Graph theoretical analysis of the phytosociological structure of plant communities: The theoretical basis

Summary A method employing samples of variable size is assumed and shown to be useful in the detection of unidirectional associations of one species with another, whether caused by direct influence or by coincidence of ecological requirements. The pattern of these associations from a signed digraph (directed graph), the graph theoretical properties of which give insight into the phytosociological structure of the plant community. The properties of transitivity, balance, homogeneity, reachable sets and types of subgraphs are examined.From a thesis submitted to the University of Toronto in partial fulfilment of the requirements for the degree of Master of Science.     

Structure and Growth of the Leeward Kohala Field System: An Analysis with Directed Graphs

This study illustrates how the theory of directed graphs can be used to investigate the structure and growth of the leeward Kohala field system, a traditional Hawaiian archaeological site that presents an unparalleled opportunity to investigate relative chronology. The relative chronological relationships of agricultural walls and trails in two detailed study areas are represented as directed graphs and then investigated using graph theoretic concepts including cycle, level, and connectedness. The structural properties of the directed graphs reveal structure in the field system at several spatial scales. A process of deduction yields a history of construction in each detailed study area that is different than the history produced by an earlier investigation. These results indicate that it is now possible to study the structure and growth of the entire field system remnant using computer software implementations of graph theoretic concepts applied to observations of agricultural wall and trail intersections made on aerial imagery and/or during fieldwork. A relative chronology of field system development with a resolution of one generation is a possible result.     

Species pool: the concept,its determination and significance for community restoration

Abstract. The concept of species pool is reviewed. It is suggested to maintain the terms regional pool and local pool but replace actual pool by community pool. The regional and local pool are considered as selections from the regional and local flora based on ecological similarity. It is also suggested to include in the community pool a selection of species present only as diaspores in the diaspore bank (including diaspores from the seed rain), the selection being based on the same ecological criteria. Four approaches to determine the species pool are discussed: ecological, functional and phytosociological similarity, and an experimental approach. The phytosociological approach appears to be promising. The species pool is elaborated as a fuzzy set in the sense that each species of a community or a local or regional flora is a member of any community, local or regional species pool with different degrees of membership. This membership is defined as a probability of a species to become part of the community pool of a target community which is a function of the ecological (environmen-tal/functional/phytosociological) similarity of the species with the target community; the shortness of the distance of its nearest populations, the frequency/abundance, the dispersal capacity, the actual presence of dispersal mechanisms, the germinability of newly arrived diaspores, and the longevity of seeds (viability) in the diaspore bank. The information on species pools is needed for designing experiments where the number of species in a community is to be manipulated, for instance in restoration management.     

Estimating similarity of communities: a parametric approach to spatio‐temporal analysis of species diversity

Several stochastic models with environmental noise generate spatio‐temporal Gaussian fields of log densities for the species in a community. Combinations of such models for many species often lead to lognormal species abundance distributions. In spatio‐temporal analysis it is often realistic to assume that the same species are expected to occur at different times and/or locations because extinctions are rare events. Spatial and temporal β‐diversity can then be analyzed by studying pairs of communities at different times or locations defined by a bivariate lognormal species abundance model in which a single correlation occurs. This correlation, which is a measure of similarity between two communities, can be estimated from samples even if the sampling intensities vary and are unknown, using the bivariate Poisson lognormal distribution. The estimators are approximately unbiased, although each specific correlation may be rather uncertain when the sampling effort is low with only a small fraction of the species represented in the samples. An important characteristic of this community correlation is that it relates to the classical Jaccard‐ or the Sørensen‐indices of similarity based on the number of species present or absent in two communities. However, these indices calculated from samples of species in a community do not necessarily reflect similarity of the communities because the observed number of species depends strongly on the sampling intensities. Thus, we propose that our community correlation should be considered as an alternative to these indices when comparing similarity of communities. We illustrate the application of the correlation method by computing the similarity between temperate bird communities.     

