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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.
Temporal variation in the detectability of a species can bias estimates of relative abundance if not handled correctly. For example, when effort varies in space and/or time it becomes necessary to take variation in detectability into account when data are analyzed. We demonstrate the importance of incorporating seasonality into the analysis of data with unequal sample sizes due to lost traps at a particular density of a species. A case study of count data was simulated using a spring-active carabid beetle. Traps were ‘lost’ randomly during high beetle activity in high abundance sites and during low beetle activity in low abundance sites. Five different models were fitted to datasets with different levels of loss. If sample sizes were unequal and a seasonality variable was not included in models that assumed the number of individuals was log-normally distributed, the models severely under- or overestimated the true effect size. Results did not improve when seasonality and number of trapping days were included in these models as offset terms, but only performed well when the response variable was specified as following a negative binomial distribution. Finally, if seasonal variation of a species is unknown, which is often the case, seasonality can be added as a free factor, resulting in well-performing negative binomial models. Based on these results we recommend (a) add sampling effort (number of trapping days in our example) to the models as an offset term, (b) if precise information is available on seasonal variation in detectability of a study object, add seasonality to the models as an offset term; (c) if information on seasonal variation in detectability is inadequate, add seasonality as a free factor; and (d) specify the response variable of count data as following a negative binomial or over-dispersed Poisson distribution.
Sucrose is known to repress the translation of Arabidopsis thaliana AtbZIP11 transcript which encodes a protein belonging to the group of S (S - stands for small) basic region-leucine zipper (bZIP)-type transcription factor. This repression is called sucrose-induced repression of translation (SIRT). It is mediated through the sucrose-controlled upstream open reading frame (SC-uORF) found in the AtbZIP11 transcript. The SIRT is reported for 4 other genes belonging to the group of S bZIP in Arabidopsis. Tobacco tbz17 is phylogenetically closely related to AtbZIP11 and carries a putative SC-uORF in its 5′-leader region. Here we demonstrate that tbz17 exhibits SIRT mediated by its SC-uORF in a manner similar to genes belonging to the S bZIP group of the Arabidopsis genus. Furthermore, constitutive transgenic expression of tbz17 lacking its 5′-leader region containing the SC-uORF leads to production of tobacco plants with thicker leaves composed of enlarged cells with 3–4 times higher sucrose content compared to wild type plants. Our finding provides a novel strategy to generate plants with high sucrose content.
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.
Spatial variations of nitrogen trace gas emissions from tropical mountain forests in Nyungwe, Rwanda
(2012)
Globally, tropical forest soils represent the second largest source of N2O and NO. However, there is still considerable uncertainty on the spatial variability and soil properties controlling N trace gas emission. Therefore, we carried out an incubation experiment with soils from 31 locations in the Nyungwe tropical mountain forest in southwestern Rwanda. All soils were incubated at three different moisture levels (50, 70 and 90 % water filled pore space (WFPS)) at 17 °C. Nitrous oxide emission varied between 4.5 and 400 μg N m−2 h−1, while NO emission varied from 6.6 to 265 μg N m−2 h−1. Mean N2O emission at different moisture levels was 46.5 ± 11.1 (50 %WFPS), 71.7 ± 11.5 (70 %WFPS) and 98.8 ± 16.4 (90 %WFPS) μg N m−2 h−1, while mean NO emission was 69.3 ± 9.3 (50 %WFPS), 47.1 ± 5.8 (70 %WFPS) and 36.1 ± 4.2 (90 %WFPS) μg N m−2 h−1. The latter suggests that climate (i.e. dry vs. wet season) controls N2O and NO emissions. Positive correlations with soil carbon and nitrogen indicate a biological control over N2O and NO production. But interestingly N2O and NO emissions also showed a positive correlation with free iron and a negative correlation with soil pH (only N2O). The latter suggest that chemo-denitrification might, at least for N2O, be an important production pathway. In conclusion improved understanding and process based modeling of N trace gas emission from tropical forests will benefit from spatially explicit trace gas emission estimates linked to basic soil property data and differentiating between biological and chemical pathways for N trace gas formation.
wo assumptions underlie current models of the geographical ranges of perennial plant species: 1. current ranges are in equilibrium with the prevailing climate, and 2. changes are attributable to changes in macroclimatic factors, including tolerance of winter cold, the duration of the growing season, and water stress during the growing season, rather than to biotic interactions. These assumptions allow model parameters to be estimated from current species ranges. Deterioration of growing conditions due to climate change, e.g. more severe drought, will cause local extinction. However, for many plant species, the predicted climate change of higher minimum temperatures and longer growing seasons means, improved growing conditions. Biogeographical models may under some circumstances predict that a species will become locally extinct, despite improved growing conditions, because they are based on an assumption of equilibrium and this forces the species range to match the species-specific macroclimatic thresholds. We argue that such model predictions should be rejected unless there is evidence either that competition influences the position of the range margins or that a certain physiological mechanism associated with the apparent improvement in growing conditions negatively affects the species performance. We illustrate how a process-based vegetation model can be used to ascertain whether such a physiological cause exists. To avoid potential modelling errors of this type, we propose a method that constrains the scenario predictions of the envelope models by changing the geographical distribution of the dominant plant functional type. Consistent modelling results are very important for evaluating how changes in species areas affect local functional trait diversity and hence ecosystem functioning and resilience, and for inferring the implications for conservation management in the face of climate change.
