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.     

Graphical comparison of resemblance measures in phytosociology

A simple graphical method, COREM, is described for the comparison of quantitative resemblance measures. The basis of the method is the ordered comparison case series (OCCAS) composed of relevé pairs ranked in decreasing order of similarity. For a given OCCAS, values of given resemblance functions are calculated and plotted in COREM.Delta resemblance (DR) is defined as the rate of change between two neighbouring relevé pairs in the OCCAS. High mean delta resemblance (% MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqaqpepeea0xe9qqVa0l% b9peea0lb9sq-JfrVkFHe9peea0dXdarVe0Fb9pgea0xa9pue9Fve9% Ffc8meGabaqaciGacaGaaeqabaWaaeaaeaaakeaadaqdaaqaaGqaai% aa-reacaWFsbaaaaaa!392E!\[\overline DR \]) of a resemblance measure indicates a high power of resolution and small standard deviation (SDDR) is indicative of linearity. A measure of efficiency combines % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqaqpepeea0xe9qqVa0l% b9peea0lb9sq-JfrVkFHe9peea0dXdarVe0Fb9pgea0xa9pue9Fve9% Ffc8meGabaqaciGacaGaaeqabaWaaeaaeaaakeaadaqdaaqaaGqaai% aa-reacaWFsbaaaaaa!392E!\[\overline DR \] and SDDR in the coefficient of variation for delta resemblance (CVDR). An efficient measure shows balanced sensitivity to the common and differential species. With the method COREM locally optimal resemblance measures may be selected for any given set of relevés which produce the sharpest separation of clusters. A reasonable compromise is to use types of measures, such as the similarity ratio (SIM6), Czekanowski coefficient (SIM8), or floristic similarity (SIM9), which have the best chance of being successful in most relevé sets. A study of transformation functions on Braun-Blanquet values with the help of COREM demonstrates that the combined transformation is the most advantageous for clustering. It is shown that standardization by relevés, or conversion to unit sum has undesirable effects.During the preparation of this paper the author was a recipient of a Postgraduate Scholarship, Deutscher Akademischer Austauschdients, Dortmund, KFA Abteilung Algenforschung, Germany. The author would like to thank L. Orlóci, P. Juhász-Nagy and E. van der Maarel for valuable suggestions, and comments.     

On resemblance measures for ecological studies, including taxonomic dissimilarities and a zero-adjusted Bray-Curtis coefficient for denuded assemblages

Bray-Curtis similarity is widely employed in multivariate analysis of assemblage data, for sound biological reasons. This paper discusses two problems, however, with its practical application: its behaviour is erratic (or even undefined) for the vanishingly sparse samples that may be found as an end-point to a severe impact gradient, or a start-point in colonisation studies; and, in common with all similarity measures on species-level data, it is sensitive to inconsistency of taxonomic identification through time. It is shown that the latter problem is ameliorated by application of ‘taxonomic dissimilarity’ coefficients, a natural extension of the concept of taxonomic distinctness indices. Two previous suggestions for use with presence/absence data, denoted here by Γ⁺ and Θ⁺, are noted to be simple generalisations of the Bray-Curtis and Kulczynski measures, respectively. Also seen is their ability to permit ordinations of assemblages from wide geographic scales, with no species in common, and for which Bray-Curtis would return zero similarity for all pairs of samples.The primary problem addressed, however, is that of denuded or entirely blank samples. Where it can be convincingly argued that impoverished samples are near-blank from the same cause, rather than by random occurrences from inadequate sample sizes (tow length, core diameter, transect or quadrat size etc.), a simple adjustment to the form of the Bray-Curtis coefficient can generate meaningful MDS displays which would otherwise collapse, and can improve values of the ANOSIM R statistic (increased separation of groups in multivariate space). It is also shown to have no effect at all on the normal functioning of a Bray-Curtis analysis when at least a modest amount of data is present for all samples.Examination of the properties of this ‘zero-adjusted’ Bray-Curtis measure goes hand-in-hand with a wider discussion of the efficacy of competing similarity, distance or dissimilarity coefficients (collectively: resemblance measures) in community ecology. The inherent biological guidelines underlying the ‘Bray-Curtis family’ of measures (including Kulczynski, Sorenson, Ochiai and Canberra dissimilarity) are made explicit. These and other commonly employed measures (e.g. Euclidean, Manhattan, Gower and chi-squared distances) are calculated for several ‘classic’ data sets of impact events or gradients in space and time. Behaviour of particular coefficients is judged against the interpretability of the resulting ordination plots and an objective measure of the ability to discriminate between a priori defined hypotheses, representing impact conditions. A second-stage MDS plot of a set of resemblance coefficients, based on the respective similarities of the multivariate patterns each generates (an MDS of MDS plots, in effect), is seen to be useful in determining which coefficients are extracting essentially different information from the same assemblage matrix. This suggests a mechanism for practical classification of the plethora of resemblance measures defined in the literature. Similarity-based ANOSIM R statistics and Spearman ρ correlations, whose non-parametric structure make them absolutely comparable across different resemblance measures, answer questions about whether the different information extracted by some coefficients is more, or less, helpful to the final biological interpretation.     