Using Random Walks to Generate Associations between Objects

Measuring similarities between objects based on their attributes has been an important problem in many disciplines. Object-attribute associations can be depicted as links on a bipartite graph. A similarity measure can be thought as a unipartite projection of this bipartite graph. The most widely used bipartite projection techniques make assumptions that are not often fulfilled in real life systems, or have the focus on the bipartite connections more than on the unipartite connections. Here, we define a new similarity measure that utilizes a practical procedure to extract unipartite graphs without making a priori assumptions about underlying distributions. Our similarity measure captures the relatedness between two objects via the likelihood of a random walker passing through these nodes sequentially on the bipartite graph. An important aspect of the method is that it is robust to heterogeneous bipartite structures and it controls for the transitivity similarity, avoiding the creation of unrealistic homogeneous degree distributions in the resulting unipartite graphs. We test this method using real world examples and compare the obtained results with alternative similarity measures, by validating the actual and orthogonal relations between the entities.     

广东森林群落排序分析

本文应用极点排序和位置向量排序的方法对广东13个森林群落进行排序分析,并分别用极点排序图和位置向量排序的二维图和三维图表示排序的结果。同时对排序图的生态学意义及排序方法的优缺点进行讨论。结果表明,三维位置向量排序图能较好地把性质相近的群落类型聚在一起,可作为植被分类的辅助方法;积点排序图从一定程度上反映了植被的连续变化;极点排序与位置向量排序虽然取得一定结果,但由于同属线性排序,损失的信息量较多,寻求非线性排序方法是研究的方向。     

Exact results for fixation probability of bithermal evolutionary graphs

One of the most fundamental concepts of evolutionary dynamics is the “fixation” probability, i.e. the probability that a mutant spreads through the whole population. Most natural communities are geographically structured into habitats exchanging individuals among each other and can be modeled by an evolutionary graph (EG), where directed links weight the probability for the offspring of one individual to replace another individual in the community. EGs have recently spurred huge interest, as it has been shown that some topology can amplify or suppress the effect of beneficial mutations. Very few exact analytical results however are known for EGs. In this article we show that the use of a new technique, the fixed point of probability generating function, allows us to compute the exact fixation probability for a large subset of bithermal graphs. We also show by numerical simulations that the computed solution holds for all bithermal graphs. Moreover, the analytical solution allows us to clarify the opposing consequences of birth–death versus death–birth processes as amplifier or suppressor of beneficial mutations for the same bithermal topology.     

基于图自编码器和协同训练预测miRNA[]与疾病的关联

近年来,越来越多的生物学实验研究表明,microRNA (miRNA)在人类复杂疾病的发展中发挥着重要作用。因此,预测miRNA与疾病之间的关联有助于疾病的准确诊断和有效治疗。由于传统的生物学实验是一种昂贵且耗时的方式,于是许多基于生物学数据的计算模型被提出来预测miRNA与疾病的关联。本研究提出了一种端到端的深度学习模型来预测miRNA-疾病关联关系,称为MDAGAC。首先,通过整合疾病语义相似性,miRNA功能相似性和高斯相互作用谱核相似性,构建miRNA和疾病的相似性图。然后,通过图自编码器和协同训练来改善标签传播的效果。该模型分别在miRNA图和疾病图上建立了两个图自编码器,并对这两个图自编码器进行了协同训练。miRNA图和疾病图上的图自编码器能够通过初始关联矩阵重构得分矩阵,这相当于在图上传播标签。miRNA-疾病关联的预测概率可以从得分矩阵得到。基于五折交叉验证的实验结果表明,MDAGAC方法可靠有效,优于现有的几种预测miRNA-疾病关联的方法。     

Parsimony analysis and ecological communities, phytosociology, nested subsets analysis, forest fragmentation: a reply to Giannini and Keller

We suggested using parsimony analysis to study community evolution in terms of species composition and to apply these results in the context of forest fragmentation as a replacement for the so‐called “nested subsets analysis” or other phenetic synecological or phytosociological methods ( Pellens et al., 2005 ). Giannini and Keller (2007 ) took issue with this new application on the basis of three misunderstandings. We re‐emphasize that communities themselves are analyzed, not landscape parts such as forest fragments. Therefore, it must be clear that communities are analogous to taxa and landscape parts such as fragments are analogous to distributions of taxa. Community evolution is the change in community composition by immigration, emigration and local extinction. Thus, gains and losses of species should not be confused with horizontal transfer. Parsimony analysis does not necessarily group communities based on shared absences of rare species. Rare species are not necessarily absent in the same communities and these absences are not necessarily inferred to be synapomorphies after rooting. This is the main advance expected when cladistics is used instead of the previously cited phenetic methods working with overall similarity. © The Willi Hennig Society 2007.     

