Institut für Ökologie, Evolution und Diversität
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Recent phylogenomic studies have failed to conclusively resolve certain branches of the placental mammalian tree, despite the evolutionary analysis of genomic data from 32 species. Previous analyses of single genes and retroposon insertion data yielded support for different phylogenetic scenarios for the most basal divergences. The results indicated that some mammalian divergences were best interpreted not as a single bifurcating tree, but as an evolutionary network. In these studies the relationships among some orders of the super-clade Laurasiatheria were poorly supported, albeit not studied in detail. Therefore, 4775 protein-coding genes (6,196,263 nucleotides) were collected and aligned in order to analyze the evolution of this clade. Additionally, over 200,000 introns were screened in silico, resulting in 32 phylogenetically informative long interspersed nuclear elements (LINE) insertion events.
The present study shows that the genome evolution of Laurasiatheria may best be understood as an evolutionary network. Thus, contrary to the common expectation to resolve major evolutionary events as a bifurcating tree, genome analyses unveil complex speciation processes even in deep mammalian divergences. We exemplify this on a subset of 1159 suitable genes that have individual histories, most likely due to incomplete lineage sorting or introgression, processes that can make the genealogy of mammalian genomes complex.
These unexpected results have major implications for the understanding of evolution in general, because the evolution of even some higher level taxa such as mammalian orders may sometimes not be interpreted as a simple bifurcating pattern.
Network graphs have become a popular tool to represent complex systems composed of many interacting subunits; especially in neuroscience, network graphs are increasingly used to represent and analyze functional interactions between multiple neural sources. Interactions are often reconstructed using pairwise bivariate analyses, overlooking the multivariate nature of interactions: it is neglected that investigating the effect of one source on a target necessitates to take all other sources as potential nuisance variables into account; also combinations of sources may act jointly on a given target. Bivariate analyses produce networks that may contain spurious interactions, which reduce the interpretability of the network and its graph metrics. A truly multivariate reconstruction, however, is computationally intractable because of the combinatorial explosion in the number of potential interactions. Thus, we have to resort to approximative methods to handle the intractability of multivariate interaction reconstruction, and thereby enable the use of networks in neuroscience. Here, we suggest such an approximative approach in the form of an algorithm that extends fast bivariate interaction reconstruction by identifying potentially spurious interactions post-hoc: the algorithm uses interaction delays reconstructed for directed bivariate interactions to tag potentially spurious edges on the basis of their timing signatures in the context of the surrounding network. Such tagged interactions may then be pruned, which produces a statistically conservative network approximation that is guaranteed to contain non-spurious interactions only. We describe the algorithm and present a reference implementation in MATLAB to test the algorithm’s performance on simulated networks as well as networks derived from magnetoencephalographic data. We discuss the algorithm in relation to other approximative multivariate methods and highlight suitable application scenarios. Our approach is a tractable and data-efficient way of reconstructing approximative networks of multivariate interactions. It is preferable if available data are limited or if fully multivariate approaches are computationally infeasible.
Animal tracking and biologging devices record large amounts of data on individual movement behaviors in natural environments. In these data, movement ecologists often view unexplained variation around the mean as “noise” when studying patterns at the population level. In the field of behavioral ecology, however, focus has shifted from population means to the biological underpinnings of variation around means. Specifically, behavioral ecologists use repeated measures of individual behavior to partition behavioral variability into intrinsic among-individual variation and reversible behavioral plasticity and to quantify: a) individual variation in behavioral types (i.e. different average behavioral expression), b) individual variation in behavioral plasticity (i.e. different responsiveness of individuals to environmental gradients), c) individual variation in behavioral predictability (i.e. different residual within-individual variability of behavior around the mean), and d) correlations among these components and correlations in suites of behaviors, called ‘behavioral syndromes’. We here suggest that partitioning behavioral variability in animal movements will further the integration of movement ecology with other fields of behavioral ecology. We provide a literature review illustrating that individual differences in movement behaviors are insightful for wildlife and conservation studies and give recommendations regarding the data required for addressing such questions. In the accompanying R tutorial we provide a guide to the statistical approaches quantifying the different aspects of among-individual variation. We use movement data from 35 African elephants and show that elephants differ in a) their average behavior for three common movement behaviors, b) the rate at which they adjusted movement over a temporal gradient, and c) their behavioral predictability (ranging from more to less predictable individuals). Finally, two of the three movement behaviors were correlated into a behavioral syndrome (d), with farther moving individuals having shorter mean residence times. Though not explicitly tested here, individual differences in movement and predictability can affect an individual’s risk to be hunted or poached and could therefore open new avenues for conservation biologists to assess population viability. We hope that this review, tutorial, and worked example will encourage movement ecologists to examine the biology of individual variation in animal movements hidden behind the population mean.