Selection of Students for Admission to Medical School: A Two-Class Decision Approach

The validity coefficient alone does not communicate sufficient information to estimate the errors in decisions to accept or reject candidates. By means of probability theory, it is demonstrated how information concerning errors in decisions may be estimated. With estimates of the frequencies of correct and incorrect decisions and the costs of such decisions, a utility index was defined, for which a minimum was sought as a function of the entrance requirement. Under the analytic criterion defined for utility, it was possible to determine for a number of cost systems the entrance score which would, in the long run, reduce losses to a minimum. The application of the model is illustrated using empirical data and hypothetical cost systems. For these data entrance requirements were determined according to the criterion in addition to selection ratios and probabilities of success.     

A framework for estimating niche metrics using the resemblance between qualitative resources

Despite the central importance of the niche concept for the ecological theory, current methods to quantify the species niche from qualitative resources, such as food or habitat types, remain insufficiently developed. Classically, information theory and diversity measures have formed the toolbox used for calculating resource niche metrics on species preference data for a set of qualitative resources. We provide a comprehensive framework that extends these classical approaches by incorporating the resemblance between resources into the calculation of resource niche metrics. This does not only allow estimation of the niche centre, breadth, overlap and displacement with greater accuracy, but also makes the estimates less influenced by the way the resources are subdivided. In addition, all niche metrics can be calculated while taking into account the variation in resource availability, and confidence intervals can be obtained by bootstrapping. We illustrate the utility of the framework with an analysis of dietary preferences in feral pigeons Columba livia.     

A disequilibrium coefficient approach to Hardy-Weinberg testing

A comparison was made of various tests for Hardy-Weinberg equilibrium, with emphasis on methods for multiple alleles. For an overall test of deviations from equilibrium, the classical chi-square goodness-of-fit test generally performs well, with continuity corrections needed for extreme gene frequencies or extreme departures from equilibrium. For small samples, probability tests are preferable and for multiple alleles these probability tests may be performed on a sample of all possible sets of genotypic frequencies having a fixed set of sample gene frequencies. Numerical work showed that the continuity-corrected chi-square was the most conservative test procedure, and the uncorrected chi-square the least conservative. With multiple alleles, a better appreciation of the nature of departures from equilibrium is given by the use of disequilibrium coefficients, defined for each heterozygote as the difference between observed and expected frequencies. Likelihood-ratio tests can be used to test each of these coefficients individually but a satisfactory procedure is to divide the squared estimate of each coefficient by its estimated variance and regard the ratio as a single-degree-of-freedom chi-square. Numerical studies confirmed the validity of this approach, which has the great advantage of not requiring solutions of nonlinear equations.     

Extended dissimilarity: a method of robust estimation of ecological distances from high beta diversity data

It is widely accepted that reliable ordination of ecological data requires a strong linear or ordinal relationship between the dissimilarity of sites, based on species composition, and the ecological distance between them. Certain dissimilarity measures, having the property that they take a fixed maximum value when sites have no species in common, have been shown to be strongly correlated with ecological distance. For ecological gradients of moderate length (moderate beta diversity), such measures, in conjunction with non-metric multidimensional scaling, will reliably yield successful ordinations. However, as beta diversity increases, more sites have no species in common, and such measures invariably under-estimate ecological distance for such sites. Thus ordinations of data with high species turnover (high beta diversity) may fail.Extended dissimilarities are defined using an iterative adaptation of flexible shortest path adjustment applied to the matrix of dissimilarities with fixed maximum values. By means of theoretical argument and simulations, this is shown to lead to far stronger correlations between the adjusted site dissimilarity and ecological distance for ecological gradients of greater length than previously considered. Hence ordinations of extended dissimilarities, by means of either metric or non-metric scaling techniques, are shown to outperform corresponding ordinations of unadjusted dissimilarities, with the difference increasing with increasing beta diversity.     

