Institut für Ökologie, Evolution und Diversität
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The partial faunal reserve of Pama is situated in the province of Kompienga, in the South-East of Burkina Faso, with typical Sudanian savanna vegetation. Adjacent to the Arli National Park and the Pendjari National Park, it is part of the so-called WAP complex, one of the largest wildlife areas in West Africa. Up to now, only little has been known about its flora. The present study aimed at reducing this gap in knowledge, and represents an important tool for conservation and research. The list of species was compiled from the surveys carried out from 2001 to 2004, additional relevé data, and herbarium specimens. We found 450 species, which belong to 244 genera and 73 families. The most species-rich family is Poaceae (83 species), followed by Fabaceae (64), Cyperaceae (24), Rubiaceae (22), Euphor- biaceae (20), Combretaceae (15), Asteraceae (14), Caesalpiniaceae (14), Mimosaceae (12), and Convolvulaceae (11).
A Bayesian framework to estimate diversification rates and their variation through time and space
(2011)
Background: Patterns of species diversity are the result of speciation and extinction processes, and molecular phylogenetic data can provide valuable information to derive their variability through time and across clades. Bayesian Markov chain Monte Carlo methods offer a promising framework to incorporate phylogenetic uncertainty when estimating rates of diversification.
Results: We introduce a new approach to estimate diversification rates in a Bayesian framework over a distribution of trees under various constant and variable rate birth-death and pure-birth models, and test it on simulated phylogenies. Furthermore, speciation and extinction rates and their posterior credibility intervals can be estimated while accounting for non-random taxon sampling. The framework is particularly suitable for hypothesis testing using Bayes factors, as we demonstrate analyzing dated phylogenies of Chondrostoma (Cyprinids) and Lupinus (Fabaceae). In addition, we develop a model that extends the rate estimation to a meta-analysis framework in which different data sets are combined in a single analysis to detect general temporal and spatial trends in diversification.
Conclusions: Our approach provides a flexible framework for the estimation of diversification parameters and hypothesis testing while simultaneously accounting for uncertainties in the divergence times and incomplete taxon sampling.
At a site in the Bolivian Chiquitano region composed by a mosaic of pastureland and primary Chiquitano Dry Forest (CDF) we conducted a camera-trapping study to (1) survey the mammals, and (2) compare individual Jaguar numbers with other Chiquitano sites. Therefore, we installed 13 camera stations (450 ha polygon) over a period of six months. On 1,762 camera-days and in 1,654 independent capture events, we recorded 24 mammalian species that represent the native fauna of large and medium-sized mammals including apex-predators (Puma, Jaguar), meso-carnivores (Ocelot, Jaguarundi, Margay), and large herbivores (Tapir, Collared and White lipped Peccary). We identified six adult Jaguars and found indications of successful reproductive activity. Captures of Jaguars were higher in CDF than in altered habitats. In summary, we believe that (1) the mammal species richness, (2) the high capture numbers of indicator species, and (3) the high capture numbers of Jaguar indicate that our study area has a good conservation status. Future efforts should be undertaken to keep this, and monitoring programs in this region are necessary to further evaluate the potential importance of the Chiquitano region as a possible key region for mammals, especially Jaguars, in South America.
Here we present a formal description of Biremis panamae Barka, Witkowski et Weisenborn sp. nov., which was isolated from the marine littoral environment of the Pacific Ocean coast of Panama. The description is based on morphology (light and electron microscopy) and the rbcL, psbC and SSU sequences of one clone of this species. The new species is included in Biremis due to its morphological features; i.e. two marginal rows of foramina, chambered striae, and girdle composed of numerous punctate copulae. The new species also possesses a striated valve face which is not seen in most known representatives of marine littoral Biremis species. In this study we also present the relationship of Biremis to other taxa using morphology, DNA sequence data and observations of auxosporulation. Our results based on these three sources point to an evolutionary relationship between Biremis, Neidium and Scoliopleura. The unusual silicified incunabular caps present in them are known otherwise only in Muelleria, which is probably related to the Neidiaceae and Scoliotropidaceae. We also discuss the relationship between Biremis and the recently described Labellicula and Olifantiella.
Video and image data are regularly used in the field of benthic ecology to document biodiversity. However, their use is subject to a number of challenges, principally the identification of taxa within the images without associated physical specimens. The challenge of applying traditional taxonomic keys to the identification of fauna from images has led to the development of personal, group, or institution level reference image catalogues of operational taxonomic units (OTUs) or morphospecies. Lack of standardisation among these reference catalogues has led to problems with observer bias and the inability to combine datasets across studies. In addition, lack of a common reference standard is stifling efforts in the application of artificial intelligence to taxon identification. Using the North Atlantic deep sea as a case study, we propose a database structure to facilitate standardisation of morphospecies image catalogues between research groups and support future use in multiple front-end applications. We also propose a framework for coordination of international efforts to develop reference guides for the identification of marine species from images. The proposed structure maps to the Darwin Core standard to allow integration with existing databases. We suggest a management framework where high-level taxonomic groups are curated by a regional team, consisting of both end users and taxonomic experts. We identify a mechanism by which overall quality of data within a common reference guide could be raised over the next decade. Finally, we discuss the role of a common reference standard in advancing marine ecology and supporting sustainable use of this ecosystem.
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 bluebottle blow fly Calliphora vicina is a common species distributed throughout Europe that can play an important role as forensic evidence in crime investigations. Developmental rates of C. vicina from distinct populations from Germany and England were compared under different temperature regimes to explore the use of growth data from different geographical regions for local case work. Wing morphometrics and molecular analysis between these populations were also studied as indicators for biological differences. One colony each of German and English C. vicina were cultured at the Institute of Legal Medicine in Frankfurt, Germany. Three different temperature regimes were applied, two constant (16°C & 25°C) and one variable (17–26°C, room temperature = RT). At seven time points (600, 850, 1200, 1450, 1800, 2050, and 2400 accumulated degree hours), larval lengths were measured; additionally, the durations of the post feeding stage and intrapuparial metamorphosis were recorded. For the morphometric and molecular study, 184 females and 133 males from each C. vicina population (Germany n = 3, England n = 4) were sampled. Right wings were measured based on 19 landmarks and analyzed using canonical variates analysis and discriminant function analysis. DNA was isolated from three legs per specimen (n = 61) using 5% chelex. A 784 bp long fragment of the mitochondrial cytochrome b gene was sequenced; sequences were aligned and phylogenetically analyzed. Similar larval growth rates of C. vicina were found from different geographic populations at different temperatures during the major part of development. Nevertheless, because minor differences were found a wider range of temperatures and sampling more time points should be analyzed to obtain more information relevant for forensic case work. Wing shape variation showed a difference between the German and English populations (P<0.0001). However, separation between the seven German and English populations at the smaller geographic scale remained ambiguous. Molecular phylogenetic analysis by maximum likelihood method could not unambiguously separate the different geographic populations at a national (Germany vs England) or local level.