How to determine a regional species pool: a study in two Swedish regions

The species pool hypothesis has been proposed as one of the possible explanations for the local species richness of plant communities. For testing and validating this theory, it is of crucial importance to determine the dimension of the regional pool, which is the reservoir of species that are potentially able to exist in a community. The main purpose of this study was to develop and test different methods for the determination of the regional species pool. Two regions in Sweden served as study areas, Öland and Uppland. In both regions, three different vegetation types were treated: dry calcareous grasslands, coastal meadows and deciduous forests. For the determination of the regional pool two main groups of methods are proposed: 1) six ecological approaches, based on Ellenberg species indicator values, and 2) two phytosociological approaches, based on the occurrence of species in different syntaxa in the framework of the Braun-Blanquet system. The different screening methods were tested using Sørensen's index expressing the similarity between the community species pool and the regional species pool. Two types of error were recognized which may result in low index values. For the six ecological methods Sørensen's index values were below 50%. The methods differed considerably from each other in accuracy, due to large differences in errors of both types. The phytosociological methods resulted in higher similarity values of up to almost 70%. The two approaches differed in error type but gave similar results.     

Assessment of Overlap of Phylogenetic Transmission Clusters and Communities in Simple Sexual Contact Networks: Applications to HIV-1

Background

Transmission patterns of sexually-transmitted infections (STIs) could relate to the structure of the underlying sexual contact network, whose features are therefore of interest to clinicians. Conventionally, we represent sexual contacts in a population with a graph, that can reveal the existence of communities. Phylogenetic methods help infer the history of an epidemic and incidentally, may help detecting communities. In particular, phylogenetic analyses of HIV-1 epidemics among men who have sex with men (MSM) have revealed the existence of large transmission clusters, possibly resulting from within-community transmissions. Past studies have explored the association between contact networks and phylogenies, including transmission clusters, producing conflicting conclusions about whether network features significantly affect observed transmission history. As far as we know however, none of them thoroughly investigated the role of communities, defined with respect to the network graph, in the observation of clusters.

Methods

The present study investigates, through simulations, community detection from phylogenies. We simulate a large number of epidemics over both unweighted and weighted, undirected random interconnected-islands networks, with islands corresponding to communities. We use weighting to modulate distance between islands. We translate each epidemic into a phylogeny, that lets us partition our samples of infected subjects into transmission clusters, based on several common definitions from the literature. We measure similarity between subjects’ island membership indices and transmission cluster membership indices with the adjusted Rand index.

Results and Conclusion

Analyses reveal modest mean correspondence between communities in graphs and phylogenetic transmission clusters. We conclude that common methods often have limited success in detecting contact network communities from phylogenies. The rarely-fulfilled requirement that network communities correspond to clades in the phylogeny is their main drawback. Understanding the link between transmission clusters and communities in sexual contact networks could help inform policymaking to curb HIV incidence in MSMs.     

Species abundance distribution and dynamics in two locally coupled communities

This study considered a model for species abundance dynamics in two local community (or islands) connected to a regional metacommunity. The model was analyzed using continuous probabilistic technique that employs Kolmogorov-Fokker-Planck forward equation to derive the probability density of the species abundance in the two local communities. Using this technique, we proposed a classification for the species abundance dynamics in the local communities. This classification was made based on such characteristics as immigration intensity, species representation in the metacommunity and the size of local communities. We further distinguished several different scenarios for species abundance dynamics using different ecological characteristics such as species persistence, extinction and monodominance in one or both local communities. The similarity of the species abundance distributions between the two local communities was studied using the correlation coefficient between species abundances in two local communities. The correlation is a function of migration rates between local communities and between local and metacommunity. Immigration between local communities drives the homogenization of the local communities, while immigration from the metacommunity will differentiate them. This community subdivision model provides useful insights for studying the effect of landscape fragmentation on species diversity.     

