Clusterings should not be compared by visual inspection: response to Gagné & Proulx

In Heikinheimo et al . ( Journal of Biogeography , 2007, 34 , 1053–1064) we used clustering to analyse European land mammal fauna. Gagné & Proulx criticized our choice of the Euclidean distance measure in the analysis, and advocated the use of the Hellinger distance measure, claiming that this leads to very different clustering results. The criticism fails to take into account the probabilistic nature of the methods used and the fact that in this case the similarity measures correlate strongly. Gagné & Proulx used subjective inspection as the criterion of similarity between clusterings. We show that this is insufficient and misleading. Namely, owing to the local minimum problem, two clustering runs rarely give identical results. In the case of our study, the measured similarity (using the kappa statistic) between the Euclidean- and Hellinger-based clusterings is roughly equal to the similarity between two clusterings that both use the Hellinger distance but different random initialization points.     

Gauging scale effects and biogeographical signals in similarity distance decay analyses: an Early Jurassic ammonite case study

In biogeography, the similarity distance decay (SDD) relationship refers to the decrease in compositional similarity between communities with geographical distance. Although representing one of the most widely used relationships in biogeography, a review of the literature reveals that: (1) SDD is influenced by both spatial extent and sample size; (2) the potential effect of the phylogenetic level has yet to be tested; (3) the effect of a marked biogeographical structuring upon SDD patterns is largely unknown; and (4) the SDD relationship is usually explored with modern, mainly terrestrial organisms, whereas fossil taxa are seldom used in that perspective. Using this relationship, we explore the long‐distance dispersal of the Early Jurassic (early Pliensbachian, c. 190.8 Ma to 187.6 Ma) ammonites of the western Tethys and adjacent areas, in a context of marked provincialism. We show that the long‐distance dispersal of these ammonites is not related to shell size and shape, but rather to the environmental characteristics of the province to which they belong. This suggests that their long‐distance dispersal may have been essentially driven by passive planktonic drift during early juvenile, post‐hatching stages. Furthermore, it seems that the SDD relationship is not always an appropriate method to characterize the existence of a biogeographical structuring. We conducted SDD analyses at various spatial, sampling and phylogenetic scales in order to evaluate their sensitivity to scale effects. This multi‐scale approach indicates that the sampling scale may influence SDD rates in an unpredictable way and that the phylogenetic level has a major impact on SDD patterns.     

Examining genetic structure in a bogus yucca moth: a sequential approach to phylogeography

Understanding the phylogeography of a species requires not only elucidating patterns of genetic structure among populations, but also identifying the possible evolutionary events creating that structure. The use of a single phylogeographic test or analysis, however, usually provides a picture of genetic structure without revealing the possible underlying evolutionary causes. We used current analytical techniques in a sequential approach to examine genetic structure and its underlying causes in the bogus yucca moth Prodoxus decipiens (Lepidoptera: Prodoxidae). Both historical biogeography and recent human transplantations of the moth's host plants provided a priori expectations of the pattern of genetic structure and its underlying causes. We evaluated these expectations by using a progression of phylogenetic, demographic, and population genetic analyses of mtDNA sequence data from 476 individuals distributed across 25 populations that encompassed the range of P. decipiens. The combination of these analyses revealed that much of the genetic structure has evolved more recently than suggested by historical biogeography, has been influenced by changes in demography, and can be best explained by long distance dispersal and isolation by distance. We suggest that performing a suite of analyses that focus on different temporal scales may be an effective approach to investigating the patterns and causes of genetic structure within species.     

