Divergence patterns in Fucus seaweeds (Phaeophyceae) in the northern Baltic Sea and in the Tjongspollen area

To be able to interpret patterns of biodiversity it is important to understand the processes by which new species evolve and how closely related species remain reproductively isolated and ecologically differentiated. Divergence and differentiation can vary during speciation and it can be seen in different stages. Groups of closely related taxa constitute important case studies to understand species and new biodiversity formation. However, it is important to assess the divergence among them at different organismal levels and from an integrative perspective. For this purpose, this study used the brown seaweeds genus Fucus as a model to study speciation, as they constitute a good opportunity to study divergence at different stages. We investigated the divergence patterns in Fucus species from two marginal areas (northern Baltic Sea and the Tjongspollen area), based on phenetic, phylogenetic and biological taxonomical criteria that are respectively characterised by algal morphology, allele frequencies of five microsatellite loci and levels of secondary polyphenolic compounds called phlorotannins. The results from this study showed divergence at morphological and genetic levels to certain extent but complete lack of divergence at biochemical level (i.e. constitutive phlorotannin production) in the Baltic Sea or Norway. Morphological divergence was clearly evident in Tjongspollen (Norway) among putative taxa as they were identified in the field and this divergence corresponds with their neutral genetic divergence. In the Baltic, there are some distinguishable patterns in the morphology of the swedish and finnish individuals according to locality to certain extent but not among putative taxa within localities. Likewise, these morphological patterns have genetic correspondence among localities but not within each locality. At the biochemical level, measured by the phlorotannin contents there were neither evidence of divergence in Norway or the Baltic Sea nor any discernable aggregation pattern among or within localities. Our study have contributed with further understanding of the Baltic Sea Fucus system and its intriguingly rapid and recent divergence as well as of the Tjongspollen area systems where formally undescribed individuals have been observed for the first time; in fact they appear largely differentiated and they may well warrant a new species status. In current times, climate change threatens, peripheral ecosystems, biodiversity, and increased knowledge of processes generating and maintaining biodiversity in those ecosystems seem particularly important and needed.

A Stable Niche Assumption-Free Test of Ecological Divergence

Understanding the impact of geological events on diversification processes is central to evolutionary ecology. The recent amalgamation between ecological niche models (ENMs) and phylogenetic analyses has been used to estimate historical ranges of modern lineages by projecting current ecological niches of organisms onto paleoclimatic reconstructions. A critical assumption underlying this approach is that niches are stable over time. Using Notophthalmus viridescens (eastern newt), in which four ecologically diverged subspecies are recognized, we introduce an analytical framework free from the niche stability assumption to examine how refugial retreat and subsequent postglacial expansion have affected intraspecific ecological divergence. We found that the current subspecies designation was not congruent with the phylogenetic lineages. Thus, we examined ecological niche overlap between the refugial and modern populations, in both subspecies and lineage, by creating ENMs independently for modern and estimated last glacial maximum (LGM) newt populations, extracting bioclimate variables by randomly generated points, and conducting principal component analyses. Our analyses consistently showed that when tested as a hypothesis, rather than used as an assumption, the niches of N. viridescens lineages have been unstable since the LGM (both subspecies and lineages). There was greater ecological niche differentiation among the subspecies than the modern phylogenetic lineages, suggesting that the subspecies, rather than the phylogenetic lineages, is the unit of the current ecological divergence. The present study found little evidence that the LGM refugial retreat caused the currently observed ecological divergence and suggests that ecological divergence has occurred during postglacial expansion to the current distribution ranges.

Divergence along a steep ecological gradient in lake whitefish (Coregonus sp.)

To understand mechanisms structuring diversity in young adaptive radiations, quantitative and unbiased information about genetic and phenotypic diversity is much needed. Here, we present the first in-depth investigation of whitefish diversity in a Swiss lake, with continuous spawning habitat sampling in both time and space. Our results show a clear cline like pattern in genetics and morphology of populations sampled along an ecological depth gradient in Lake Neuchâtel. Divergent natural selection appears to be involved in shaping this cline given that trait specific P(ST)-values are significantly higher than F(ST)-values when comparing populations caught at different depths. These differences also tend to increase with increasing differences in depth, indicating adaptive divergence along a depth gradient, which persists despite considerable gene flow between adjacent demes. It however remains unclear, whether the observed pattern is a result of currently stable selection-gene flow balance, incipient speciation, or reverse speciation due to anthropogenic habitat alteration causing two formerly divergent species to collapse into a single gene pool.

