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Intensive land use is a driving force for biodiversity decline in many ecosystems. In semi-natural grasslands, land-use activities such as mowing, grazing and fertilization affect the diversity of plants and arthropods, but the combined effects of different drivers and the chain of effects are largely unknown. In this study we used structural equation modelling to analyse how the arthropod communities in managed grasslands respond to land use and whether these responses are mediated through changes in resource diversity or resource quantity (biomass). Plants were considered resources for herbivores which themselves were considered resources for predators. Plant and arthropod (herbivores and predators) communities were sampled on 141 meadows, pastures and mown pastures within three regions in Germany in 2008 and 2009. Increasing land-use intensity generally increased plant biomass and decreased plant diversity, mainly through increasing fertilization. Herbivore diversity decreased together with plant diversity but showed no response to changes in plant biomass. Hence, land-use effects on herbivore diversity were mediated through resource diversity rather than quantity. Land-use effects on predator diversity were mediated by both herbivore diversity (resource diversity) and herbivore quantity (herbivore biomass), but indirect effects through resource quantity were stronger. Our findings highlight the importance of assessing both direct and indirect effects of land-use intensity and mode on different trophic levels. In addition to the overall effects, there were subtle differences between the different regions, pointing to the importance of regional land-use specificities. Our study underlines the commonly observed strong effect of grassland land use on biodiversity. It also highlights that mechanistic approaches help us to understand how different land-use modes affect biodiversity.
An ever-increasing demand for novel antimicrobials to treat life-threatening infections caused by the global spread of multidrug-resistant bacterial pathogens stands in stark contrast to the current level of investment in their development, particularly in the fields of natural-product-derived and synthetic small molecules. New agents displaying innovative chemistry and modes of action are desperately needed worldwide to tackle the public health menace posed by antimicrobial resistance. Here, our consortium presents a strategic blueprint to substantially improve our ability to discover and develop new antibiotics. We propose both short-term and long-term solutions to overcome the most urgent limitations in the various sectors of research and funding, aiming to bridge the gap between academic, industrial and political stakeholders, and to unite interdisciplinary expertise in order to efficiently fuel the translational pipeline for the benefit of future generations.
Forest fragmentation and selective logging are two main drivers of global environmental change and modify biodiversity and environmental conditions in many tropical forests. The consequences of these changes for the functioning of tropical forest ecosystems have rarely been explored in a comprehensive approach. In a Kenyan rainforest, we studied six animal-mediated ecosystem processes and recorded species richness and community composition of all animal taxa involved in these processes. We used linear models and a formal meta-analysis to test whether forest fragmentation and selective logging affected ecosystem processes and biodiversity and used structural equation models to disentangle direct from biodiversity-related indirect effects of human disturbance on multiple ecosystem processes. Fragmentation increased decomposition and reduced antbird predation, while selective logging consistently increased pollination, seed dispersal and army-ant raiding. Fragmentation modified species richness or community composition of five taxa, whereas selective logging did not affect any component of biodiversity. Changes in the abundance of functionally important species were related to lower predation by antbirds and higher decomposition rates in small forest fragments. The positive effects of selective logging on bee pollination, bird seed dispersal and army-ant raiding were direct, i.e. not related to changes in biodiversity, and were probably due to behavioural changes of these highly mobile animal taxa. We conclude that animal-mediated ecosystem processes respond in distinct ways to different types of human disturbance in Kakamega Forest. Our findings suggest that forest fragmentation affects ecosystem processes indirectly by changes in biodiversity, whereas selective logging influences processes directly by modifying local environmental conditions and resource distributions. The positive to neutral effects of selective logging on ecosystem processes show that the functionality of tropical forests can be maintained in moderately disturbed forest fragments. Conservation concepts for tropical forests should thus include not only remaining pristine forests but also functionally viable forest remnants.
Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.
Crista junctions (CJs) are important for mitochondrial organization and function, but the molecular basis of their formation and architecture is obscure. We have identified and characterized a mitochondrial membrane protein in yeast, Fcj1 (formation of CJ protein 1), which is specifically enriched in CJs. Cells lacking Fcj1 lack CJs, exhibit concentric stacks of inner membrane in the mitochondrial matrix, and show increased levels of F1FO–ATP synthase (F1FO) supercomplexes. Overexpression of Fcj1 leads to increased CJ formation, branching of cristae, enlargement of CJ diameter, and reduced levels of F1FO supercomplexes. Impairment of F1FO oligomer formation by deletion of its subunits e/g (Su e/g) causes CJ diameter enlargement and reduction of cristae tip numbers and promotes cristae branching. Fcj1 and Su e/g genetically interact. We propose a model in which the antagonism between Fcj1 and Su e/g locally modulates the F1FO oligomeric state, thereby controlling membrane curvature of cristae to generate CJs and cristae tips.
High-throughput gene trapping is a random approach for inducing insertional mutations across the mouse genome. This approach uses gene trap vectors that simultaneously inactivate and report the expression of the trapped gene at the insertion site, and provide a DNA tag for the rapid identification of the disrupted gene. Gene trapping has been used by both public and private institutions to produce libraries of embryonic stem (ES) cells harboring mutations in single genes. Presently,~ 66% of the protein coding genes in the mouse genome have been disrupted by gene trap insertions. Among these, however, genes encoding signal peptides or transmembrane domains (secretory genes) are underrepresented because they are not susceptible to conventional trapping methods. Here, we describe a high-throughput gene trapping strategy that effectively targets secretory genes. We used this strategy to assemble a library of ES cells harboring mutations in 716 unique secretory genes, of which 61% were not trapped by conventional trapping, indicating that the two strategies are complementary. The trapped ES cell lines, which can be ordered from the International Gene Trap Consortium (http://www.genetrap.org), are freely available to the scientific community.