Do Geographically Isolated Grasslands Follow the Principle of Island Biogeography in a Landscape Scale? Taking Poyang Lake Grassland as an Example

As one of the basic theories of biodiversity conservation, island biogeography has been widely accepted in the past decades. Originally, island biogeography was put forward and applied in oceanic environments. But later on, it was found out that the application was not only limited to oceanic islands, but also in terrestrial environments with relatively isolated conditions. In terms of biodiversity level, island biogeography generally focuses on a small scale, such as species diversity and genetic diversity. The studies of biodiversity on a large-scale based on island biogeography, such as ecosystem and landscape scales, were seldomly conducted. Taking Poyang Lake, the largest fresh water lake in China as case study area, 30 grasslands were randomly selected to study whether island biogeography can be applied to grasslands at a landscape level from three island attributes (area, distance and shape), and the most important ecological variable (flooding) in Poyang Lake. The results showed that in general, grasslands have the property of an island, and follow the basic principle of island biogeography. We found the area and flooding duration were the two most important determinants of landscape diversity. There was a significant positive correlation between the grassland area and the landscape diversity, which could be well expressed by logarithmic function model (R² = 0.73). There was a negative correlation between flooding duration and landscape diversity, which could be described by an inverse model (R² = 0.206). The distance to mainland and the shape of grassland were correlated with landscape diversity, but the fitting result of the models was not as good as expected. The possible reason could be that Poyang Lake is a seasonal lake, the water level varies with hydrological conditions, so that the grasslands are not strongly isolated and their shape is not stable enough required by island biogeography. Furthermore, it indicates that besides area, distance and shape attributes, flooding strongly affects the biodiversity of grassland vegetation, and should not be ignored when applying island biogeography theory to Poyang Lake. This study is expected to be a supplement for island biogeography in terrestrial environments, and the results are expected to benefit for the biodiversity conservation in Poyang Lake.     

大数据时代土壤微生物地理学研究综述

土壤蕴含极为丰富的微生物多样性,它们在物质分解、元素生物地球化学循环、植物生产力和生物健康中扮演着关键角色。理解土壤微生物的生物地理分布格局、形成机制与群落构建规则,有助于预测在全球变化背景下土壤微生物组的功能演变及其对陆地生态系统的调控影响。自21世纪以来,土壤微生物生物地理学在各种大型国际微生物计划的推动下逐步形成了分子生物学技术耦合大数据分析的模式,实现了多种尺度上的关联研究。阐述了土壤微生物在分布格局和群落构建规则方面的研究进展,重点介绍了分子生物学技术和大数据分析在土壤微生物生物地理研究中的应用,对土壤微生物生物地理学未来在微生物分类分辨率、模型验证与构建和功能基因地理学的发展方向进行了展望。     

丛枝菌根真菌生物地理学研究进展

丛枝菌根真菌(arbuscular mycorrhizal fungi,AMF)普遍存在于陆地生态系统中,能与绝大多数高等植物形成菌根共生体系。AMF能够促进植物对矿质养分的吸收,增强植物的抗逆能力,在维持生态系统稳定性和生产力中发挥着重要作用。AMF生物地理学主要研究AMF的生物地理分布格局和群落构建机制,对于理解AMF在不同生态系统中的重要性至关重要。总结了AMF生物地理学最新研究进展及研究方法,提出了AMF生物地理学研究理论框架。认为AMF在自然界中并非简单随机分布,宿主植物、地理因子、气候因子和土壤因子共同决定AMF的群落结构,不同尺度下的AMF群落构建符合生态位-中性连续统假说,但在不同尺度下这些驱动因子的相对重要性不同。在全球尺度和区域尺度下,AMF的地理分布格局主要受地理距离和气候因子的影响,中性理论的作用大于生态位理论。随着空间尺度的缩减,宿主植物和环境因子对AMF群落的影响胜过地理距离和扩散限制的作用,生态位理论取代中性理论在AMF群落构建中的主导地位。此外,很多研究发现,同一生境中AMF的群落构建机制并非一成不变,会随环境的变化而发生改变。在未来的研究中,应在野外调查和公共数据库的基础上加强整合分析和数据挖掘工作,从而进一步丰富和完善AMF生物地理学理论。     

Dispersal,niche, and isolation processes jointly explain species turnover patterns of nonvolant small mammals in a large mountainous region of China