Count-dependent filter for smoothing bivariate FCM histograms

A data-smoothing filter has been developed that permits the improvement in accuracy of individual elements of a bivariate flow cytometry (FCM) histogram by making use of data from adjacent elements, a knowledge of the two-dimensional measurement system point spread function (PSF), and the local count density. For FCM data, the PSF is assumed to be a set of two-dimensional Gaussian functions with a constant coefficient of variation for each axis. A set of space variant smoothing kernels are developed from the basic PSF by adjusting the orthogonal standard deviations of each Gaussian smoothing kernel according to the local count density. This adjustment in kernel size matches the degree of smoothing to the local reliability of the data. When the count density is high, a small kernel is sufficient. When the density is low, however, a broader kernel should be used. The local count density is taken from a region defined by the measurement PSF. The smoothing algorithm permits the reduction in statistical fluctuations present in bivariate FCM histograms due to the low count densities often encountered in some elements. This reduction in high-frequency spatial noise aids in the visual interpretation of the data. Additionally, by making more efficient use of smaller samples, systematic errors due to system drift may be minimized.     

A computational approach to measuring coherence of gene expression in pathways

This study uses a computational approach to analyze coherence of expression of genes in pathways. Microarray data were analyzed with respect to coherent gene expression in a group of genes defined as a pathway in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Our hypothesis is that genes in the same pathway are more likely to be coordinately regulated than a randomly selected gene set. A correlation coefficient for each pair of genes in a pathway was estimated based on gene expression in normal or tumor samples, and statistically significant correlation coefficients were identified. The coherence indicator was defined as the ratio of the number of gene pairs in the pathway whose correlation coefficients are significant, divided by the total number of gene pairs in the pathway. We defined all genes that appeared in the KEGG pathways as a reference gene set. Our analysis indicated that the mean coherence indicator of pathways is significantly larger than the mean coherence indicator of random gene sets drawn from the reference gene set. Thus, the result supports our hypothesis. The significance of each individual pathway of n genes was evaluated by comparing its coherence indicator with coherence indicators of 1000 random permutation sets of n genes chosen from the reference gene set. We analyzed three data sets: two Affymetrix microarrays and one cDNA microarray. For each of the three data sets, statistically significant pathways were identified among all KEGG pathways. Seven of 96 pathways had a significant coherence indicator in normal tissue and 14 of 96 pathways had a significant coherence indicator in tumor tissue in all three data sets. The increase in the number of pathways with significant coherence indicators may reflect the fact that tumor cells have a higher rate of metabolism than normal cells. Five pathways involved in oxidative phosphorylation, ATP synthesis, protein synthesis, or RNA synthesis were coherent in both normal and tumor tissue, demonstrating that these are essential genes, a high level of expression of which is required regardless of cell type.     

Biological adaptations for functional features of language in the face of cultural evolution

Although there may be no true language universals, it is nonetheless possible to discern several family resemblance patterns across the languages of the world. Recent work on the cultural evolution of language indicates the source of these patterns is unlikely to be an innate universal grammar evolved through biological adaptations for arbitrary linguistic features. Instead, it has been suggested that the patterns of resemblance emerge because language has been shaped by the brain, with individual languages representing different but partially overlapping solutions to the same set of nonlinguistic constraints. Here, we use computational simulations to investigate whether biological adaptation for functional features of language, deriving from cognitive and communicative constraints, may nonetheless be possible alongside rapid cultural evolution. Specifically, we focus on the Baldwin effect as an evolutionary mechanism by which previously learned linguistic features might become innate through natural selection across many generations of language users. The results indicate that cultural evolution of language does not necessarily prevent functional features of language from becoming genetically fixed, thus potentially providing a particularly informative source of constraints on cross-linguistic resemblance patterns.     

Extraction of symbolic determinants common to a family of biological sequences

A set of sequences can be defined by their common subsequences, and the length of these is a measure of the overall resemblance of the set. Each subsequence corresponds to a succession of symbols embedded in every sequence, following the same order but not necessarily contiguous. Determining the longest common subsequence (LCS) requires the exhaustive testing of all possible common subsequences, which sum up to about 2L, if L is the length of the shortest sequence. We present a polynomial algorithm (O(n X L4), where n is the number of sequences) for generating strings related to the LCS and constructed with the sequence alphabet and an indetermination symbol. Such strings are iteratively improved by deleting indetermination symbols and concomitantly introducing the greatest number of alphabet symbols. Processed accordingly, nucleic acid and protein sequences lead to key-words encompassing the salient positions of homologous chains, which can be used for aligning or classifying them, as well as for finding related sequences in data banks.     

