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Right on track?
(2019)
Satellite telemetry is an increasingly utilized technology in wildlife research, and current devices can track individual animal movements at unprecedented spatial and temporal resolutions. However, as we enter the golden age of satellite telemetry, we need an in-depth understanding of the main technological, species-specific and environmental factors that determine the success and failure of satellite tracking devices across species and habitats. Here, we assess the relative influence of such factors on the ability of satellite telemetry units to provide the expected amount and quality of data by analyzing data from over 3,000 devices deployed on 62 terrestrial species in 167 projects worldwide. We evaluate the success rate in obtaining GPS fixes as well as in transferring these fixes to the user and we evaluate failure rates. Average fix success and data transfer rates were high and were generally better predicted by species and unit characteristics, while environmental characteristics influenced the variability of performance. However, 48% of the unit deployments ended prematurely, half of them due to technical failure. Nonetheless, this study shows that the performance of satellite telemetry applications has shown improvements over time, and based on our findings, we provide further recommendations for both users and manufacturers.
River ecosystems receive and process vast quantities of terrestrial organic carbon, the fate of which depends strongly on microbial activity. Variation in and controls of processing rates, however, are poorly characterized at the global scale. In response, we used a peer-sourced research network and a highly standardized carbon processing assay to conduct a global-scale field experiment in greater than 1000 river and riparian sites. We found that Earth’s biomes have distinct carbon processing signatures. Slow processing is evident across latitudes, whereas rapid rates are restricted to lower latitudes. Both the mean rate and variability decline with latitude, suggesting temperature constraints toward the poles and greater roles for other environmental drivers (e.g., nutrient loading) toward the equator. These results and data set the stage for unprecedented “next-generation biomonitoring” by establishing baselines to help quantify environmental impacts to the functioning of ecosystems at a global scale.
The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia
(2019)
The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.
Being at the western fringe of Europe, Iberia had a peculiar prehistory and a complex pattern of Neolithization. A few studies, all based on modern populations, reported the presence of DNA of likely African origin in this region, generally concluding it was the result of recent gene flow, probably during the Islamic period. Here, we provide evidence of much older gene flow from Africa to Iberia by sequencing whole genomes from four human remains from northern Portugal and southern Spain dated around 4000 years BP (from the Middle Neolithic to the Bronze Age). We found one of them to carry an unequivocal sub-Saharan mitogenome of most probably West or West-Central African origin, to our knowledge never reported before in prehistoric remains outside Africa. Our analyses of ancient nuclear genomes show small but significant levels of sub-Saharan African affinity in several ancient Iberian samples, which indicates that what we detected was not an occasional individual phenomenon, but an admixture event recognizable at the population level. We interpret this result as evidence of an early migration process from Africa into the Iberian Peninsula through a western route, possibly across the Strait of Gibraltar.
Specialisation and diversity of multiple trophic groups are promoted by different forest features
(2019)
While forest management strongly influences biodiversity, it remains unclear how the structural and compositional changes caused by management affect different community dimensions (e.g. richness, specialisation, abundance or completeness) and how this differs between taxa. We assessed the effects of nine forest features (representing stand structure, heterogeneity and tree composition) on thirteen above- and belowground trophic groups of plants, animals, fungi and bacteria in 150 temperate forest plots differing in their management type. Canopy cover decreased light resources, which increased community specialisation but reduced overall diversity and abundance. Features increasing resource types and diversifying microhabitats (admixing of oaks and conifers) were important and mostly affected richness. Belowground groups responded differently to those aboveground and had weaker responses to most forest features. Our results show that we need to consider forest features rather than broad management types and highlight the importance of considering several groups and community dimensions to better inform conservation.