Understanding the mechanisms that govern the spatial patterns of species turnover (beta diversity) has been one of the fundamental issues in biogeography. Species turnover is generally recognized as strong in mountainous regions, but the way in which different processes (dispersal, niche, and isolation) have shaped the spatial turnover patterns in mountainous regions remains largely unexplored. Here, we explore the directional and elevational patterns of species turnover for nonvolant small mammals in the Hengduan Mountains of southwest China and distinguish the relative roles of geographic distance, environmental distance, and geographic isolation on the patterns. The spatial turnover was assessed using the halving distance (km), which was the geographic distance that halved the similarity (Jaccard similarity) from its initial value. The halving distance was calculated for the linear, logarithmic, and exponential regression models between Jaccard similarity and geographic distance. We found that the east–west turnover is generally faster than the south–north turnover for high‐latitudinal regions in the Hengduan Mountains and that this pattern corresponds to the geographic structure of the major mountain ranges and rivers that mainly extend in a south–north direction. There is an increasing trend of turnover toward the higher‐elevation zones. Most of the variation in the Jaccard similarity could be explained by the pure effect of geographic distance and the joint effects of geographic distance, environmental distance, and average elevation difference. Our study indicates that dispersal, niche, and isolation processes are all important determinants of the spatial turnover patterns of nonvolant small mammals in the Hengduan Mountains. The spatial configuration of the landscape and geographic isolation can strongly influence the rate of species turnover in mountainous regions at multiple spatial scales.     

Inferential Clustering Approach for Microarray Experiments with Replicated Measurements

Cluster analysis has proven to be a useful tool for investigating the association structure among genes in a microarray data set. There is a rich literature on cluster analysis and various techniques have been developed. Such analyses heavily depend on an appropriate (dis)similarity measure. In this paper, we introduce a general clustering approach based on the confidence interval inferential methodology, which is applied to gene expression data of microarray experiments. Emphasis is placed on data with low replication (three or five replicates). The proposed method makes more efficient use of the measured data and avoids the subjective choice of a dissimilarity measure. This new methodology, when applied to real data, provides an easy-to-use bioinformatics solution for the cluster analysis of microarray experiments with replicates (see the Appendix). Even though the method is presented under the framework of microarray experiments, it is a general algorithm that can be used to identify clusters in any situation. The method's performance is evaluated using simulated and publicly available data set. Our results also clearly show that our method is not an extension of the conventional clustering method based on correlation or euclidean distance.     

A system dynamics model of island biogeography

The MacArthur-Wilson equilibrium theory of island biogeography has been one of the more influential concepts in modern biogeography and ecology. In this paper, we synthesize the theory and examine effects of different immigration/extinction rate-species diversity curves on original predictions from the theory by using the System Dynamics simulation modeling approach. Moreover, we develop a comprehensive and generic System Dynamics model to incorporate a variety of recent modifications and extensions of the theory, including area effect, distance effect, competition effect, habitat diversity effect, target effect, and rescue effect. Through computer simulation with STELLA, a more profound understanding of the theory of island biogeography can be gained. The System Dynamics modeling approach is especially appropriate for such a study because it maximizes the utilization of the ecological data by incorporating qualitative information so that a complex, imprecisely-defined ecological system can be studied quantitatively, effectively, and comprehensively. Our simulation results show that different monotonic rate-species diversity curves do not affect the essence of the theory of island biogeography, while the magnitude of equilibrium species diversity may be greatly affected. Non-monotonic rate-species diversity curves may result in potential multiple equilibria of species diversity. In addition, our model suggests that a non-monotonic relationship may exist between the equilibrium turnover rate and island area and between the equilibrium turnover rate and distance.     

