Open Access

One of the major problems in evolutionary biology is to elucidate the relationships between historical events and the tempo and mode of lineage divergence. The development of relaxed molecular clock models and the increasing availability of DNA sequences resulted in more accurate estimations of taxa divergence times. However, finding the link between competing historical events and divergence is still challenging. Here we investigate assigning constrained-age priors to nodes of interest in a time-calibrated phylogeny as a means of hypothesis comparison. These priors are equivalent to historic scenarios for lineage origin. The hypothesis that best explains the data can be selected by comparing the likelihood values of the competing hypotheses, modelled with different priors. A simulation approach was taken to evaluate the performance of the prior-based method and to compare it with an unconstrained approach. We explored the effect of DNA sequence length and the temporal placement and span of competing hypotheses (i.e. historic scenarios) on selection of the correct hypothesis and the strength of the inference. Competing hypotheses were compared applying a posterior simulation analogue of the Akaike Information Criterion and Bayes factors (obtained after calculation of the marginal likelihood with three estimators: Harmonic Mean, Stepping Stone and Path Sampling). We illustrate the potential application of the prior-based method on an empirical data set to compare competing geological hypotheses explaining the biogeographic patterns in Pleurodeles newts. The correct hypothesis was selected on average 89% times. The best performance was observed with DNA sequence length of 3500-10000 bp. The prior-based method is most reliable when the hypotheses compared are not temporally too close. The strongest inferences were obtained when using the Stepping Stone and Path Sampling estimators. The prior-based approach proved effective in discriminating between competing hypotheses when used on empirical data. The unconstrained analyses performed well but it probably requires additional computational effort. Researchers applying this approach should rely only on inferences with moderate to strong support. The prior-based approach could be applied on biogeographical and phylogeographical studies where robust methods for historical inferences are still lacking.

Global water models (GWMs) simulate the terrestrial water cycle, on the global scale, and are used to assess the impacts of climate change on freshwater systems. GWMs are developed within different modeling frameworks and consider different underlying hydrological processes, leading to varied model structures. Furthermore, the equations used to describe various processes take different forms and are generally accessible only from within the individual model codes. These factors have hindered a holistic and detailed understanding of how different models operate, yet such an understanding is crucial for explaining the results of model evaluation studies, understanding inter-model differences in their simulations, and identifying areas for future model development. This study provides a comprehensive overview of how state-of-the-art GWMs are designed. We analyze water storage compartments, water flows, and human water use sectors included in 16 GWMs that provide simulations for the Inter-Sectoral Impact Model Intercomparison Project phase 2b (ISIMIP2b). We develop a standard writing style for the model equations to further enhance model improvement, intercomparison, and communication. In this study, WaterGAP2 used the highest number of water storage compartments, 11, and CWatM used 10 compartments. Seven models used six compartments, while three models (JULES-W1, Mac-PDM.20, and VIC) used the lowest number, three compartments. WaterGAP2 simulates five human water use sectors, while four models (CLM4.5, CLM5.0, LPJmL, and MPIHM) simulate only water used by humans for the irrigation sector. We conclude that even though hydrologic processes are often based on similar equations, in the end, these equations have been adjusted or have used different values for specific parameters or specific variables. Our results highlight that the predictive uncertainty of GWMs can be reduced through improvements of the existing hydrologic processes, implementation of new processes in the models, and high-quality input data.

Combinatorial CRISPR-Cas screens have advanced the mapping of genetic interactions, but their experimental scale limits the number of targetable gene combinations. Here, we describe 3Cs multiplexing, a rapid and scalable method to generate highly diverse and uniformly distributed combinatorial CRISPR libraries. We demonstrate that the library distribution skew is the critical determinant of its required screening coverage. By circumventing iterative cloning of PCR-amplified oligonucleotides, 3Cs multiplexing facilitates the generation of combinatorial CRISPR libraries with low distribution skews. We show that combinatorial 3Cs libraries can be screened with minimal coverages, reducing associated efforts and costs at least 10-fold. We apply a 3Cs multiplexing library targeting 12,736 autophagy gene combinations with 247,032 paired gRNAs in viability and reporter-based enrichment screens. In the viability screen, we identify, among others, the synthetic lethal WDR45B-PIK3R4 and the proliferation-enhancing ATG7-KEAP1 genetic interactions. In the reporter-based screen, we identify over 1,570 essential genetic interactions for autophagy flux, including interactions among paralogous genes, namely ATG2A-ATG2B, GABARAP-MAP1LC3B and GABARAP-GABARAPL2. However, we only observe few genetic interactions within paralogous gene families of more than two members, indicating functional compensation between them. This work establishes 3Cs multiplexing as a platform for genetic interaction screens at scale.

Peronospora aquilegiicola is a destructive pathogen of columbines and has wiped out most Aquilegia cultivars in several private and public gardens throughout Britain. The pathogen, which is native to East Asia was noticed in England and Wales in 2013 and quickly spread through the country, probably by infested plants or seeds. To our knowledge, the pathogen has so far not been reported from other parts of Europe. Here, we report the emergence of the pathogen in the northwest of Germany, based on morphological and phylogenetic evidence. As the pathogen was found in a garden in which no new columbines had been planted recently, we assume that the pathogen has already spread from its original point of introduction in Germany. This calls for an increased attention to the further spread of the pathogen and the eradication of infection spots to avoid the spread to naturally occurring columbines in Germany and to prevent another downy mildew from becoming a global threat, like Peronospora belbahrii and Plasmopara destructor, the downy mildews of basil and balsamines, respectively.

Nature benefits human health. To date, however, little is known whether biodiversity relates to human health. While some local and city level studies show that species diversity, as a measure of biodiversity, can have positive effects, there is a lack of studies about the relationship between different species diversity measures and human health, especially at larger spatial scales. Here, we conduct cross-sectional analyses of the association between species diversity and human health across Germany, while controlling for socio-economic factors and other nature characteristics. As indicators for human health, we use the mental (MCS) and physical health (PCS) component scales of the German Socio-Economic Panel (SOEP, Short Form Health Questionnaire – SF12). For species diversity, we use species richness and abundance estimates of two species groups: plants and birds. We phrase the following hypotheses: plant and bird species are positively associated with mental and physical health (H1 & H3); bird abundance is positively related to mental health (H2). Our results demonstrate a significant positive relationship between plant and bird species richness and mental health across all model variations controlling for a multitude of other factors. These results highlight the importance for species diversity for people’s mental health and well-being. Therefore, policy makers, landscape planners and greenspace managers on the local and national level should consider supporting biodiverse environments to promote mental health and wellbeing. For this purpose, we propose to use species diversity measures as indicators for salutogenic (health promoting) characteristics of nature, landscape and urban green space.