypotheses tested in these methods may or may not correspond to the ecological hypotheses of interest. A major discrepancy emerges if a large proportion of sampling units in the analysed dataset share no species, in which case compositional dissimilarities saturate to a fixed maximum value although explanatory dissimilarities do not. With increasing dissimilarity saturation, the explanatory power of regression models decrease, which may lead to the erroneous conclusion that the ecological processes represented by the explanatory variables are not operating. A survey of recent literature suggests that there is a general lack of awareness of this problem, although it appears to affect > 10% of relevant studies. Our simulations show that if dissimilarity saturation is due to a long ecological gradient, extended dissimilarities essentially solve the problem for any degree of saturation. Using distances from a hybrid multidimensional scaling alleviates the saturation problem when the degree of saturation is < 60%. However, neither correction method can provide a solution to problems caused by insufficient sampling. How the presence of multiple explanatory gradients in combination with sampling noise affects overall analysis performance remains to be clarified.     

Species and plant community distribution in a Mojave-Great Basin desert transition

Multivariate analyses were used to describe the vegetation characteristics of a transition from lowelevation Mojave desert to higher-elevation Great Basin desert. Vegetation data used were from Plutonium Valley in the Nevada Test Site. Data from forty nine releves were analyzed with two classifications (two-day indicator analysis or TWINSPAN and unweighted paried group cluster analysis or CLUSTER). Three ordinations, reciprocal averaging (RA), detrended reciprocal averaging (DCA) and non-metric multidimensional scaling (MNDS), were also used. A rotational correlation analysis was used to determine the vector direction of environmental gradients that correlate best with ordination results. Only token correspondence was found between multivariate classes generated by TWINSPAN and CLUSTER, and seven classes (plant communities) identified from field reconnaissance. The latter seven communities were based on differences in dominant species. Distribution of the vegetation was related more to beta diversity than alpha diversity. Individual species were much less diagnostic than the amount of plant cover, groups or guilds of species or differences in elevation and steepness of slope. Because of the high beta diversity the NMDS ordination gave results with the greatest ease of interpretation.     

Effects of freshwater eutrophication on species and functional beta diversity of periphytic algae

Studies about beta diversity and environmental heterogeneity have shown that the strength of the environmental filtering effect may decrease with the increasing scale. These empirical results have related eutrophic aquatic environments to higher values of beta diversity, but never to dissimilarity of species and functional traits of periphytic algae. We tested the hypotheses that periphytic algae have higher dissimilarity of both species and functional traits in eutrophic environments, and that these dissimilarities are related to environmental dissimilarity. To this end, we used richness, density, and four functional traits of periphytic algae and local limnological data from wetlands in the Brazilian savanna (Cerrado). We analyzed the beta diversity and the relationship of species and functional dissimilarities with the environmental dissimilarity and geographic distances. Our hypothesis was confirmed for functional traits dissimilarity and for the importance of the environmental dissimilarity for both species and functional beta diversity. The cultural eutrophication led to a functional homogenization in urban wetlands, which indicates the establishment of species with similar ecological requirements, and consequently, similar ‘roles’ in the ecosystem, and also that sensitive species may have been replaced by tolerant species, leading to declining biodiversity.

     

Multiple site dissimilarity quantifies compositional heterogeneity among several sites,while average pairwise dissimilarity may be misleading

Several measures of multiple site dissimilarity have been proposed to quantify the overall heterogeneity in assemblage composition among any number of sites. It is also a common practice to quantify such overall heterogeneity by averaging pairwise dissimilarities between all pairs of sites in the pool. However, pairwise dissimilarities do not account for patterns of co‐occurrence among more than two sites. In consequence, the average of pairwise dissimilarities may not accurately reflect the overall compositional heterogeneity within a pool of more than two sites. Here I use several idealized examples to illustrate why pairwise dissimilarity measures fail to properly quantify overall heterogeneity. Thereafter, the effect of this potential problem in empirical patterns is exemplified with data of world amphibians. In conclusion, when the attribute of interest is the overall heterogeneity in a pool of sites (i.e. beta diversity) or its turnover or nestedness components, only multiple site dissimilarity measures are recommended.     

A family of functional dissimilarity measures for presence and absence data

Plot‐to‐plot dissimilarity measures are considered a valuable tool for understanding the complex ecological mechanisms that drive community composition. Traditional presence/absence coefficients are usually based on different combinations of the matching/mismatching components of the 2 × 2 contingency table. However, more recently, dissimilarity measures that incorporate information about the degree of functional differences between the species in both plots have received increasing attention. This is because such “functional dissimilarity measures” capture information on the species' functional traits, which is ignored by traditional coefficients. Therefore, functional dissimilarity measures tend to correlate more strongly with ecosystem‐level processes, as species influence these processes via their traits. In this study, we introduce a new family of dissimilarity measures for presence and absence data, which consider functional dissimilarities among species in the calculation of the matching/mismatching components of the 2 × 2 contingency table. Within this family, the behavior of the Jaccard coefficient, together with its additive components, species replacement, and richness difference, is examined by graphical comparisons and ordinations based on simulated data.     