Biases with the Generalized Euclidean Distance measure in disparity analyses with high levels of missing data

The Generalized Euclidean Distance (GED) measure has been extensively used to conduct morphological disparity analyses based on palaeontological matrices of discrete characters. This is in part because some implementations allow the use of morphological matrices with high percentages of missing data without needing to prune taxa for a subsequent ordination of the data set. Previous studies have suggested that this way of using the GED may generate a bias in the resulting morphospace, but a detailed study of this possible effect has been lacking. Here, we test whether the percentage of missing data for a taxon artificially influences its position in the morphospace, and if missing data affects pre‐ and post‐ordination disparity measures. We find that this use of the GED creates a systematic bias, whereby taxa with higher percentages of missing data are placed closer to the centre of the morphospace than those with more complete scorings. This bias extends into pre‐ and post‐ordination calculations of disparity measures and can lead to erroneous interpretations of disparity patterns, especially if specimens present in a particular time interval or clade have distinct proportions of missing information. We suggest that this implementation of the GED should be used with caution, especially in cases with high percentages of missing data. Results recovered using an alternative distance measure, Maximum Observed Rescaled Distance (MORD), are more robust to missing data. As a consequence, we suggest that MORD is a more appropriate distance measure than GED when analysing data sets with high amounts of missing data.     

Does size matter for dispersal distance?

Aim The aim of this study is to answer the questions: (1) do small organisms disperse farther than large, or vice versa; and (2) does the observed pattern differ for passive and active dispersers? These questions are central to several themes in biogeography (including microbial biogeography), macroecology, metacommunity ecology and conservation biology. Location The meta‐analysis was conducted using published data collected worldwide. Methods We collected and analysed 795 data values in the peer‐reviewed literature for direct observations of both maximal dispersal distance and mass of the dispersing organisms (e.g. seeds, not trees). Analysed taxa ranged in size from bacteria to whales. We applied macroecology analyses based on null models (using Monte Carlo randomizations) to test patterns relative to specific hypotheses. Results Collected dispersal distance and mass data spanned 9 and 21 orders of magnitude, respectively. Active dispersers dispersed significantly farther (P < 0.001) and were significantly greater in mass (P < 0.001) than passive dispersers. Overall, size matters: larger active dispersers attained greater maximum observed dispersal distances than smaller active dispersers. In contrast, passive‐disperser distances were random with respect to propagule mass, but not uniformly random, in part due to sparse data available for tiny propagules. Conclusions Size is important to maximal dispersal distance for active dispersers, but not for passive dispersers. Claims that microbes disperse widely cannot be tested by current data based on direct observations of dispersal: indirect approaches will need to be applied. Distance–mass relationships should contribute to a resolution of neutral and niche‐based metacommunity theories by helping scale expectations for dispersal limitation. Also, distance–mass relationships should inform analyses of latitudinal species richness and conservation biology topics such as fragmentation, umbrella species and taxonomic homogenization.     

Seed dispersal distance classes and dispersal modes for the European flora

Motivation

Although dispersal ability is one of the key features determining the spatial dynamics of plant populations and the structure of plant communities, it is also one of the traits for which we still lack data for most species. We compiled a comprehensive dataset of seed dispersal distance classes and predominant dispersal modes for most European vascular plants. Our seed dispersal dataset can be used in functional biogeography, dynamic vegetation modelling and ecological studies at local to continental scales.

Main Types of Variables Contained

Species were classified into seven ordered classes with similar dispersal distances estimated based on the predominant dispersal mode, the morphology of dispersal units (diaspores or propagules), life form, plant height, seed mass, habitat and known dispersal by humans. We evaluated our results by comparing them with dispersal distances calculated using the ‘dispeRsal’ function in R.

Spatial Location

Europe.

Time Period

Present.

Major Taxa and Level of Measurement

The seed dispersal dataset contains information on dispersal distance classes and the predominant dispersal mode for 10,327 most frequent and locally dominant European vascular plant species.

Software Format

Data are available in .csv format.     