Contemporary ecotypic divergence during a recent range expansion was facilitated by adaptive introgression

Although rapid phenotypic evolution during range expansion associated with colonization of contrasting habitats has been documented in several taxa, the evolutionary mechanisms that underlie such phenotypic divergence have less often been investigated. A strong candidate for rapid ecotype formation within an invaded range is the three-spine stickleback in the Lake Geneva region of central Europe. Since its introduction only about 140 years ago, it has undergone a significant expansion of its range and its niche, now forming phenotypically differentiated parapatric ecotypes that occupy either the pelagic zone of the large lake or small inlet streams, respectively. By comparing museum collections from different times with contemporary population samples, we here reconstruct the evolution of parapatric phenotypic divergence through time. Using genetic data from modern samples, we infer the underlying invasion history. We find that parapatric habitat-dependent phenotypic divergence between the lake and stream was already present in the first half of the twentieth century, but the magnitude of differentiation increased through time, particularly in antipredator defence traits. This suggests that divergent selection between the habitats occurred and was stable through much of the time since colonization. Recently, increased phenotypic differentiation in antipredator defence traits likely results from habitat-dependent selection on alleles that arrived through introgression from a distantly related lineage from outside the Lake Geneva region. This illustrates how hybridization can quickly promote phenotypic divergence in a system where adaptation from standing genetic variation was constrained.

Hybrid ‘superswarm’ leads to rapid divergence and establishment of populations during a biological invasion

Understanding the genetic background of invading species can be crucial information clarifying why they become invasive. Intraspecific genetic admixture among lineages separated in the native ranges may promote the rate and extent of an invasion by substantially increasing standing genetic variation. Here we examine the genetic relationships among threespine stickleback that recently colonized Switzerland. This invasion results from several distinct genetic lineages that colonized multiple locations and have since undergone range expansions, where they coexist and admix in parts of their range. Using 17 microsatellites genotyped for 634 individuals collected from 17 Swiss and two non-Swiss European sites, we reconstruct the invasion of stickleback and investigate the potential and extent of admixture and hybridization among the colonizing lineages from a population genetic perspective. Specifically we test for an increase in standing genetic variation in populations where multiple lineages coexist. We find strong evidence of massive hybridization early on, followed by what appears to be recent increased genetic isolation and the formation of several new genetically distinguishable populations, consistent with a hybrid ‘superswarm’. This massive hybridization and population formation event(s) occurred over approximately 140 years and likely fuelled the successful invasion of a diverse range of habitats. The implications are that multiple colonizations coupled with hybridization can lead to the formation of new stable genetic populations potentially kick-starting speciation and adaptive radiation over a very short time.

Time series irreversibility: a visibility graph approach

We propose a method to measure real-valued time series irreversibility which combines two different tools: the horizontal visibility algorithm and the Kullback-Leibler divergence. This method maps a time series to a directed network according to a geometric criterion. The degree of irreversibility of the series is then estimated by the Kullback-Leibler divergence (i.e. the distinguishability) between the in and out degree distributions of the associated graph. The method is computationally efficient and does not require any ad hoc symbolization process. We find that the method correctly distinguishes between reversible and irreversible stationary time series, including analytical and numerical studies of its performance for: (i) reversible stochastic processes (uncorrelated and Gaussian linearly correlated), (ii) irreversible stochastic processes (a discrete flashing ratchet in an asymmetric potential), (iii) reversible (conservative) and irreversible (dissipative) chaotic maps, and (iv) dissipative chaotic maps in the presence of noise. Two alternative graph functionals, the degree and the degree-degree distributions, can be used as the Kullback-Leibler divergence argument. The former is simpler and more intuitive and can be used as a benchmark, but in the case of an irreversible process with null net current, the degree-degree distribution has to be considered to identify the irreversible nature of the series

