Herbivory increases diversification across insect clades.

Insects contain more than half of all living species, but the causes of their remarkable diversity remain poorly understood. Many authors have suggested that herbivory has accelerated diversification in many insect clades. However, others have questioned the role of herbivory in insect diversification. Here, we test the relationships between herbivory and insect diversification across multiple scales. We find a strong, positive relationship between herbivory and diversification among insect orders. However, herbivory explains less variation in diversification within some orders (Diptera, Hemiptera) or shows no significant relationship with diversification in others (Coleoptera, Hymenoptera, Orthoptera). Thus, we support the overall importance of herbivory for insect diversification, but also show that its impacts can vary across scales and clades. In summary, our results illuminate the causes of species richness patterns in a group containing most living species, and show the importance of ecological impacts on diversification in explaining the diversity of life

An efficient parallel immersed boundary algorithm using a pseudo-compressible fluid solver

We propose an efficient algorithm for the immersed boundary method on distributed-memory architectures, with the computational complexity of a completely explicit method and excellent parallel scaling. The algorithm utilizes the pseudo-compressibility method recently proposed by Guermond and Minev [Comptes Rendus Mathematique, 348:581-585, 2010] that uses a directional splitting strategy to discretize the incompressible Navier-Stokes equations, thereby reducing the linear systems to a series of one-dimensional tridiagonal systems. We perform numerical simulations of several fluid-structure interaction problems in two and three dimensions and study the accuracy and convergence rates of the proposed algorithm. For these problems, we compare the proposed algorithm against other second-order projection-based fluid solvers. Lastly, the strong and weak scaling properties of the proposed algorithm are investigated

Learning the Probability of Activation in the Presence of Latent Spreaders

When an infection spreads in a community, an individual's probability of becoming infected depends on both her susceptibility and exposure to the contagion through contact with others. While one often has knowledge regarding an individual's susceptibility, in many cases, whether or not an individual's contacts are contagious is unknown. We study the problem of predicting if an individual will adopt a contagion in the presence of multiple modes of infection (exposure/susceptibility) and latent neighbor influence. We present a generative probabilistic model and a variational inference method to learn the parameters of our model. Through a series of experiments on synthetic data, we measure the ability of the proposed model to identify latent spreaders, and predict the risk of infection. Applied to a real dataset of 20,000 hospital patients, we demonstrate the utility of our model in predicting the onset of a healthcare associated infection using patient room-sharing and nurse-sharing networks. Our model outperforms existing benchmarks and provides actionable insights for the design and implementation of targeted interventions to curb the spread of infection.Comment: To appear in AAA1-1

Modular vector fields attached to Dwork family: sl2(C)\mathfrak{sl}_2(\mathbb{C}) Lie algebra

We introduce an algebraic group $\sf G$ that acts from right on the moduli space $\textsf{T}$ of Calabi-Yau $n$-folds arising from Dwork family enhanced with differential forms, and describe its Lie algebra ${\rm Lie}({\sf G})$. We observe that ${\rm Lie}({\sf G})$ together with a modular vector field ${\sf R}$ on $\textsf{T}$ generates another Lie algebra $\mathfrak{G}$, called AMSY-Lie algebra, such that $\dim \mathfrak{G}=\dim {\sf T}$. We find $\mathfrak{sl}_2(\mathbb{C})$ as a Lie subalgebra of $\mathfrak{G}$ that contains $\sf R$.Comment: 20 page

Time Explains Regional Richness Patterns within Clades More Often than Diversification Rates or Area