Line Transect Sampling in Small and Large Regions

Melville and Welsh (2001, Biometrics 57, 1130-1137) consider an approach to line transect sampling using a separate calibration study to estimate the detection function g. They present a simulation study contrasting their results with poor results from a traditional estimator, labeled the "Buckland" estimator and referenced to Buckland et al. (1993, Distance Sampling: Estimating Abundance of Biological populations). The poor results from the "Buckland" estimator can be explained by the following observations: (i) the estimator is designated for untruncated distance data, but was applied by Melville and Welsh to truncated distance data; (ii) distance data were not pooled across transects, contrary to standard practice; and (iii) bias of the estimator was evaluated with respect to a fixed rather than a randomized grid of transect lines. We elaborate on the points above and show that the traditional methods perform to expectation when applied correctly. We also emphasize that the estimator labeled the "Buckland" estimator by Melville and Welsh is not an estimator recommended by Buckland et al. for practical survey applications.     

Estimation of Reversible Substitution Matrices from Multiple Pairs of Sequences

We present a method for estimating the most general reversible substitution matrix corresponding to a given collection of pairwise aligned DNA sequences. This matrix can then be used to calculate evolutionary distances between pairs of sequences in the collection. If only two sequences are considered, our method is equivalent to that of Lanave et al. (1984). The main novelty of our approach is in combining data from different sequence pairs. We describe a weighting method for pairs of taxa related by a known tree that results in uniform weights for all branches. Our method for estimating the rate matrix results in fast execution times, even on large data sets, and does not require knowledge of the phylogenetic relationships among sequences. In a test case on a primate pseudogene, the matrix we arrived at resembles one obtained using maximum likelihood, and the resulting distance measure is shown to have better linearity than is obtained in a less general model.     

Dissimilarity for partially ranked data and its application to cover-abundance data

Cover-abundance estimates are commonly employed in phytosociological investigations to record the performance of species. Because the coded values are on an ordinal scale of measure, various authors have suggested that some transformation is necessary before such values can be used for classification and ordination. However, it is not clear that transformation is a sufficient treatment, and it would seem preferable to use ordinal data directly. In this paper we examine such direct use of partial rankings and show that several dissimilarity measures can be defined for this case without invoking any transformations. They include dissimilarity measures associated with various rank correlation measures and with distances between strings; all the measure are variant forms of Hausdorf's interset distance. Certain other kinds of data, such as those employing dominant and subdominant species and the dry-weight-rank estimation of biomass, are also on an ordinal scale and could be analysed using similar techniques.To illustrate the approach, a string dissimilarity measure is used to analyse a set of data from Slovakian grasslands which appear to reflect a simple gradient. The original data were recorded with 10 classes of performance and are analysed using hierarchical and nondeterministic, overlapping, classifications.     

Inference of kinship coefficients from Korean SNP genotyping data

The determination of relatedness between individuals in a family is crucial in analysis of common complex diseases. We present a method to infer close inter-familial relationships based on SNP genotyping data and provide the relationship coefficient of kinship in Korean families. We obtained blood samples from 43 Korean individuals in two families. SNP data was obtained using the Affymetrix Genome-wide Human SNP array 6.0 and the Illumina Human 1M-Duo chip. To measure the kinship coefficient with the SNP genotyping data, we considered all possible pairs of individuals in each family. The genetic distance between two individuals in a pair was determined using the allele sharing distance method. The results show that genetic distance is proportional to the kinship coefficient and that a close degree of kinship can be confirmed with SNP genotyping data. This study represents the first attempt to identify the genetic distance between very closely related individuals. [BMB Reports 2013; 46(6): 305-309]     

Effect of Approaching Boats on Nesting Black Skimmers: Using Response Distances to Establish Protective Buffer Zones