Determining divergence times with a protein clock: Update and reevaluation

A recent study of the divergence times of the major groups of organisms as gauged by amino acid sequence comparison has been expanded and the data have been reanalyzed with a distance measure that corrects for both constraints on amino acid interchange and variation in substitution rate at different sites. Beyond that, the availability of complete genome sequences for several eubacteria and an archaebacterium has had a great impact on the interpretation of certain aspects of the data. Thus, the majority of the archaebacterial sequences are not consistent with currently accepted views of the Tree of Life which cluster the archaebacteria with eukaryotes. Instead, they are either outliers or mixed in with eubacterial orthologs. The simplest resolution of the problem is to postulate that many of these sequences were carried into eukaryotes by early eubacterial endosymbionts about 2 billion years ago, only very shortly after or even coincident with the divergence of eukaryotes and archaebacteria. The strong resemblances of these same enzymes among the major eubacterial groups suggest that the cyanobacteria and Gram-positive and Gram-negative eubacteria also diverged at about this same time, whereas the much greater differences between archaebacterial and eubacterial sequences indicate these two groups may have diverged between 3 and 4 billion years ago.

A new Eocene archaeocete (Mammalia, Cetacea) from India and the time of origin of whales

Himalayacetus subathuensis is a new pakicetid archaeocete from the Subathu Formation of northern India. The type dentary has a small mandibular canal indicating a lack of auditory specializations seen in more advanced cetaceans, and it has Pakicetus-like molar teeth suggesting that it fed on fish. Himalayacetus is significant because it is the oldest archaeocete known and because it was found in marine strata associated with a marine fauna. Himalayacetus extends the fossil record of whales about 3.5 million years back in geological time, to the middle part of the early Eocene [≈53.5 million years ago (Ma)]. Oxygen in the tooth-enamel phosphate has an isotopic composition intermediate between values reported for freshwater and marine archaeocetes, indicating that Himalayacetus probably spent some time in both environments. When the temporal range of Archaeoceti is calibrated radiometrically, comparison of likelihoods constrains the time of origin of Archaeoceti and hence Cetacea to about 54–55 Ma (beginning of the Eocene), whereas their divergence from extant Artiodactyla may have been as early as 64–65 Ma (beginning of the Cenozoic).

Estimation of divergence times from multiprotein sequences for a few mammalian species and several distantly related organisms

When many protein sequences are available for estimating the time of divergence between two species, it is customary to estimate the time for each protein separately and then use the average for all proteins as the final estimate. However, it can be shown that this estimate generally has an upward bias, and that an unbiased estimate is obtained by using distances based on concatenated sequences. We have shown that two concatenation-based distances, i.e., average gamma distance weighted with sequence length (d2) and multiprotein gamma distance (d3), generally give more satisfactory results than other concatenation-based distances. Using these two distance measures for 104 protein sequences, we estimated the time of divergence between mice and rats to be approximately 33 million years ago. Similarly, the time of divergence between humans and rodents was estimated to be approximately 96 million years ago. We also investigated the dependency of time estimates on statistical methods and various assumptions made by using sequence data from eubacteria, protists, plants, fungi, and animals. Our best estimates of the times of divergence between eubacteria and eukaryotes, between protists and other eukaryotes, and between plants, fungi, and animals were 3, 1.7, and 1.3 billion years ago, respectively. However, estimates of ancient divergence times are subject to a substantial amount of error caused by uncertainty of the molecular clock, horizontal gene transfer, errors in sequence alignments, etc.

Government failure, opposition success? Electoral performance in Portugal and Italy at the time of the crisis. Jean Monnet Occasional Paper 05/2014

The costs of the crisis in Southern European countries have not been only economic but political. Economic crises tend to lead to government instability and termination while political challengers are expected to exploit this contingent window of opportunity to gain an advantage over incumbents in national elections. The current crisis seems to make no exception, looking at the results of the general elections recently held in Southern Europe. However, this did not always lead to a clear victory of the main opposition parties. In most of the elections, in fact, the incumbent parties’ loss did not coincide with the official opposition’s gain. The extreme case is represented by Italy, where both the outgoing government coalition led by Silvio Berlusconi – setting aside for the moment the technocratic phase – and its main challenger, the centre left coalition, ended up losing millions of voters and a new political force, the Five Star Movement, obtained about 25 per cent of votes. On the opposite side there is Portugal. Only in Portugal did the vote increase for the centre right PSD, in fact, exceed the incumbent socialists’ loss. The present work aims at exploring the factors which might account for this significant divergence between the two cases.