Most groups of organisms occur in multiple regions and have different numbers of species in different regions. These richness patterns are directly explained by speciation, extinction, and dispersal. Thus, regional richness patterns may be explained by differences in when regions were colonized (more time for speciation in regions colonized earlier), differences in how often they were colonized, or differences in diversification rates (speciation minus extinction) among regions (with diversification rates potentially influenced by area, climate, and/or many other variables). Few studies have tested all three factors, and most that did examined them only in individual clades. Here, we analyze a diverse set of 15 clades of plants and animals to test the causes of regional species richness patterns within clades. We find that time was the sole variable significantly explaining richness patterns in the best-fitting models for most clades (10/15), whereas time combined with other factors explained richness in all others. Time was the most important factor explaining richness in 13 of 15 clades, and it explained 72% of the variance in species richness among regions across all 15 clades (on average). Surprisingly, time was increasingly important in older and larger clades. In contrast, the area of the regions was relatively unimportant for explaining these regional richness patterns. A systematic review yielded 15 other relevant studies, which also overwhelmingly supported time over diversification rates (13 to 1, with one study supporting both diversification rates and time). Overall, our results suggest that colonization time is a major factor explaining regional-scale richness patterns within clades (e.g., families).National Natural Science Foundation of China [31670422, 31770402, 31770443]; Qinlan Project of Nanjing Normal University; Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) of Jiangsu Higher Education Institutions; US National Science Foundation [DEB 1655690]12 month embargo; Published online: 20 February 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Proofs of some Propositions of the semi-Intuitionistic Logic with Strong Negation

We offer the proofs that complete our article introducing the propositional calculus called semi-intuitionistic logic with strong negation.Comment: Contains proofs omitted, because of their extention, from an article published in Studia Logic

APPLICATION OF AN AVIAN BIOENERGETICS SIMULATION MODEL TO RED-WINGED BLACKBIRD - CROP RELATIONS

The impact of bird populations upon the properties or processes of ecosystems is mediated through patterns and magnitudes of energy flow. This impact may be either direct, by processing of large quantities of energy or nutrients, or indirect, through feedback control of other ecosystem rate processes or components. In either case, however, the impact is a result of the population dynamics and the pattern and magnitude of food consumption of the birds. Recent research by several groups points to a relatively small direct impact on birds on most natural ecosystems (Wiens 1973). Impact through feedback control, a more difficult relationship to study, is just beginning to receive close attention in a total systems framework. In managed ecosystems, however, where our interest is in either the bird population or its prey as an aesthetic or economic resource, the direct impacts are of considerable importance. These direct impacts are a reflection of prey consumption, which in turn is a result of the interactions of prey selection and energy demand. There is little field information available on either of these components for most bird populations, however, and we have therefore employed simulation modelling, coupled with existing information on dietary composition, to generate estimates of prey consumption rates and thus of potential impact. Our modelling tactic has been to stress generality and biological realism at the expense of precision (Levins 1966), since we are interested in models which are both robust and broadly applicable. Also, we recognize that the data base of the model is frequently imprecise, and it seems intuitively illogical to build extremely precise models for imprecise data inputs, even though this if often done

Phylogenetic analyses reveal unexpected patterns in the evolution of reproductive modes in frogs

Understanding phenotypic diversity requires not only identification of selective factors that favor origins of derived states, but also factors that favor retention of primitive states. Anurans (frogs and toads) exhibit a remarkable diversity of reproductive modes that is unique among terrestrial vertebrates. Here, we analyze the evolution of these modes, using comparative methods on a phylogeny and matched life-history database of 720 species, including most families and modes. As expected, modes with terrestrial eggs and aquatic larvae often precede direct development (terrestrial egg, no tadpole stage), but surprisingly, direct development evolves directly from aquatic breeding nearly as often. Modes with primitive exotrophic larvae (feeding outside the egg) frequently give rise to direct developers, whereas those with nonfeeding larvae (endotrophic) do not. Similarly, modes with eggs and larvae placed in locations protected from aquatic predators evolve frequently but rarely give rise to direct developers. Thus, frogs frequently bypass many seemingly intermediate stages in the evolution of direct development. We also find significant associations between terrestrial reproduction and reduced clutch size, larger egg size, reduced adult size, parental care, and occurrence in wetter and warmer regions. These associations may help explain the widespread retention of aquatic eggs and larvae, and the overall diversity of anuran reproductive modes. © 2012 The Society for the Study of Evolution.Peer Reviewe