Comparisons of three ordination techniques

Summary Simulated coenoclines were used to test performance of several techniques for ordinating samples by species composition: Wisconsin polar or Bray-Curtis ordination with Euclidean distance (ED) and the complements of percentage similarity (PD) and coefficient of community (CD) as distance measures, Principal components analysis, and polar and non-polar or indirect use of Discriminant function analysis. In general the Bray-Curtis technique gave the best ordinations, and PD was the best distance measure. Euclidean distance gave greater distortion than PD in all tests; CD may be better than PD only for some sample sets of high alpha and beta diversity and high levels of noise or sample error. Principal components ordinations are increasingly distored as beta diversity increases, and are highly vulnerable to effects of both noise and sample clustering. Discriminant function analysis was found generally unsuitable for ordination of samples by species composition, but likely to be useful for sample classification.     

Resemblance in phylogenetic diversity among ecological assemblages

Questions: How can a resemblance (similarity or dissimilarity) measure be formulated to include information on both the evolutionary relationships and abundances of organisms, and how does it compare to measures lacking such information? Methods: We extend the family of Phylogenetic Diversity (PD) measures to include a generalized method for calculating pair‐wise resemblance of ecological assemblages. Building on previous work, we calculate the matching/mismatching components of the 2 × 2 contingency table so as to incorporate information on both phylogeny and abundance. We refer to the class of measures so defined as “PD resemblance” and use the term “SD resemblance” for the traditional class of measures based on species diversity alone. As an illustration, we employ data on the diversity and stem density of shrubs of Toohey Forest, Australia, to compare PD resemblance to its SD resemblance equivalent for both incidence and abundance data. Results: While highly correlated, PD resemblance consistently measures assemblages as more similar than does SD resemblance, and tends to “smooth out” the otherwise skewed and truncated distribution of pair‐wise resemblance indices of our high‐turnover data set, resulting in nMDS ordinations with lower stress. Randomization of species distributions across assemblages indicates that phylogeny has made a significant contribution to the ordination pattern. Conclusions: PD resemblance measures, in addition to providing an evolutionary perspective, have great potential to improve distance‐based analyses of community patterns, particularly if species responses to ecological gradients are unimodal and phylogenetically conserved.     

Phylogenetic beta diversity metrics, trait evolution and inferring the functional beta diversity of communities

The beta diversity of communities along gradients has fascinated ecologists for decades. Traditionally such studies have focused on the species composition of communities, but researchers are becoming increasingly interested in analyzing the phylogenetic composition in the hope of achieving mechanistic insights into community structure. To date many metrics of phylogenetic beta diversity have been published, but few empirical studies have been published. Further inferences made from such phylogenetic studies critically rely on the pattern of trait evolution. The present work provides a study of the phylogenetic dissimilarity of 96 tree communities in India. The work compares and contrasts eight metrics of phylogenetic dissimilarity, considers the role of phylogenetic signal in trait data and shows that environmental distance rather than spatial distance is the best correlate of phylogenetic dissimilarity in the study system.     

Using generalized dissimilarity modelling to analyse and predict patterns of beta diversity in regional biodiversity assessment

Generalized dissimilarity modelling (GDM) is a statistical technique for analysing and predicting spatial patterns of turnover in community composition (beta diversity) across large regions. The approach is an extension of matrix regression, designed specifically to accommodate two types of nonlinearity commonly encountered in large-scaled ecological data sets: (1) the curvilinear relationship between increasing ecological distance, and observed compositional dissimilarity, between sites; and (2) the variation in the rate of compositional turnover at different positions along environmental gradients. GDM can be further adapted to accommodate special types of biological and environmental data including, for example, information on phylogenetic relationships between species and information on barriers to dispersal between geographical locations. The approach can be applied to a wide range of assessment activities including visualization of spatial patterns in community composition, constrained environmental classification, distributional modelling of species or community types, survey gap analysis, conservation assessment, and climate-change impact assessment.     