Spectral analysis of a Plio-Pleistocene multispecies time series using the Mantel periodogram

A simple method for the spectral analysis of multispecies microfossil data through time or stratigraphic level is presented. The method is based on the Mantel correlogram, allowing any ecological similarity measure to be used. The method can therefore be applied to binary (presence-absence) data as well as raw or normalized species counts. In contrast with spectral analysis of univariate ordination scores, this approach does not explicitly discard information. The method, referred to as the Mantel periodogram, is exemplified with a data set from the literature, demonstrating several astronomically forced periodicities in microfaunal data from the Plio-Pleistocene.     

Does the aardwolf mimic a hyena?

A recent suggestion that the visual resemblance of the Aardwolf to the Striped Hyena may have been evolved as Batesian mimicry is critically examined. But the fact that the close similarity in appearance (apart from size) between these two species appears to be just as good in southern Africa, where the Striped Hyena does not occur, being replaced by the Brown Hyena which does not look much like an aardwolf, argues against the mimicry hypothesis. It seems more likely that the resemblance is due simply to close phylogenetic relationship, both species having retained the cryptic coloration of a common ancestor, together with its erectile dorsal crest, used for threat display as in many other mammals.     

A new metric for evaluating the correspondence of spatial patterns in vegetation models

Aim  To present a new metric, the 'opposite and identity' (OI) index, for evaluating the correspondence between two sets of simulated time-series dynamics of an ecological variable.
Innovation  The OI index is introduced and its mathematical expression is defined using vectors to denote simulated variations of an ecological variable on the basis of the vector addition rule. The value of the OI index varies from 0 to 1 with a value 0 (or 1) indicating that compared simulations are opposite (or identical). An OI index with a value near 0.5 suggests that the difference in the amplitudes of variations between compared simulations is large. The OI index can be calculated in a grid cell, for a given biome and for time-series simulations. The OI indices calculated in each grid cell can be used to map the spatial agreement between compared simulations, allowing researchers to pinpoint the extent of agreement or disagreement between two simulations. The OI indices calculated for time-series simulations allow researchers to identify the time at which one simulation differs from another. A case study demonstrates the application and reliability of the OI index for comparing two simulated time-series dynamics of terrestrial net primary productivity in Asia from 1982 to 2000. In the case study, the OI index performs better than the correlation coefficient at accurately quantifying the agreement between two simulated time-series dynamics of terrestrial net primary productivity in Asia.
Main conclusions  The OI index provides researchers with a useful tool and multiple flexible ways to compare two simulation results or to evaluate simulation results against observed spatiotemporal data. The OI index can, in some cases, quantify the agreement between compared spatiotemporal data more accurately than the correlation coefficient because of its insensitivity to influential data and outliers and the autocorrelation of simulated spatiotemporal data.     

Similarity of mammalian body size across the taxonomic hierarchy and across space and time

Although it is commonly assumed that closely related animals are similar in body size, the degree of similarity has not been examined across the taxonomic hierarchy. Moreover, little is known about the variation or consistency of body size patterns across geographic space or evolutionary time. Here, we draw from a data set of terrestrial, nonvolant mammals to quantify and compare patterns across the body size spectrum, the taxonomic hierarchy, continental space, and evolutionary time. We employ a variety of statistical techniques including "sib-sib" regression, phylogenetic autocorrelation, and nested ANOVA. We find an extremely high resemblance (heritability) of size among congeneric species for mammals over approximately 18 g; the result is consistent across the size spectrum. However, there is no significant relationship among the body sizes of congeneric species for mammals under approximately 18 g. We suspect that life-history and ecological parameters are so tightly constrained by allometry at diminutive size that animals can only adapt to novel ecological conditions by modifying body size. The overall distributions of size for each continental fauna and for the most diverse orders are quantitatively similar for North America, South America, and Africa, despite virtually no overlap in species composition. Differences in ordinal composition appear to account for quantitative differences between continents. For most mammalian orders, body size is highly conserved, although there is extensive overlap at all levels of the taxonomic hierarchy. The body size distribution for terrestrial mammals apparently was established early in the Tertiary, and it has remained remarkably constant over the past 50 Ma and across the major continents. Lineages have diversified in size to exploit environmental opportunities but only within limits set by allometric, ecological, and evolutionary constraints.     

