Senckenbergische Naturforschende Gesellschaft
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Before the advent of molecular phylogenetics, species concepts in the downy mildews, an economically important group of obligate biotrophic oomycete pathogens, have mostly been based upon host range and morphology. While molecular phylogenetic studies have confirmed a narrow host range for many downy mildew species, others, like Pseudoperonospora cubensis affect even different genera. Although often morphological differences were found for new, phylogenetically distinct species, uncertainty prevails regarding their host ranges, especially regarding related plants that have been reported as downy mildew hosts, but were not included in the phylogenetic studies. In these cases, the basis for deciding if the divergence in some morphological characters can be deemed sufficient for designation as separate species is uncertain, as observed morphological divergence could be due to different host matrices colonised. The broad host range of P. cubensis (ca. 60 host species) renders this pathogen an ideal model organism for the investigation of morphological variations in relation to the host matrix and to evaluate which characteristics are best indicators for conspecificity or distinctiveness. On the basis of twelve morphological characterisitcs and a set of twelve cucurbits from five different Cucurbitaceae tribes, including the two species, Cyclanthera pedata and Thladiantha dubia, hitherto not reported as hosts of P. cubensis, a significant influence of the host matrix on pathogen morphology was found. Given the high intraspecific variation of some characteristics, also their plasticity has to be taken into account. The implications for morphological species determination and the confidence limits of morphological characteristics are discussed. For species delimitations in Pseudoperonospora it is shown that the ratio of the height of the first ramification to the sporangiophore length, ratio of the longer to the shorter ultimate branchlet, and especially the length and width of sporangia, as well as, with some reservations, their ratio, are the most suitable characteristics for species delimitation.
The Arabidopsis arenosa complex is closely related to the model plant Arabidopsis thaliana. Species and subspecies in the complex are mainly biennial, predominantly outcrossing, herbaceous, and with a distribution range covering most parts of latitudes and the eastern reaches of Europe. In this study we present the first comprehensive evolutionary history of the A. arenosa species complex, covering its natural range, by using chromosome counts, nuclear AFLP data, and a maternally inherited marker from the chloroplast genome [trnL intron (trnL) and trnL/F intergenic spacer (trnL/F-IGS) of tRNALeu and tRNAPhe, respectively]. We unravel the broad-scale cytogeographic and phylogeographic patterns of diploids and tetraploids. Diploid cytotypes were exclusively found on the Balkan Peninsula and in the Carpathians while tetraploid cytotypes were found throughout the remaining distribution range of the A. arenosa complex. Three centers of genetic diversity were identified: the Balkan Peninsula, the Carpathians, and the unglaciated Eastern and Southeastern Alps. All three could have served as long-term refugia during Pleistocene climate oscillations. We hypothesize that the Western Carpathians were and still are the cradle of speciation within the A. arenosa complex due to the high species number and genetic diversity and the concurrence of both cytotypes there.
Background: Mammalian fossils from the Eppelsheim Formation (Dinotheriensande) have been a benchmark for Neogene vertebrate palaeontology since 200 years. Worldwide famous sites like Eppelsheim serve as key localities for biochronologic, palaeobiologic, environmental, and mammal community studies. So far the formation is considered to be of early Late Miocene age (~9.5 Ma, Vallesian), representing the oldest sediments of the Rhine River. The stratigraphic unity of the formation and of its fossil content was disputed at times, but persists unresolved.
Principal Findings: Here we investigate a new fossil sample from Sprendlingen, composed by over 300 mammalian specimens and silicified wood. The mammals comprise entirely Middle Miocene species, like cervids Dicrocerus elegans, Paradicrocerus elegantulus, and deinotheres Deinotherium bavaricum and D. levius. A stratigraphic evaluation of Miocene Central European deer and deinothere species proof the stratigraphic inhomogenity of the sample, and suggest late Middle Miocene (~12.5 Ma) reworking of early Middle Miocene (~15 Ma) sediments. This results agree with taxonomic and palaeoclimatic analysis of plant fossils from above and within the mammalian assemblage. Based on the new fossil sample and published data three biochronologic levels within the Dinotheriensand fauna can be differentiated, corresponding to early Middle Miocene (late Orleanian to early Astaracian), late Middle Miocene (late Astaracian), and early Late Miocene (Vallesian) ages.
Conclusions/Significance: This study documents complex faunal mixing of classical Dinotheriensand fauna, covering at least six million years, during a time of low subsidence in the Mainz Basin and shifts back the origination of the Rhine River by some five million years. Our results have severe implications for biostratigraphy and palaeobiology of the Middle to Late Miocene. They suggest that turnover events may be obliterated and challenge the proposed ‘supersaturated’ biodiversity, caused by Middle Miocene superstites, of Vallesian ecosystems in Central Europe.