Environmental and historical imprints on beta diversity: insights from variation in rates of species turnover along gradients

A common approach for analysing geographical variation in biodiversity involves using linear models to determine the rate at which species similarity declines with geographical or environmental distance and comparing this rate among regions, taxa or communities. Implicit in this approach are weakly justified assumptions that the rate of species turnover remains constant along gradients and that this rate can therefore serve as a means to compare ecological systems. We use generalized dissimilarity modelling, a novel method that accommodates variation in rates of species turnover along gradients and between different gradients, to compare environmental and spatial controls on the floras of two regions with contrasting evolutionary and climatic histories: southwest Australia and northern Europe. We find stronger signals of climate history in the northern European flora and demonstrate that variation in rates of species turnover is persistent across regions, taxa and different gradients. Such variation may represent an important but often overlooked component of biodiversity that complicates comparisons of distance–decay relationships and underscores the importance of using methods that accommodate the curvilinear relationships expected when modelling beta diversity. Determining how rates of species turnover vary along and between gradients is relevant to understanding the sensitivity of ecological systems to environmental change.     

β‐diversity scaling patterns are consistent across metrics and taxa

β‐diversity (variation in community composition) is a fundamental component of biodiversity, with implications for macroecology, community ecology and conservation. However, its scaling properties are poorly understood. Here, we systematically assessed the spatial scaling of β‐diversity using 12 empirical large‐scale datasets including different taxonomic groups, by examining two conceptual types of β‐diversity and explicitly considering the turnover and nestedness components. We found highly consistent patterns across datasets. Multiple‐site β‐diversity (i.e. variation across multiple sites) scaling curves were remarkably consistent, with β‐diversity decreasing with sampled area according to a power law. For pairwise dissimilarities, the rates of increase of dissimilarity with geographic distance remained largely constant across scales, while grain size (or scale level) had a stronger effect on overall dissimilarity. In both analyses, turnover was the main contributor to β‐diversity, following total β‐diversity patterns closely, while the nestedness component was largely insensitive to scale changes. Our results highlight the importance of integrating both inter‐ and intraspecific aggregation patterns across spatial scales, which underpin substantial differences in community structure from local to regional scales.     

Biotic homogenisation and differentiation as directional change in beta diversity: synthesising driver–response relationships to develop conceptual models across ecosystems

Biotic homogenisation is defined as decreasing dissimilarity among ecological assemblages sampled within a given spatial area over time. Biotic differentiation, in turn, is defined as increasing dissimilarity over time. Overall, changes in the spatial dissimilarities among assemblages (termed ‘beta diversity’) is an increasingly recognised feature of broader biodiversity change in the Anthropocene. Empirical evidence of biotic homogenisation and biotic differentiation remains scattered across different ecosystems. Most meta-analyses quantify the prevalence and direction of change in beta diversity, rather than attempting to identify underlying ecological drivers of such changes. By conceptualising the mechanisms that contribute to decreasing or increasing dissimilarity in the composition of ecological assemblages across space, environmental managers and conservation practitioners can make informed decisions about what interventions may be required to sustain biodiversity and can predict potential biodiversity outcomes of future disturbances. We systematically reviewed and synthesised published empirical evidence for ecological drivers of biotic homogenisation and differentiation across terrestrial, marine, and freshwater realms to derive conceptual models that explain changes in spatial beta diversity. We pursued five key themes in our review: (i) temporal environmental change; (ii) disturbance regime; (iii) connectivity alteration and species redistribution; (iv) habitat change; and (v) biotic and trophic interactions. Our first conceptual model highlights how biotic homogenisation and differentiation can occur as a function of changes in local (alpha) diversity or regional (gamma) diversity, independently of species invasions and losses due to changes in species occurrence among assemblages. Second, the direction and magnitude of change in beta diversity depends on the interaction between spatial variation (patchiness) and temporal variation (synchronicity) of disturbance events. Third, in the context of connectivity and species redistribution, divergent beta diversity outcomes occur as different species have different dispersal characteristics, and the magnitude of beta diversity change associated with species invasions also depends strongly on alpha and gamma diversity prior to species invasion. Fourth, beta diversity is positively linked with spatial environmental variability, such that biotic homogenisation and differentiation occur when environmental heterogeneity decreases or increases, respectively. Fifth, species interactions can influence beta diversity via habitat modification, disease, consumption (trophic dynamics), competition, and by altering ecosystem productivity. Our synthesis highlights the multitude of mechanisms that cause assemblages to be more or less spatially similar in composition (taxonomically, functionally, phylogenetically) through time. We consider that future studies should aim to enhance our collective understanding of ecological systems by clarifying the underlying mechanisms driving homogenisation or differentiation, rather than focusing only on reporting the prevalence and direction of change in beta diversity, per se.     

Analyses of multivariately determined community matrices using cluster analysis and multidimensional scaling

Linear discriminant analysis was used to compute the p-variate MACARTHUR-LEVINS and Density Overlap measures of niche overlap between all pairs of 24 passerine bird species. The overlap values for the species pairs were then organized into a community matrix for each approach. The relationships inherent in the community matrices were structured by cluster analysis and non-metric multidimensional scaling. Cluster analysis identified the highly related species groups whereas multidimensional scaling demonstrated community wide relationships. In particular, the scaling approach clearly delineated shrub density and ground cover gradients.     