Space remote sensing for spatial vegetation characterization

The study area, Madhav National Park (MP) represents northern tropical dry deciduous forest. The national park, due to its unique location (nearest to township), is under tremendous biotic pressure. In order to understand vegetation structure and dynamics, vegetation mapping at community level was considered important. Prolonged leafless period and background reflection due to open canopy poses challenge in interpretation of satellite data. The vegetation of Madhav National Park was mapped using Landsat TM data. The ground data collected from sample points were subjected to TWINSPAN analysis to cluster sample point data into six communities. The vegetation classification obtained by interpretation (visual and digital) of remote sensing data and TWINSPAN were compared to validate the vegetation classification at community level. The phytosociological data collected from sample points were analysed to characterize communities. The results indicate that structural variations in the communities modulate spectral signatures of vegetation and form basis to describe community structure subjectively and at spatial level.     

Diagnostic analysis of conservation zones using remote sensing and GIS techniques in wet evergreen forests of the Western Ghats – An ecological hotspot, Tamil Nadu, India

This study highlights spatial characterization of evergreen forests of the Western Ghats – an ecological hotspot in Tamil Nadu, India – using remote sensing and GIS-based analysis in conjunction with ground-based phytosociological data. The evergreen forests of Tamil Nadu are distributed in four distinct hill ranges, Nilgiri, Anamalai, Palni and Tirunelveli, having different topographic, bioclimatic and disturbance levels. The evergreen forests in these four hill ranges are characterized for their uniqueness in terms of patch characteristics and phytosociology. A vegetation type map was prepared using IRS LISS III satellite data and was used to study the patch characteristics in terms of patch size, number, shape, porosity and landcover diversity (LD). The phytosociological characteristics, namely species richness, diversity, similarity and community assemblages, were studied using ground data collected from 95 sample points of 0.1 ha size. Patch size and number revealed distinct intactness and disturbance levels in these four hill ranges. Evergreen forests in the Tirunelveli hills comprising 216.09 km² are distributed in 306 patches, and in the Palni hills, with 285 km², forests are distributed in 1029 patches, indicating a high level of fragmentation. LD, indicating the spatial heterogeneity of landcover, was very high in the Nilgiri hills and low in the Tirunelveli hills. The spatial analysis helped to delineate homogenous large patches of evergreen forest, which can be adopted for appropriate conservation strategies. A total of 342 tree species belonging to 4490 stems were evaluated for phytosociology. Only 15–28% of similarity in terms of species distribution was found across the hill ranges. Conjunctive analysis of patch characteristics and species distribution showed high species richness in less fragmented evergreen forests and vice versa. The study identified the areas of prioritization in terms of ecorestoration and conservation based on patch and phytosociological characteristics.     

Context-dependence of diagnostic species: A case study of the central european spruce forests

In the phytosociological literature, there are numerous different approaches to the designation of diagnostic species. Frequently, this results in discrepancies between the lists of diagnostic species published for one and the same community. We examined different approaches to determining diagnostic species using as an examplePicea abies forests within the broader context of all Central European forests. Diagnostic species of spruce forests were determined from a data set of 20,164 phytosociological relevés of forests from the Eastern Alps, Western Carpathians, and the Bohemian Massif, which included 3,569 relevés of spruce forests. Phi coefficient of association was used to measure species fidelity, and species with the highest fidelities were considered as diagnostic. Diagnostic species were determined in four ways, including (A) comparison of spruce forests among the three mountain ranges, (B) comparison between spruce forests and other forests, performed separately in each of the mountain ranges, (C) simultaneous comparison of spruce forests of each of the mountain ranges with spruce forests of the other two ranges and with the other forests of all ranges, (D) comparison of spruce forests with the other forests, using pooled data sets from the three mountain ranges. The sets of diagnostic species of spruce forests yielded in comparisons A and B were sharply different; the set resulting from comparison C was intermediate between the first two and comparison D resulted in similar diagnostic species as comparison B. In comparison A, spruce forests of the Eastern Alps had a number of diagnostic species, while the spruce forests of the other two mountain ranges had only few diagnostic species. In comparison B, by contrast, the number and quality of diagnostic species decreased from the Bohemian Massif to the Eastern Alps. This exercise points out that lists of diagnostic species published in phytosociological literature are dependent on the context, i.e. the underlying data sets and comparisons: some of these lists are useful for identification of vegetation units at a local scale, some others for distinguishing units within a narrowly delimited community type over a large area. The thoughtless application of published lists of diagnostic species outside of the context for which they were intended should therefore be avoided.     

