Given the global continuous rise, artificial light at night is often considered a driving force behind moth population declines. Although negative effects on individuals have been shown, there is no evidence for effects on population sizes to date. Therefore, we compared population trends of Dutch macromoth fauna over the period 1985-2015 between moth species that differ in phototaxis and adult circadian rhythm. We found that moth species that show positive phototaxis or are nocturnally active have stronger negative population trends than species that are not attracted to light or are diurnal species. Our results indicate that artificial light at night is an important factor in explaining declines in moth populations in regions with high artificial night sky brightness. Our study supports efforts to reduce the impacts of artificial light at night by promoting lamps that do not attract insects and reduce overall levels of illumination in rural areas to reverse declines of moth populations.

Rapidly growing biological data—including molecular sequences and fossils—hold an unprecedented potential to reveal how evolutionary processes generate and maintain biodiversity. However, researchers often have to develop their own idiosyncratic workflows to integrate and analyze these data for reconstructing time-calibrated phylogenies. In addition, divergence times estimated under different methods and assumptions, and based on data of various quality and reliability, should not be combined without proper correction. Here we introduce a modular framework termed SUPERSMART (Self-Updating Platform for Estimating Rates of Speciation and Migration, Ages, and Relationships of Taxa), and provide a proof of concept for dealing with the moving targets of evolutionary and biogeographical research. This framework assembles comprehensive data sets of molecular and fossil data for any taxa and infers dated phylogenies using robust species tree methods, also allowing for the inclusion of genomic data produced through next-generation sequencing techniques. We exemplify the application of our method by presenting phylogenetic and dating analyses for the mammal order Primates and for the plant family Arecaceae (palms). We believe that this framework will provide a valuable tool for a wide range of hypothesis-driven research questions in systematics, biogeography, and evolution. SUPERSMART will also accelerate the inference of a “Dated Tree of Life” where all node ages are directly comparable.

Mycorrhizal symbiosis between soil fungi and land plants is one of the most widespread and ecologically important mutualisms on earth. It has long been hypothesized that the Glomeromycotina, the mycorrhizal symbionts of the majority of plants, facilitated colonization of land by plants in the Ordovician. This view was recently challenged by the discovery of mycorrhiza-like associations with Mucoromycotina in several early diverging lineages of land plants. Utilizing a large, species-level database of plants’ mycorrhiza-like associations and a Bayesian approach to state transition dynamics we here show that the recruitment of Mucoromycotina is the best supported transition from a non-mycorrhizal state. We further found that transitions between different combinations of either or both of Mucoromycotina and Glomeromycotina occur at high rates, and found similar promiscuity among combinations that include either or both of Glomeromycotina and Ascomycota with a nearly fixed association with Basidiomycota. Our results portray an evolutionary scenario of evolution of mycorrhizal symbiosis with a prominent role for Mucoromycotina in the early stages of land plant diversification.

BackgroundThe systematic analysis of a large number of comparable plant trait data can support investigations into phylogenetics and ecological adaptation, with broad applications in evolutionary biology, agriculture, conservation, and the functioning of ecosystems. Floras, i.e., books collecting the information on all known plant species found within a region, are a potentially rich source of such plant trait data. Floras describe plant traits with a focus on morphology and other traits relevant for species identification in addition to other characteristics of plant species, such as ecological affinities, distribution, economic value, health applications, traditional uses, and so on. However, a key limitation in systematically analyzing information in Floras is the lack of a standardized vocabulary for the described traits as well as the difficulties in extracting structured information from free text.ResultsWe have developed the Flora Phenotype Ontology (FLOPO), an ontology for describing traits of plant species found in Floras. We used the Plant Ontology (PO) and the Phenotype And Trait Ontology (PATO) to extract entity-quality relationships from digitized taxon descriptions in Floras, and used a formal ontological approach based on phenotype description patterns and automated reasoning to generate the FLOPO. The resulting ontology consists of 25,407 classes and is based on the PO and PATO. The classified ontology closely follows the structure of Plant Ontology in that the primary axis of classification is the observed plant anatomical structure, and more specific traits are then classified based on parthood and subclass relations between anatomical structures as well as subclass relations between phenotypic qualities.ConclusionsThe FLOPO is primarily intended as a framework based on which plant traits can be integrated computationally across all species and higher taxa of flowering plants. Importantly, it is not intended to replace established vocabularies or ontologies, but rather serve as an overarching framework based on which different application- and domain-specific ontologies, thesauri and vocabularies of phenotypes observed in flowering plants can be integrated.Electronic supplementary materialThe online version of this article (doi:10.1186/s13326-016-0107-8) contains supplementary material, which is available to authorized users.