The use of phylogenies in ecology is increasingly common and has broadened our understanding of biological diversity. Ecological sub-disciplines, particularly conservation, community ecology and macroecology, all recognize the value of evolutionary relationships but the resulting development of phylogenetic approaches has led to a proliferation of phylogenetic diversity metrics. The use of many metrics across the sub-disciplines hampers potential meta-analyses, syntheses, and generalizations of existing results. Further, there is no guide for selecting the appropriate metric for a given question, and different metrics are frequently used to address similar questions. To improve the choice, application, and interpretation of phylo-diversity metrics, we organize existing metrics by expanding on a unifying framework for phylogenetic information.
Generally, questions about phylogenetic relationships within or between assemblages tend to ask three types of question: how much; how different; or how regular? We show that these questions reflect three dimensions of a phylogenetic tree: richness, divergence, and regularity. We classify 70 existing phylo-diversity metrics based on their mathematical form within these three dimensions and identify ‘anchor’ representatives: for α-diversity metrics these are PD (Faith's phylogenetic diversity), MPD (mean pairwise distance), and VPD (variation of pairwise distances). By analysing mathematical formulae and using simulations, we use this framework to identify metrics that mix dimensions, and we provide a guide to choosing and using the most appropriate metrics. We show that metric choice requires connecting the research question with the correct dimension of the framework and that there are logical approaches to selecting and interpreting metrics. The guide outlined herein will help researchers navigate the current jungle of indices.
The lichen-forming genus Pertusaria under its current circumscription is polyphyletic and its phylogenetic affiliations are uncertain. Here we study the species of the genera Pertusaria and Varicellaria which containlecanoric acid as major constituent, have disciform apothecia, strongly amyloid asci, non-amyloid hymenial gel, 1-2-spored asci, and 1- or 2-celled ascospores with thick, 1-layered walls. We infer phylogenetic relationships using maximum likelihood and Bayesian analyses based on four molecular loci (mtSSU, nuLSU rDNA, and the protein-coding, nuclear RPB1 and MCM7 genes). Our results show that the lecanoric acid-containing species form a well-supported, monophyletic group, which is only distantly related to Pertusaria s.str. The phylogenetic position of this clade is unclear, but placement in Pertusaria s.str. is rejected using alternative hypothesis testing. The circumscription of the genus Varicellaria is enlarged to also include species with non-septate ascospores. Seven species are accepted in the genus: Varicellaria culbersonii (Vězda) Schmitt & Lumbsch, comb. nov., Varicellaria hemisphaerica (Flörke) Schmitt & Lumbsch, comb. nov., Varicellaria kasandjeffii (Szatala) Schmitt & Lumbsch, comb. nov., Varicellaria lactea (L.) Schmitt & Lumbsch, comb. nov., Varicellaria philippina (Vain.) Schmitt & Lumbsch, comb. nov., Varicellaria rhodocarpa (Körb.) Th. Fr., and Varicellaria velata (Turner) Schmitt & Lumbsch, comb. nov. A key to the species of Varicellaria is provided.
Molecular phylogenetic studies of Moraea Mill. and the inclusion of Barnardiella Goldblatt, Galaxia Thunb., Gynandriris Parl., Hexaglottis Vent., Homeria Vent. and Roggeveldia Goldblatt in the genus have rendered the existing infrageneric classification, dating from 1976, in need of substantial revision. In particular, subg. Moraea and subg. Vieusseuxia have been shown to be paraphyletic. We propose a new infrageneric classification, based, as far as current data permit, on phylogenetic principles. Monophyletic subgenera and sections are circumscribed based on molecular phylogenies alone or in combination with morphological considerations. We recognize 11 subgenera, 15 sections and three series, arranged as follows in phylogenetic sequence: Plumarieae; Visciramosae (with sect. Multifoliae and sect. Visciramosae); Moraea (with sect. Moraea and sect. Polyphyllae); Galaxia (with ser. Unguiculatae, ser. Eurystigma and ser. Galaxia); Monocephalae; Acaules; Polyanthes (with sect. Serpentinae, sect. Deserticola, sect. Hexaglottis, sect. Gynandriris, sect. Polyanthes and sect. Pseudospicatae); Grandifl orae; Vieusseuxia (with sect. Integres, sect. Vieusseuxia and sect. Villosae); and Homeria (with sect. Stipanthera, sect. Flexuosae, sect. Homeria and sect. Conantherae). Most are moderately to well circumscribed at the morphological level either by floral or vegetative characters, except subg. Moraea, which includes a small number of unspecialized species apparently not linked by any apomorphic features. With over 27 new species described in the past 25 years and another 60 transferred to the genus, Moraea now includes 214 species. We provide a full taxonomic synopsis of the genus.
A world dataset on the geographic distributions of Solenidae razor clams (Mollusca: Bivalvia)
(2019)
Background: Using this dataset, we examined the global geographical distributions of Solenidae species in relation to their endemicity, species richness and latitudinal ranges and then predicted their distributions under future climate change using species distribution modelling techniques (Saeedi et al. 2016a, Saeedi et al. 2016b). We found that the global latitudinal species richness in Solenidae is bi-modal, dipping at the equator most likely derived by high sea surface temperature (Saeedi et al. 2016b). We also found that most of the Solenidae species will shift their distribution ranges polewards due to global warming (Saeedi et al. 2016a). We also provided a comprehensive review of the taxon to test whether the latitudinal gradient in species richness was uni-modal with a peak in the tropics or northern hemisphere or asymmetric and bimodal as proposed previously (Chaudhary et al. 2016).