The influence of life history milestones and association networks on crop-raiding behavior in male African elephants

Factors that influence learning and the spread of behavior in wild animal populations are important for understanding species responses to changing environments and for species conservation. In populations of wildlife species that come into conflict with humans by raiding cultivated crops, simple models of exposure of individual animals to crops do not entirely explain the prevalence of crop raiding behavior. We investigated the influence of life history milestones using age and association patterns on the probability of being a crop raider among wild free ranging male African elephants; we focused on males because female elephants are not known to raid crops in our study population. We examined several features of an elephant association network; network density, community structure and association based on age similarity since they are known to influence the spread of behaviors in a population. We found that older males were more likely to be raiders than younger males, that males were more likely to be raiders when their closest associates were also raiders, and that males were more likely to be raiders when their second closest associates were raiders older than them. The male association network had sparse associations, a tendency for individuals similar in age and raiding status to associate, and a strong community structure. However, raiders were randomly distributed between communities. These features of the elephant association network may limit the spread of raiding behavior and likely determine the prevalence of raiding behavior in elephant populations. Our results suggest that social learning has a major influence on the acquisition of raiding behavior in younger males whereas life history factors are important drivers of raiding behavior in older males. Further, both life-history and network patterns may influence the acquisition and spread of complex behaviors in animal populations and provide insight on managing human-wildlife conflict.     

Grazing and the vanishing complexity of plant association networks in grasslands

Interactions are key drivers of the functioning and fate of plant communities. A traditional way to measure them is to use pairwise experiments, but such experiments do not scale up to species-rich communities. For those, using association networks based on spatial patterns may provide a more realistic approach. While this method has been successful in abiotically-stressed environments (alpine and arid ecosystems), it is unclear how well it generalizes to other types of environments. We help fill this knowledge gap by documenting how the structure of plant communities changes in a Mediterranean dry grassland grazed by sheep using plant spatial association networks. We investigated how the structure of these networks changed with grazing intensity to show the effect of biotic disturbance on community structure. We found that these grazed grassland communities were mostly dominated by negative associations, suggesting a dominance of interference over facilitation regardless of the disturbance level. The topology of the networks revealed that the number of associations were not evenly-distributed across species, but rather that a small subset of species established most negative associations under low grazing conditions. All these aspects of spatial organization vanished under high level of grazing as association networks became more similar to null expectations. Our study shows that grazed herbaceous plant communities display a highly non-random organization that responds strongly to disturbance and can be measured through association networks. This approach thus appears insightful to test general hypotheses about plant communities, and in particular understand how anthropogenic perturbations affect the organization of ecological communities.     

Community differentiation on landscapes: drift, migration and speciation

Theories of the differentiation of ecological communities on landscapes have typically not considered evolutionary dynamics. Here we analytically study the expected differentiation among local communities in a large metacommunity, undergoing speciation, ecological drift and intercommunity dispersal, in the context of neutral theory. We demonstrate that heterogeneity in species diversity and abundance arises among communities when local communities are small and intercommunity migration is infrequent. We propose a new measure to describe community differentiation, defined as the average correlation or the average probability (C_st) that two randomly sampled individuals of the same species within local communities are from the same ancestor. The effects of driving forces (migration, mutation, and ecological drift) are incorporated into the two-level hierarchical community structure in a finite island model of neutral communities. Community differentiation can increase the effective metacommunity size or the Hubbell's fundamental species diversity in the metacommunity by a factor (1−C_st)⁻¹. Significant community differentiation arises when C_st≠0. Intercommunity migration promotes species diversity in local communities but reduce species diversity in the metacommunity. In either the finite or infinite island case, one can estimate the number of intercommunity migrants by using multiple local community datasets when the speciation is negligible in the neutral local communities, or by using the metacommunity dataset when the speciation is included in the local neutral communities. These results highlight the significance of the evolutionary mechanisms in generating heterogeneous communities in the absence of complicated ecological processes on large landscapes.