We study how species richness of arthropods relates to theories concerning net primary productivity, ambient energy, water-energy dynamics and spatial environmental heterogeneity. We use two datasets of arthropod richness with similar spatial extents (Scandinavia to Mediterranean), but contrasting spatial grain (local habitat and country). Samples of ground-dwelling spiders, beetles, bugs and ants were collected from 32 paired habitats at 16 locations across Europe. Species richness of these taxonomic groups was also determined for 25 European countries based on the Fauna Europaea database. We tested effects of net primary productivity (NPP), annual mean temperature (T), annual rainfall (R) and potential evapotranspiration of the coldest month (PETmin) on species richness and turnover. Spatial environmental heterogeneity within countries was considered by including the ranges of NPP, T, R and PETmin. At the local habitat grain, relationships between species richness and environmental variables differed strongly between taxa and trophic groups. However, species turnover across locations was strongly correlated with differences in T. At the country grain, species richness was significantly correlated with environmental variables from all four theories. In particular, species richness within countries increased strongly with spatial heterogeneity in T. The importance of spatial heterogeneity in T for both species turnover across locations and for species richness within countries suggests that the temperature niche is an important determinant of arthropod diversity. We suggest that, unless climatic heterogeneity is constant across sampling units, coarse-grained studies should always account for environmental heterogeneity as a predictor of arthropod species richness, just as studies with variable area of sampling units routinely consider area.
Freshwater biodiversity has declined dramatically in Europe in recent decades. Because of massive habitat pollution and morphological degradation of water bodies, many once widespread species persist in small fractions of their original range. These range contractions are generally believed to be accompanied by loss of intraspecific genetic diversity, due to the reduction of effective population sizes and the extinction of regional genetic lineages. We aimed to assess the loss of genetic diversity and its significance for future potential reintroduction of the long-tailed mayfly Palingenia longicauda (Olivier), which experienced approximately 98% range loss during the past century. Analysis of 936 bp of mitochondrial DNA of 245 extant specimens across the current range revealed a surprisingly large number of haplotypes (87), and a high level of haplotype diversity (Hd = 0.875). In contrast, historic specimens (6) from the lost range (Rhine catchment) were not differentiated from the extant Rába population (F ST = 0.02, p = 0.61), despite considerable geographic distance separating the two rivers. These observations can be explained by an overlap of the current with the historic (Pleistocene) refugia of the species. Most likely, the massive recent range loss mainly affected the range which was occupied by rapid post-glacial dispersal. We conclude that massive range losses do not necessarily coincide with genetic impoverishment and that a species' history must be considered when estimating loss of genetic diversity. The assessment of spatial genetic structures and prior phylogeographic information seems essential to conserve once widespread species.
Reporting on the southernmost locality in Costa Rica and the first two localities in Panama, we extend the known geographic distribution of the lizard Potamites apodemus (Uzzell, 1966) roughly 20 km eastwards, 40 km southwards, and 175 m in elevation. We provide photos of Panamanian specimens, comment on their morphology, and map the distribution of this unique species.
The aim of this study was to assess the invasion risk of freshwater habitats and determine the environmental variables that are most favorable for the establishment of alien amphipods, isopods, gastropods, and bivalves. A total of 981 sites located in streams and rivers in Germany. Therefore we analyzed presence-absence data of alien and indigenous amphipods, isopods, gastropods, and bivalves from 981 sites located in small to large rivers in Germany with regard to eight environmental variables: chloride, ammonium, nitrate, oxygen, orthophosphate, distance to the next navigable waterway, and maximum and minimum temperature. Degraded sites close to navigable waters were exposed to an increased invasion risk by all major groups of alien species. Moreover, invaded sites by all four groups of alien species were similar, whereas the sites where indigenous members of the four groups occurred were more variable. Increased temperature and chloride concentration as well as decreased oxygen concentration were identified as major factors for the invasibility of a site. Species-specific analyses showed that chloride was among the three most predictive environmental variables determining species assemblage in all four taxonomic groups. Also distance to the next navigable waterways was similarly important. Additionally, the minimum temperature was among the most important variables for amphipods, isopods, and bivalves. The bias in the occurrence patterns of alien species toward similarly degraded habitats suggests that the members of all four major groups of freshwater alien species are a non-random, more tolerant set of species. Their common tolerance to salinity, high temperature, and oxygen depletion may reflect that most alien species were spread in ballast water tanks, where strong selective pressures, particularly temperature fluctuations, oxygen depletion, and increased salinity may create a bottleneck for successful invasion. Knowledge on the major factors that influence the invasion risk of a habitat is needed to develop strategies to limit the spread of invasive species.
Patterns of post-glacial genetic differentiation in marginal populations of a marine microalga
(2012)
This study investigates the genetic structure of an eukaryotic microorganism, the toxic dinoflagellate Alexandrium ostenfeldii, from the Baltic Sea, a geologically young and ecologically marginal brackish water estuary which is predicted to support evolution of distinct, genetically impoverished lineages of marine macroorganisms. Analyses of the internal transcribed spacer (ITS) sequences and Amplified Fragment Length Polymorphism (AFLP) of 84 A. ostenfeldii isolates from five different Baltic locations and multiple external sites revealed that Baltic A. ostenfeldii is phylogenetically differentiated from other lineages of the species and micro-geographically fragmented within the Baltic Sea. Significant genetic differentiation (FST) between northern and southern locations was correlated to geographical distance. However, instead of discrete genetic units or continuous genetic differentiation, the analysis of population structure suggests a complex and partially hierarchic pattern of genetic differentiation. The observed pattern suggests that initial colonization was followed by local differentiation and varying degrees of dispersal, most likely depending on local habitat conditions and prevailing current systems separating the Baltic Sea populations. Local subpopulations generally exhibited low levels of overall gene diversity. Association analysis suggests predominately asexual reproduction most likely accompanied by frequency shifts of clonal lineages during planktonic growth. Our results indicate that the general pattern of genetic differentiation and reduced genetic diversity of Baltic populations found in large organisms also applies to microscopic eukaryotic organisms.