Accounting for non-independence of extinction probabilities in the derivation of conservation priorities based on Weitzman’s diversity concept

In the original formulation of Weitzman’s diversity concept, extinction probabilities of different operational taxonomic units (OTUs) are implicitly defined to be independent. In this study, it is shown, that dependencies like concurrence or synergistic relations between OTUs can be accounted for by assuming that joint extinction probabilities differ from the product of the extinction probabilities of the interacting OTUs. A fully analytical treatment is provided for the case of two interacting OTUs, and all cases are illustrated with an example data set. For the case of concurring OTUs, the following general results are derived: (a) concurrence between OTUs always reduces the amount of diversity expected to be conserved in the future; (b) concurrence has a more adverse effect on the more endangered OTUs involved; (c) concurrence can change conservation priorities between OTUs; and (d) with high levels of concurrence, investments in the conservation of some of the concurring OTUs can have a negative effect on the overall diversity conserved. In addition to conservation activities targeted towards some of the OTUs, reduction of the causes of concurrence may be a valid and cost-efficient alternative. For the case of synergistic dependencies between OTUs it was found, that such dependencies always increase the conservation potential of the involved OTUs but may lead to a change of priority ranking in extreme cases. Finally possible extensions and generalisations of the suggested approach are discussed and it is argued, that by adopting these extensions Weitzman’s diversity concept becomes an even more powerful and flexible tool to derive conservation priorities both in an ecological and in a farm animal context.     

Parasites, ecosystems and sustainability: an ecological and complex systems perspective

Host-parasite relationships can be conceptualised either narrowly, where the parasite is metabolically dependent on the host, or more broadly, as suggested by an ecological-evolutionary and complex systems perspective. In this view Host-parasite relationships are part of a larger set of ecological and co-evolutionary interdependencies and a complex adaptive system. These interdependencies affect not just the hosts, vectors, parasites, the immediate agents, but also those indirectly or consequentially affected by the relationship. Host-parasite relationships also can be viewed as systems embedded within larger systems represented by ecological communities and ecosystems. So defined, it can be argued that Host-parasite relationships may often benefit their hosts and contribute significantly to the structuring of ecological communities. The broader, complex adaptive system view also contributes to understanding the phenomenon of disease emergence, the ecological and evolutionary mechanisms involved, and the role of parasitology in research and management of ecosystems in light of the apparently growing problem of emerging infectious diseases in wildlife and humans. An expanded set of principles for integrated parasite management is suggested by this perspective.     

Academic performance in Hawaii

Abstract

Differences among census tracts in academic performance are estimated and related by path analysis to social class, race, and school characteristics in the only American state without local autonomous school districts. Contrary to the Coleman Report, school has a significant effect and race does not, but social class is the major cause of census tract difference in academic performance. Without appropriate data on family resemblance, a genetic component in class structure cannot be delineated.     

The U.S. Environmental Protection Agency's Generic Ecological Assessment Endpoints

The U.S. Environmental Protection Agency determined that one of the major impediments to the advancement and application of ecological risk assessment is doubt concerning appropriate assessment endpoints. The Agency's Risk Assessment Forum determined that the best solution to this problem was to define a set of generic ecological assessment endpoints (GEAEs). They are assessment endpoints that are applicable to a wide range of ecological risk assessments; because they reflect the programmatic goals of the Agency, they are applicable to a wide array of environmental issues, and they may be estimated using existing assessment tools. They are not specifically defined for individual cases; some ad hoc elaboration by users is expected. The GEAEs are not exhaustive or mandatory. Although most of the Agency's ecological decisions have been based on organism-level effects, GEAEs are also defined for populations, ecosystems, and special places.     

Family resemblance for anthropometric and blood pressure measurements in Black Caribs and Creoles from St. Vincent Island

This paper examines family resemblance for five anthropometric measurements (height, weight, triceps skinfold, upper arm circumference relaxed [UACR] and flexed [UACF] and for systolic and diastolic blood pressure in a group of adult Caribbean islanders of primarily African ancestry. Six hypotheses about family resemblance are tested by using path analysis and likelihood ratios. Significant intergenerational transmission is found only for height and UACR. For weight, UACF, and diastolic blood pressure, non-transmissible sibling resemblance is the primary component of family resemblance, although significant marital resemblance exists for diastolic blood pressure. Triceps skinfold and systolic blood pressure show no evidence of any family resemblance. Although results for highly heritable traits such as height are comparable to reports from other populations, measurements with a large contribution from common family environment or residual environmental effects, such as triceps skinfold or blood pressure, have much lower family resemblance in this population than in other populations. We hypothesize that this difference is due to the fact that adult children and their parents do not share a common household in this culture and to the presence of major nonfamilial environmental factors contributing to obesity and hypertension in this population.