A quantum Jensen-Shannon graph kernel using discrete-time quantum walks

In this paper, we develop a new graph kernel by using the quantum Jensen-Shannon divergence and the discrete-time quantum walk. To this end, we commence by performing a discrete-time quantum walk to compute a density matrix over each graph being compared. For a pair of graphs, we compare the mixed quantum states represented by their density matrices using the quantum Jensen-Shannon divergence. With the density matrices for a pair of graphs to hand, the quantum graph kernel between the pair of graphs is defined by exponentiating the negative quantum Jensen-Shannon divergence between the graph density matrices. We evaluate the performance of our kernel on several standard graph datasets, and demonstrate the effectiveness of the new kernel.

Node centrality for continuous-time quantum walks

The study of complex networks has recently attracted increasing interest because of the large variety of systems that can be modeled using graphs. A fundamental operation in the analysis of complex networks is that of measuring the centrality of a vertex. In this paper, we propose to measure vertex centrality using a continuous-time quantum walk. More specifically, we relate the importance of a vertex to the influence that its initial phase has on the interference patterns that emerge during the quantum walk evolution. To this end, we make use of the quantum Jensen-Shannon divergence between two suitably defined quantum states. We investigate how the importance varies as we change the initial state of the walk and the Hamiltonian of the system. We find that, for a suitable combination of the two, the importance of a vertex is almost linearly correlated with its degree. Finally, we evaluate the proposed measure on two commonly used networks. © 2014 Springer-Verlag Berlin Heidelberg.

A quantum Jensen-Shannon graph kernel using the continuous-time quantum walk

In this paper, we use the quantum Jensen-Shannon divergence as a means to establish the similarity between a pair of graphs and to develop a novel graph kernel. In quantum theory, the quantum Jensen-Shannon divergence is defined as a distance measure between quantum states. In order to compute the quantum Jensen-Shannon divergence between a pair of graphs, we first need to associate a density operator with each of them. Hence, we decide to simulate the evolution of a continuous-time quantum walk on each graph and we propose a way to associate a suitable quantum state with it. With the density operator of this quantum state to hand, the graph kernel is defined as a function of the quantum Jensen-Shannon divergence between the graph density operators. We evaluate the performance of our kernel on several standard graph datasets from bioinformatics. We use the Principle Component Analysis (PCA) on the kernel matrix to embed the graphs into a feature space for classification. The experimental results demonstrate the effectiveness of the proposed approach. © 2013 Springer-Verlag.

A continuous-time quantum walk kernel for unattributed graphs

Kernel methods provide a way to apply a wide range of learning techniques to complex and structured data by shifting the representational problem from one of finding an embedding of the data to that of defining a positive semidefinite kernel. In this paper, we propose a novel kernel on unattributed graphs where the structure is characterized through the evolution of a continuous-time quantum walk. More precisely, given a pair of graphs, we create a derived structure whose degree of symmetry is maximum when the original graphs are isomorphic. With this new graph to hand, we compute the density operators of the quantum systems representing the evolutions of two suitably defined quantum walks. Finally, we define the kernel between the two original graphs as the quantum Jensen-Shannon divergence between these two density operators. The experimental evaluation shows the effectiveness of the proposed approach. © 2013 Springer-Verlag.

Attributed graph similarity from the quantum Jensen-Shannon divergence

One of the most fundamental problem that we face in the graph domain is that of establishing the similarity, or alternatively the distance, between graphs. In this paper, we address the problem of measuring the similarity between attributed graphs. In particular, we propose a novel way to measure the similarity through the evolution of a continuous-time quantum walk. Given a pair of graphs, we create a derived structure whose degree of symmetry is maximum when the original graphs are isomorphic, and where a subset of the edges is labeled with the similarity between the respective nodes. With this compositional structure to hand, we compute the density operators of the quantum systems representing the evolution of two suitably defined quantum walks. We define the similarity between the two original graphs as the quantum Jensen-Shannon divergence between these two density operators, and then we show how to build a novel kernel on attributed graphs based on the proposed similarity measure. We perform an extensive experimental evaluation both on synthetic and real-world data, which shows the effectiveness the proposed approach. © 2013 Springer-Verlag.