Rescaling of ecological gradients. I. Calculation of ecological distance between vegetation stands by means of their floristic composition

Geometric models of vegetation (conceptual spaces) are reviewed. Spaces with samples or species as axes are termed flortistic spaces, as opposed to ecological space with environmental gradients as axes. The terms floristic and ecological relationships are defined as relationships in floristic and ecological spaces, respectively. Compositional turnover is pointed out as the essence of ecological gradients, and arguments in favour of measuring ecological distance in units of compositional turnover are given. The most important criteria for evaluation of ecological distance measures are considered to be linear response to separation along ecological gradients and robustness. Theoretical disadvantages of measures of floristic relationships used as ecological distance measures are discussed. A new measure of ecological distance, separation along a DCA ordination axis, is proposed. This measure and four measures of floristic relationships were tested on four simulated coenoclines (high and low beta diversity, high and low noise) using four weighting functions. The new measure was generally superior, particularly with noisy data. The distance measures generally performed best with intermediate weighting of a percentage cover scale. Application of DCA to calculation of ecological distances in multi-gradient systems is briefly discussed. The potential of DCA for rescaling of ecological gradients is emphasized, and some possible applications of rescaling are suggested.     

Does phylogenetic distance aid in detecting environmental gradients related to species composition?

Questions: How should we evaluate the success of new distance measures combining community abundance and phylogenetic information? How do we interpret ordinations using these metrics? Methods: We generated synthetic data along a known environmental gradient with two hypothetical underlying phylogenetic structures: niche phylogenetically conserved or dispersed along a gradient. We also examined tree species composition associated with gradients in elevation and longitude in Oregon, USA. NMS ordinations of plots in species space from phylogenetic (PD) and Sørensen distance (SD) matrices allowed comparison of the use of PD in different scenarios. Results: PD caused plots to cluster based on the clades that they contained, reducing stress with the synthetic data but not with the real example. Phylogenetic distance highlighted clades related to gradients when these were associated. When phylogeny was not conserved along a gradient, that gradient was less strong. Regardless of phylogenetic conservation, NMS using SD consistently extracted the strongest gradients in species composition. Conclusions: The success of PD should be evaluated on how well it extracts gradients in species composition and allows community ecologists to determine which gradients are partially explained by phylogeny and not based on its ability to reduce ordination stress. PD ordinations can help community ecologists interpret niche conservation but may obscure gradients related to species composition when niches are not conserved along the gradient of interest at the scale of the study.     

千岛湖岛屿维管植物β多样性及其影响因素

通过样地调查方法、Jaccard相异性指数、Spearman回归分析和非度量多维标度(NMDS)排序分析,研究了千岛湖154个岛屿上不同植物群落β多样性及其主要影响因素。结果表明不同的景观参数对不同植物生长型有不同程度的影响,其中(1)藤本、灌木的β多样性形成的主导因素是面积,即面积差越大的区域间的β多样性越高;(2)乔木的β多样性主要受到岛屿间距离的限制,岛屿间距离越远,β多样性越高;(3)草本植物的β多样性分布与岛屿面积差及岛屿间距离并未呈现出显著相关,即其分布不受这两种因素限制;(4)NMDS分析结果显示岛屿面积、形状、边缘面积比和岛屿到大陆最小距离等特征对千岛湖岛屿上植物β多样性起决定性的作用。千岛湖陆桥岛屿组成的片段化生境中植物β多样性受扩散限制和生态位假说的共同影响。     

Is spectral distance a proxy of beta diversity at different taxonomic ranks? A test using quantile regression

Beta diversity represents a powerful indicator of ecological conditions because of its intrinsic relation with environmental gradients. In this view, remote sensing may be profitably used to derive models characterizing or estimating species turnover over an area. While several examples exist using spectral variability to estimate species diversity at several spatial scales, most of these have relied on standard correlation or regression approaches like the common Ordinary Least Square (OLS) regression which are problematic with noisy data. Moreover, very few attempts were made to derive beta diversity characterization models at different taxonomic ranks. In this paper, we performed quantile regression to test if spectral distance represents a good proxy of beta diversity considering different data thresholds and taxonomic ranks. We used plant distribution data from the North and South Carolina including 146 counties and covering a variety of vegetation formations. The dissimilarity in species composition at different taxonomic ranks (using Sørensen distance) among pairs of counties was compared with their distance in NDVI values derived from 23 yearly MODIS images. Our results indicate that (i) spectral variability represents a good proxy of beta diversity when appropriate statistics are applied and (ii) a lower taxonomic rank is important when changes in species composition are examined spatially using remotely sensed data.