BackgroundCalifornia is a world floristic biodiversity hotspot where the terms neo- and paleo-endemism were first applied. Using spatial phylogenetics, it is now possible to evaluate biodiversity from an evolutionary standpoint, including discovering significant areas of neo- and paleo-endemism, by combining spatial information from museum collections and DNA-based phylogenies. Here we used a distributional dataset of 1.39 million herbarium specimens, a phylogeny of 1083 operational taxonomic units (OTUs) and 9 genes, and a spatial randomization test to identify regions of significant phylogenetic diversity, relative phylogenetic diversity, and phylogenetic endemism (PE), as well as to conduct a categorical analysis of neo- and paleo-endemism (CANAPE).ResultsWe found (1) extensive phylogenetic clustering in the South Coast Ranges, southern Great Valley, and deserts of California; (2) significant concentrations of short branches in the Mojave and Great Basin Deserts and the South Coast Ranges and long branches in the northern Great Valley, Sierra Nevada foothills, and the northwestern and southwestern parts of the state; (3) significant concentrations of paleo-endemism in Northwestern California, the northern Great Valley, and western Sonoran Desert, and neo-endemism in the White-Inyo Range, northern Mojave Desert, and southern Channel Islands. Multiple analyses were run to observe the effects on significance patterns of using different phylogenetic tree topologies (uncalibrated trees versus time-calibrated ultrametric trees) and using different representations of OTU ranges (herbarium specimen locations versus species distribution models).ConclusionsThese analyses showed that examining the geographic distributions of branch lengths in a statistical framework adds a new dimension to California floristics that, in comparison with climatic data, helps to illuminate causes of endemism. In particular, the concentration of significant PE in more arid regions of California extends previous ideas about aridity as an evolutionary stimulus. The patterns seen are largely robust to phylogenetic uncertainty and time calibration but are sensitive to the use of occurrence data versus modeled ranges, indicating that special attention toward improving geographic distributional data should be top priority in the future for advancing understanding of spatial patterns of biodiversity.Electronic supplementary materialThe online version of this article (doi:10.1186/s12915-017-0435-x) contains supplementary material, which is available to authorized users.
The genus Scouleria has three to five traditionally recognized species from Northeast Asia, western North America, and southern South America. While the genus is well defined by several morphological synapomorphies, species circumscriptions have varied, especially with respect to narrow versus broad concepts of S. aqiialica. We used Maximum Likelihood and Bayesian phylogenetic analyses of ITS and the chloroplast loci ndliA, trnS-trnG, and rpL32-trnL to test species circumscriptions and to re-evaluate an earlier hypothesis of evolutionary relationships within the genus. Our results strongly support the recognition of S. marginata and S. patagónica as currently recognized based on geography and morphology. Phylogenetic patterns within S. aquatica sensu lato support the resurrection of two northeast Asian species, S. rschewinii and S. pukhcrrima as distinct from North American S. aquatica sensu stricto. In addition, tlie recognition of the North American S. "species A" sensu Norris and Shevock (2004) as distinct from S. aquatica sensu stricto is supported. In al] analyses, Drummondia prorepens (Drummondiaceae), rather than Tridontium tasmanicum (Scouleriaceae), was resolved as sister to Scouleria, thus providing support for the placement of Tridontium outside of Scouleriaceae.
Automation of a technical process involves the feedback of sensor data for the automated control of particular aspects of the process itself. The same feedback data can be used for other applications such as health monitoring of systems or to update a graphical user interface or to analysis process performance. In order for this data to be utilized effectively, a system architecture must be designed to provide such functionality. This architecture must accommodate the dependencies of the system and sustain the required data transmission speed to ensure stability and data integrity. Such an architecture is presented in this paper, which shows how the data needs of multiple applications are satisfied from a single source of data. Also it will show that the flexibility of this architecture enables the integration of additional data sources that can be used to protect the performance of applications that consume the data as the order of data dependencies grows.
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