New information: This paper presents an integrated global geographic distribution dataset for 77 Solenidae taxa, including 3,034 geographic distribution records. This dataset was compiled after a careful data-collection and cleaning procedure over four years. Data were collected using field sampling, literature and from open-access databases. Then all the records went through quality control procedures such as validating the taxonomy of the species by examining and re-identifying the specimens in museum collections and using taxonomic and geographic data quality control tools in the World Register of Marine Species (WoRMS) and the r-OBIS package (Provoost and Bosch 2017). This dataset can thus be further used for taxonomical and biogeographical studies of Solenidae.
Background: Many fungal species occur across a variety of habitats. Particularly lichens, fungi forming symbioses with photosynthetic partners, have evolved remarkable tolerances for environmental extremes. Despite their ecological importance and ubiquity, little is known about the genetic basis of adaption in lichen populations. Here we studied patterns of genome-wide differentiation in the lichen-forming fungus Lasallia pustulata along an altitudinal gradient in the Mediterranean region. We resequenced six populations as pools and identified highly differentiated genomic regions. We then detected gene-environment correlations while controlling for shared population history and pooled sequencing bias, and performed ecophysiological experiments to assess fitness differences of individuals from different environments.
Results: We detected two strongly differentiated genetic clusters linked to Mediterranean and temperate-oceanic climate, and an admixture zone, which coincided with the transition between the two bioclimates. High altitude individuals showed ecophysiological adaptations to wetter and more shaded conditions. Highly differentiated genome regions contained a number of genes associated with stress response, local environmental adaptation, and sexual reproduction.
Conclusions: Taken together our results provide evidence for a complex interplay between demographic history and spatially varying selection acting on a number of key biological processes, suggesting a scenario of ecological speciation.
Parasites of the nematode genus Anisakis are associated with aquatic organisms. They can be found in a variety of marine hosts including whales, crustaceans, fish and cephalopods and are known to be the cause of the zoonotic disease anisakiasis, a painful inflammation of the gastro-intestinal tract caused by the accidental consumptions of infectious larvae raw or semi-raw fishery products. Since the demand on fish as dietary protein source and the export rates of seafood products in general is rapidly increasing worldwide, the knowledge about the distribution of potential foodborne human pathogens in seafood is of major significance for human health. Studies have provided evidence that a few Anisakis species can cause clinical symptoms in humans. The aim of our study was to interpolate the species range for every described Anisakis species on the basis of the existing occurrence data. We used sequence data of 373 Anisakis larvae from 30 different hosts worldwide and previously published molecular data (n = 584) from 53 field-specific publications to model the species range of Anisakis spp., using a interpolation method that combines aspects of the alpha hull interpolation algorithm as well as the conditional interpolation approach. The results of our approach strongly indicate the existence of species-specific distribution patterns of Anisakis spp. within different climate zones and oceans that are in principle congruent with those of their respective final hosts. Our results support preceding studies that propose anisakid nematodes as useful biological indicators for their final host distribution and abundance as they closely follow the trophic relationships among their successive hosts. The modeling might although be helpful for predicting the likelihood of infection in order to reduce the risk of anisakiasis cases in a given area.
Background: Aedes albopictus and Ae. japonicus are two of the most widespread invasive mosquito species that have recently become established in western Europe. Both species are associated with the transmission of a number of serious diseases and are projected to continue their spread in Europe.
Methods: In the present study, we modelled the habitat suitability for both species under current and future climatic conditions by means of an Ensemble forecasting approach. We additionally compared the modelled MAXENT niches of Ae. albopictus and Ae. japonicus regarding temperature and precipitation requirements.
Results: Both species were modelled to find suitable habitat conditions in distinct areas within Europe: Ae. albopictus within the Mediterranean regions in southern Europe, Ae. japonicus within the more temperate regions of central Europe. Only in few regions, suitable habitat conditions were projected to overlap for both species. Whereas Ae. albopictus is projected to be generally promoted by climate change in Europe, the area modelled to be climatically suitable for Ae. japonicus is projected to decrease under climate change. This projection of range reduction under climate change relies on the assumption that Ae. japonicus is not able to adapt to warmer climatic conditions. The modelled MAXENT temperature niches of Ae. japonicus were found to be narrower with an optimum at lower temperatures compared to the niches of Ae. albopictus.
Conclusions: Species distribution models identifying areas with high habitat suitability can help improving monitoring programmes for invasive species currently in place. However, as mosquito species are known to be able to adapt to new environmental conditions within the invasion range quickly, niche evolution of invasive mosquito species should be closely followed upon in future studies.