Protective ant-plant mutualisms that are exploited by non-defending parasitic ants represent prominent model systems for ecology and evolutionary biology. The mutualist Pseudomyrmex ferrugineus is an obligate plant-ant and fully depends on acacias for nesting space and food. The parasite Pseudomyrmex gracilis facultatively nests on acacias and uses host-derived food rewards but also external food sources. Integrative analyses of genetic microsatellite data, cuticular hydrocarbons and behavioral assays showed that an individual acacia might be inhabited by the workers of several P. gracilis queens, whereas one P. ferrugineus colony monopolizes one or more host trees. Despite these differences in social organization, neither of the species exhibited aggressive behavior among conspecific workers sharing a tree regardless of their relatedness. This lack of aggression corresponds to the high similarity of cuticular hydrocarbon profiles among ants living on the same tree. Host sharing by unrelated colonies, or the presence of several queens in a single colony are discussed as strategies by which parasite colonies could achieve the observed social organization. We argue that in ecological terms, the non-aggressive behavior of non-sibling P. gracilis workers — regardless of the route to achieve this social structure — enables this species to efficiently occupy and exploit a host plant. By contrast, single large and long-lived colonies of the mutualist P. ferrugineus monopolize individual host plants and defend them aggressively against invaders from other trees. Our findings highlight the necessity for using several methods in combination to fully understand how differing life history strategies affect social organization in ants.
Fungal populations that reproduce sexually are likely to be genetically more diverse and have a higher adaptive potential than asexually reproducing populations. Mating systems of fungal species can be self-incompatible, requiring the presence of isolates of different mating-type genes for sexual reproduction to occur, or self-compatible, requiring only one. Understanding the distribution of mating-type genes in populations can help to assess the potential of self-incompatible species to reproduce sexually. In the locally threatened epiphytic lichen-forming fungus Lobaria pulmonaria (L.) Hoffm., low frequency of sexual reproduction is likely to limit the potential of populations to adapt to changing environmental conditions. Our study provides direct evidence of self-incompatibility (heterothallism) in L. pulmonaria. It can thus be hypothesized that sexual reproduction in small populations might be limited by an unbalanced distribution of mating-type genes. We therefore assessed neutral genetic diversity (using microsatellites) and mating-type ratio in 27 lichen populations (933 individuals). We found significant differences in the frequency of the two mating types in 13 populations, indicating a lower likelihood of sexual reproduction in these populations. This suggests that conservation translocation activities aiming at maximizing genetic heterogeneity in threatened and declining populations should take into account not only presence of fruiting bodies in transplanted individuals, but also the identity and balanced representation of mating-type genes.
Our large brain, long life span and high fertility are key elements of human evolutionary success and are often thought to have evolved in interplay with tool use, carnivory and hunting. However, the specific impact of carnivory on human evolution, life history and development remains controversial. Here we show in quantitative terms that dietary profile is a key factor influencing time to weaning across a wide taxonomic range of mammals, including humans. In a model encompassing a total of 67 species and genera from 12 mammalian orders, adult brain mass and two dichotomous variables reflecting species differences regarding limb biomechanics and dietary profile, accounted for 75.5%, 10.3% and 3.4% of variance in time to weaning, respectively, together capturing 89.2% of total variance. Crucially, carnivory predicted the time point of early weaning in humans with remarkable precision, yielding a prediction error of less than 5% with a sample of forty-six human natural fertility societies as reference. Hence, carnivory appears to provide both a necessary and sufficient explanation as to why humans wean so much earlier than the great apes. While early weaning is regarded as essentially differentiating the genus Homo from the great apes, its timing seems to be determined by the same limited set of factors in humans as in mammals in general, despite some 90 million years of evolution. Our analysis emphasizes the high degree of similarity of relative time scales in mammalian development and life history across 67 genera from 12 mammalian orders and shows that the impact of carnivory on time to weaning in humans is quantifiable, and critical. Since early weaning yields shorter interbirth intervals and higher rates of reproduction, with profound effects on population dynamics, our findings highlight the emergence of carnivory as a process fundamentally determining human evolution.
Background: The genome of the carnivorous marsupial, the Tasmanian devil (Sarcophilus harrisii, Order: Dasyuromorphia), was sequenced in the hopes of finding a cure for or gaining a better understanding of the contagious devil facial tumor disease that is threatening the species’ survival. To better understand the Tasmanian devil genome, we screened it for transposable elements and investigated the dynamics of short interspersed element (SINE) retroposons.
Results: The temporal history of Tasmanian devil SINEs, elucidated using a transposition in transposition analysis, indicates that WSINE1, a CORE-SINE present in around 200,000 copies, is the most recently active element. Moreover, we discovered a new subtype of WSINE1 (WSINE1b) that comprises at least 90% of all Tasmanian devil WSINE1s. The frequencies of WSINE1 subtypes differ in the genomes of two of the other Australian marsupial orders. A co-segregation analysis indicated that at least 66 subfamilies of WSINE1 evolved during the evolution of Dasyuromorphia. Using a substitution rate derived from WSINE1 insertions, the ages of the subfamilies were estimated and correlated with a newly established phylogeny of Dasyuromorphia. Phylogenetic analyses and divergence time estimates of mitochondrial genome data indicate a rapid radiation of the Tasmanian devil and the closest relative the quolls (Dasyurus) around 14 million years ago.
Conclusions: The radiation and abundance of CORE-SINEs in marsupial genomes indicates that they may be a major player in the evolution of marsupials. It is evident that the early phases of evolution of the carnivorous marsupial order Dasyuromorphia was characterized by a burst of SINE activity. A correlation between a speciation event and a major burst of retroposon activity is for the first time shown in a marsupial genome.