ABSTRACT Understanding how birds respond to the activities of people is an important component of conserving wildlife. We measured responses of nesting black skimmers (Rynchops niger) to an approaching boat in Barnegat Bay, New Jersey, USA, by examining distance to first respond, distance to flush, and time to return to the colony. Our objective was to determine if response distances of skimmers changed as a function of year, reproductive stage, direction of approach (direct or tangential), or number of birds nesting in the colony. Generally, reproductive stage had the greatest effect on all responses, followed by direction of approach, number of adults present at the colony, number of nests, and year, which also explained variation in behavioral responses. The distance at which skimmers first flew when a boat approached decreased from the pre-egg-laying period to hatching, and then increased slightly later in the season. Time (x̄± SE) for skimmers to return to the nesting colony varied seasonally, with birds taking longer to return during the pre-egg period (9.5 ± min) than during hatching (0.7 ± 0.1 min). The decision process for determining set-back distances to protect nesting skimmers should involve selecting 1) behavioral response of highest concern, 2) reproductive stage of highest concern, and 3) an appropriate level of response at which to establish the buffer area. We recommend that managers use a set-back distance of ± 118 m from the perimeter of the colony for black skimmers, which is the 95% percentile of the distance that skimmers first flew in response to approaching boats. Managers can use these data to set buffer distances for skimmers and other colonial birds.     

Bee foraging ranges and their relationship to body size

Bees are the most important pollinator taxon; therefore, understanding the scale at which they forage has important ecological implications and conservation applications. The foraging ranges for most bee species are unknown. Foraging distance information is critical for understanding the scale at which bee populations respond to the landscape, assessing the role of bee pollinators in affecting plant population structure, planning conservation strategies for plants, and designing bee habitat refugia that maintain pollination function for wild and crop plants. We used data from 96 records of 62 bee species to determine whether body size predicts foraging distance. We regressed maximum and typical foraging distances on body size and found highly significant and explanatory nonlinear relationships. We used a second data set to: (1) compare observed reports of foraging distance to the distances predicted by our regression equations and (2) assess the biases inherent to the different techniques that have been used to assess foraging distance. The equations we present can be used to predict foraging distances for many bee species, based on a simple measurement of body size. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Distance geometry generates native-like folds for small helical proteins using the consensus distances of predicted protein structures.

For successful ab initio protein structure prediction, a method is needed to identify native-like structures from a set containing both native and non-native protein-like conformations. In this regard, the use of distance geometry has shown promise when accurate inter-residue distances are available. We describe a method by which distance geometry restraints are culled from sets of 500 protein-like conformations for four small helical proteins generated by the method of Simons et al. (1997). A consensus-based approach was applied in which every inter-Calpha distance was measured, and the most frequently occurring distances were used as input restraints for distance geometry. For each protein, a structure with lower coordinate root-mean-square (RMS) error than the mean of the original set was constructed; in three cases the topology of the fold resembled that of the native protein. When the fold sets were filtered for the best scoring conformations with respect to an all-atom knowledge-based scoring function, the remaining subset of 50 structures yielded restraints of higher accuracy. A second round of distance geometry using these restraints resulted in an average coordinate RMS error of 4.38 A.     

Isolation by distance and post-glacial range expansion in the rough-skinned newt, Taricha granulosa

Allozymes and mitochondrial DNA sequences were used to examine the phylogeographical history of the rough-skinned newt, Taricha granulosa, in western North America. Nineteen populations were analysed for allozyme variation at 45 loci, and 23 populations were analysed for cytochrome b sequence variation. Both data sets agree that populations in the southern part of the range are characterized by isolation by distance, whereas northern populations fit the expectations of a recent range expansion. However, the northern limit of isolation by distance (and the southern limit of range expansion) is located in Oregon State by the mtDNA data, and in Washington State by the allozyme data. Nevertheless, both data sets are consistent with the known Pleistocene history of western North America, with phylogenetically basal populations in central and northern California, and a recent range expansion in the north following the retreat of the Cordilleran ice sheet 10,000 years ago. Additionally, a population in Idaho, previously considered introduced from central California based on morphometric analyses, possesses a distinct mtDNA haplotype, suggesting it could be native. The relevance of these results for Pacific Northwest biogeography is discussed.