Intraspecific genetic diversity and distribution of North African hedgehogs (Mammalia: Erinaceidae)
(2019)
Despite growing efforts to halt biodiversity loss, knowledge of species diversity and distribution is highly geographically biased, leaving some areas unexplored. Taxa distributed in remote, desert areas, such as hedgehogs (Mammalia; Eulipotyphla) in North Africa, are good examples of current knowledge gaps in systematics and biogeography. Here we studied the geographical distribution and intraspecific genetic diversity of hedgehogs in North Africa. Specimens belonging to North African and Eurasian species were analysed with mitochondrial (control region, CR) and nuclear (recombination activating gene 1, RAG1) gene fragments. This revealed a broader geographical distribution of Atelerix algirus in south-western Libya and of Paraechinus aethiopicus along the Atlantic Sahara. High intraspecific genetic differentiation was found in A. algirus and A. albiventris at the mitochondrial level, with nuclear haplotype sharing across their ranges. These findings suggest that biogeographical patterns of hedgehogs in North Africa are more complex than previously suggested, highlighting a need for further investigation in this remote and poorly known area.
The intrinsic predictability of ecological time series and its potential to guide forecasting
(2019)
Influenza A virus is a pathogen responsible for severe seasonal epidemics threatening human and animal populations every year. One of the ten major proteins encoded by the viral genome, the matrix protein M1, is abundantly produced in infected cells and plays a structural role in determining the morphology of the virus. During assembly of new viral particles, M1 is recruited to the host cell membrane where it associates with lipids and other viral proteins. The structure of M1 is only partially known. In particular, structural details of M1 interactions with the cellular plasma membrane as well as M1 protein interactions and multimerization have not been clarified, yet. In this work, we employed a set of complementary experimental and theoretical tools to tackle these issues. Using raster image correlation, surface plasmon resonance and circular dichroism spectroscopies, we quantified membrane association and oligomerization of full-length M1 and of different genetically engineered M1 constructs (i.e., N- and C-terminally truncated constructs and a mutant of the polybasic region, residues 95-105). Furthermore, we report novel information on structural changes in M1 occurring upon binding to membranes. Our experimental results are corroborated by an all-atom model of the full-length M1 protein bound to a negatively charged lipid bilayer.
Enhancers are critical for developmental stage-specific gene expression, but their dynamic regulation in plants remains poorly understood. Here we compare genome-wide localization of H3K27ac, chromatin accessibility and transcriptomic changes during flower development in Arabidopsis. H3K27ac prevalently marks promoter-proximal regions, suggesting that H3K27ac is not a hallmark for enhancers in Arabidopsis. We provide computational and experimental evidence to confirm that distal DNase. hypersensitive sites are predictive of enhancers. The predicted enhancers are highly stage-specific across flower development, significantly associated with SNPs for flowering-related phenotypes, and conserved across crucifer species. Through the integration of genome-wide transcription factor (TF) binding datasets, we find that floral master regulators and stage-specific TFs are largely enriched at developmentally dynamic enhancers. Finally, we show that enhancer clusters and intronic enhancers significantly associate with stage-specific gene regulation by floral master TFs. Our study provides insights into the functional flexibility of enhancers during plant development, as well as hints to annotate plant enhancers.
Habitat fragmentation threatens global biodiversity. To date, there is only limited understanding of how the different aspects of habitat fragmentation (habitat loss, number of fragments and isolation) affect species diversity within complex ecological networks such as food webs. Here, we present a dynamic and spatially explicit food web model which integrates complex food web dynamics at the local scale and species-specific dispersal dynamics at the landscape scale, allowing us to study the interplay of local and spatial processes in metacommunities. We here explore how the number of habitat patches, i.e. the number of fragments, and an increase of habitat isolation affect the species diversity patterns of complex food webs (alpha-,beta-,gamma-, diversities). We specifically test whether there is a trophic dependency in the effect of these two factors on species diversity. In our model, habitat isolation is the main driver causing species loss and diversity decline. Our results emphasize that large-bodied consumer species at high trophic positions go extinct faster than smaller species at lower trophic levels, despite being superior dispersers that connect fragmented landscapes better. We attribute the loss of top species to a combined effect of higher biomass loss during dispersal with increasing habitat isolation in general, and the associated energy limitation in highly fragmented landscapes, preventing higher trophic levels to persist. To maintain trophic-complex and species-rich communities calls for effective conservation planning which considers the interdependence of trophic and spatial dynamics as well as the spatial context of a landscape and its energy availability.