Assessing the uncertainties of simulation results of ecological models is becoming of increasing importance, specifically if these models are used to estimate greenhouse gas emissions at site to regional/national levels. Four general sources of uncertainty effect the outcome of process-based models: (i) uncertainty of information used to initialise and drive the model, (ii) uncertainty of model parameters describing specific ecosystem processes, (iii) uncertainty of the model structure and (iv) accurateness of measurements (e.g. soil-atmosphere greenhouse gas exchange) which are used for model testing and development.
The aim of our study was to assess the simulation uncertainty of the process-based biogeochemical model LandscapeDNDC. For this we set up a Bayesian framework using a Markov Chain Monte Carlo (MCMC) method, to estimate the joint model parameter distribution. Data for model testing, parameter estimation and uncertainty assessment were taken from observations of soil fluxes of nitrous oxide (N2O), nitric oxide (NO), and carbon dioxide (CO2) as observed over a 10 yr period at the spruce site of the Höglwald Forest, Germany. By running four independent Markov Chains in parallel with identical properties (except for the parameter start values), an objective criteria for chain convergence developed by Gelman et al. (2003) could be used.
Our approach showed that by means of the joined parameter distribution, we were able not only to limit the parameter space and specify the probability of parameter values, but also to assess the complex dependencies among model parameters used for simulating soil C and N trace gas emissions. This helped to improve the understanding of the behaviour of the complex LandscapeDNDC model while simulating soil C and N turnover processes and associated C and N soil-atmosphere exchange.
In a final step the parameter distribution of the most sensitive parameters determining soil-atmosphere C and N exchange were used to obtain the parameter-induced uncertainty of simulated N2O, NO and CO2 emissions. These were compared to observational data of the calibration set (6 yr) and an independent validation set of 4 yr.
The comparison showed that most of the annual observed trace gas emissions were in the range of simulated values and were predicted with a high certainty (Residual mean squared error (RMSE) NO: 2.5 to 21.3 g N ha−1 d−1, N2O: 0.2 to 21.4 g N ha−1 d−1, CO2: 5.8 to 12.6 kg C ha−1 d−1). However, LandscapeDNDC simulations were sometimes limited to accurately predict observed seasonal variations in fluxes.
Assessing the uncertainties of simulation results of ecological models is becoming increasingly important, specifically if these models are used to estimate greenhouse gas emissions on site to regional/national levels. Four general sources of uncertainty effect the outcome of process-based models: (i) uncertainty of information used to initialise and drive the model, (ii) uncertainty of model parameters describing specific ecosystem processes, (iii) uncertainty of the model structure, and (iv) accurateness of measurements (e.g., soil-atmosphere greenhouse gas exchange) which are used for model testing and development.
The aim of our study was to assess the simulation uncertainty of the process-based biogeochemical model LandscapeDNDC. For this we set up a Bayesian framework using a Markov Chain Monte Carlo (MCMC) method, to estimate the joint model parameter distribution. Data for model testing, parameter estimation and uncertainty assessment were taken from observations of soil fluxes of nitrous oxide (N2O), nitric oxide (NO) and carbon dioxide (CO2) as observed over a 10 yr period at the spruce site of the Höglwald Forest, Germany. By running four independent Markov Chains in parallel with identical properties (except for the parameter start values), an objective criteria for chain convergence developed by Gelman et al. (2003) could be used.
Our approach shows that by means of the joint parameter distribution, we were able not only to limit the parameter space and specify the probability of parameter values, but also to assess the complex dependencies among model parameters used for simulating soil C and N trace gas emissions. This helped to improve the understanding of the behaviour of the complex LandscapeDNDC model while simulating soil C and N turnover processes and associated C and N soil-atmosphere exchange. In a final step the parameter distribution of the most sensitive parameters determining soil-atmosphere C and N exchange were used to obtain the parameter-induced uncertainty of simulated N2O, NO and CO2 emissions. These were compared to observational data of an calibration set (6 yr) and an independent validation set of 4 yr. The comparison showed that most of the annual observed trace gas emissions were in the range of simulated values and were predicted with a high certainty (Root-mean-squared error (RMSE) NO: 2.4 to 18.95 g N ha−1 d−1, N2O: 0.14 to 21.12 g N ha−1 d−1, CO2: 5.4 to 11.9 kg C ha−1 d−1). However, LandscapeDNDC simulations were sometimes still limited to accurately predict observed seasonal variations in fluxes.