Institutes
Refine
Document Type
- Preprint (6) (remove)
Language
- English (6) (remove)
Has Fulltext
- yes (6)
Is part of the Bibliography
- no (6)
Keywords
Institute
- Senckenbergische Naturforschende Gesellschaft (6) (remove)
The establishment and maintenance of protected areas (PAs) is viewed as a key action in delivering post-2020 biodiversity targets. PAs often need to meet multiple objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation, but available land and conservation funding is limited. Therefore, optimizing resources by selecting the most beneficial PAs is vital. Here, we advocate for a flexible and transparent approach to selecting protected areas based on multiple objectives, and illustrate this with a decision support tool on a global scale. The tool allows weighting and prioritization of different conservation objectives according to user-specified preferences, as well as real-time comparison of the selected areas that result from such different priorities. We apply the tool across 1347 terrestrial PAs and highlight frequent trade-offs among different objectives, e.g., between species protection and ecosystem integrity. Outputs indicate that decision makers frequently face trade-offs among conflicting objectives. Nevertheless, we show that transparent decision-support tools can reveal synergies and trade-offs associated with PA selection, thereby helping to illuminate and resolve land-use conflicts embedded in divergent societal and political demands and values.
The establishment and maintenance of protected areas(PAs) is viewed as a key action in delivering post-2020 biodiversity targets. PAs often need to meet a multitude of objectives, ranging from biodiversity protection to ecosystem service provision and climate change mitigation. As available land and conservation funding are limited, optimizing resources by selecting the most beneficial PAs is vital. Here we present a decision support tool that enables a flexible approach to PA selection on a global scale, allowing different conservation objectives to be weighted and prioritized according to user-specified preferences. We apply the tool across 1347 terrestrial PAs and highlight frequent trade-offs among different objectives, e.g., between biodiversity protection and ecosystem integrity. These results indicate that decision makers must usually decide among conflicting objectives. To assist this our decision support tool provides an explicitly value-based approach that can help resolve such conflicts by considering divergent societal and political demands and values.
The basidiomycete smut fungi are predominantly plant parasitic, causing severe losses in some crops. Most species feature a saprotrophic haploid yeast stage, and several smut fungi are only known from this stage, with some isolated from habitats without suitable hosts, e.g. from Antarctica. Thus, these species are generally believed to be apathogenic, but recent findings that some of these might have a plant pathogenic sexual counterpart, casts doubts on the validity of this hypothesis. Here, four Pseudozyma genomes were re-annotated and compared to published smut pathogens and the well-characterised effector gene Pep1 from these species was checked for its ability to complement a Pep1 deletion strain of Ustilago maydis. It was found that 113 high-confidence putative effector proteins were conserved among smut and Pseudozyma genomes. Among these were several validated effector proteins, including Pep1. By genetic complementation we show that Pep1 homologs from the supposedly apathogenic yeasts restore virulence in Pep1-deficient mutants Ustilago maydis. Thus, it is concluded that Pseudozyma species have retained a suite of effectors. This hints at the possibility that Pseudozyma species have kept an unknown plant pathogenic stage for sexual recombination or that these effectors have positive effects when colonising plant surfaces.
Orthologs document the evolution of genes and metabolic capacities encoded in extant and ancient genomes. Orthologous genes that are detected across the full diversity of contemporary life allow reconstructing the gene set of LUCA, the last universal common ancestor. These genes presumably represent the functional repertoire common to – and necessary for – all living organisms. Design of artificial life has the potential to test this. Recently, a minimal gene (MG) set for a self-replicating cell was determined experimentally, and a surprisingly high number of genes have unknown functions and are not represented in LUCA. However, as similarity between orthologs decays with time, it becomes insufficient to infer common ancestry, leaving ancient gene set reconstructions incomplete and distorted to an unknown extent. Here we introduce the evolutionary traceability, together with the software protTrace, that quantifies, for each protein, the evolutionary distance beyond which the sensitivity of the ortholog search becomes limiting. We show that the LUCA set comprises only high-traceable proteins most of which have catalytic functions. We further show that proteins in the MG set lacking orthologs outside bacteria mostly have low traceability, leaving open whether their eukaryotic orthologs have just been overlooked. On the example of REC8, a protein essential for chromosome cohesion, we demonstrate how a traceability-informed adjustment of the search sensitivity identifies hitherto missed orthologs in the fast-evolving microsporidia. Taken together, the evolutionary traceability helps to differentiate between true absence and non-detection of orthologs, and thus improves our understanding about the evolutionary conservation of functional protein networks.
The most basic behavioural states of animals can be described as active or passive. However, while high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which the automated VHF radio-tracking of small vertebrates fitted with lightweight transmitters (< 0.2 g) is used to distinguish between active and passive behavioural states.
A dataset containing > 3 million VHF signals was used to train and test a random forest model in the assignment of either active or passive behaviour to individuals from two forest-dwelling bat species (Myotis bechsteinii (n = 50) and Nyctalus leisleri (n = 20)). The applicability of the model to other taxonomic groups was demonstrated by recording and classifying the behaviour of a tagged bird and by simulating the effect of different types of vertebrate activity with the help of humans carrying transmitters. The random forest model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F-score 0.96–0.98).
The utility of the model in tackling ecologically relevant questions was demonstrated in a study of the differences in the daily activity patterns of the two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that significant differences in the timing of species activity according to ecological preferences or seasonality can be distinguished using our method.
Our approach enables the assignment of VHF signal patterns to fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radio-tracking method, we provide the trained random forest models together with an R-package that includes all necessary data-processing functionalities. In combination with state-of-the-art open-source automated radio-tracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.
Bacterial biosynthetic assembly lines, such as non-ribosomal peptide synthetases (NRPS) and polyketide synthases, are often subject of synthetic biology – because they produce a variety of natural products invaluable for modern pharmacotherapy. Acquiring the ability to engineer these biosynthetic assembly lines allows the production of artificial non-ribosomal peptides (NRP), polyketides, and hybrids thereof with new or improved properties. However, traditional bioengineering approaches have suffered for decades from their very limited applicability and, unlike combinatorial chemistry, are stigmatized as inefficient because they cannot be linked to the high-throughput screening platforms of the pharmaceutical industry. Although combinatorial chemistry can generate new molecules cheaper, faster, and in greater numbers than traditional natural product discovery and bioengineering approaches, it does not meet current medical needs because it covers only a limited biologically relevant chemical space. Hence, methods for high-throughput generation of new natural product-like compound libraries could provide a new avenue towards the identification of new lead compounds. To this end, prior to this work, we introduced an artificial synthetic NRPS type, referred to as type S NRPS, to provide a first-of-its-kind bicombinatorial approach to parallelized high-throughput NRP library generation. However, a bottleneck of these first two generations of type S NRPS was a significant drop in production yields. To address this issue, we applied an iterative optimization process that enabled titer increases of up to 55-fold compared to the non-optimized equivalents, restoring them to wild-type levels and beyond.