Phylogenetic Relationships among Chinese Rice Frogs within the Fejervarya limnocharis Species Complex (Amphibia: Dicroglossidae)

We present a molecular assessment of the widely-distributed rice frog (Fejervar ya limnocharis) which provides many new samples tha t add to knowledge of their phylogeography within China and considers genetic support for five Chinese species within this complex. Two mtDNA fragments from 270 individuals and eight nuclear DNA loci (105 individuals) were sequenced from specimens sampled from across China. Data from nine specimens from China, Indonesia and Japan were also retrieved from previous studies. MtDNA was informative a bout population divergence within China and indicated one major clade (with four subclades) from South China and the Zhoushan Archipelago, Zhejiang, China, and a second major clade (with eight subclades) from other parts of China. Recent demographic expansions (less than 50ka ago) were detected within three of these 12 subclades, potentially associated with lowered sea-levels after marine transgressions. Notably, most frogs from the previously unstudied Zhoushan Archipelago (eastern China) were found to be closely related to Japanese populations. BPP and STACEY species delimitation analyses of the multilocus data favoured five candidate species within the complex. Previous work had described Fe jervar ya multistriata and F. kawamurai from the Chinese mainland although here we detected considerable genetic divergence within the latter and found that this may be indicative of two species. One of these corresponds to the Zhoushan Archipelago, Zhejiang, China and Japan, and the other from most parts of Chinese mainland. This study provides a large multilocus dataset that contributes to the systematics of this species complex

A Survey on the Krein-von Neumann Extension, the corresponding Abstract Buckling Problem, and Weyl-Type Spectral Asymptotics for Perturbed Krein Laplacians in Nonsmooth Domains

In the first (and abstract) part of this survey we prove the unitary equivalence of the inverse of the Krein--von Neumann extension (on the orthogonal complement of its kernel) of a densely defined, closed, strictly positive operator, $S\geq \varepsilon I_{\mathcal{H}}$ for some $\varepsilon >0$ in a Hilbert space $\mathcal{H}$ to an abstract buckling problem operator. This establishes the Krein extension as a natural object in elasticity theory (in analogy to the Friedrichs extension, which found natural applications in quantum mechanics, elasticity, etc.). In the second, and principal part of this survey, we study spectral properties for $H_{K,\Omega}$, the Krein--von Neumann extension of the perturbed Laplacian $-\Delta+V$ (in short, the perturbed Krein Laplacian) defined on $C^\infty_0(\Omega)$, where $V$ is measurable, bounded and nonnegative, in a bounded open set $\Omega\subset\mathbb{R}^n$ belonging to a class of nonsmooth domains which contains all convex domains, along with all domains of class $C^{1,r}$, $r>1/2$.Comment: 68 pages. arXiv admin note: extreme text overlap with arXiv:0907.144

The genomes of two key bumblebee species with primitive eusocial organization

Background: The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results: We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions: These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation

Search for rare quark-annihilation decays, B --> Ds(*) Phi

We report on searches for B- --> Ds- Phi and B- --> Ds*- Phi. In the context of the Standard Model, these decays are expected to be highly suppressed since they proceed through annihilation of the b and u-bar quarks in the B- meson. Our results are based on 234 million Upsilon(4S) --> B Bbar decays collected with the BABAR detector at SLAC. We find no evidence for these decays, and we set Bayesian 90% confidence level upper limits on the branching fractions BF(B- --> Ds- Phi) Ds*- Phi)<1.2x10^(-5). These results are consistent with Standard Model expectations.Comment: 8 pages, 3 postscript figues, submitted to Phys. Rev. D (Rapid Communications

Search for Gravitational Waves from Primordial Black Hole Binary Coalescences in the Galactic Halo

We use data from the second science run of the LIGO gravitational-wave detectors to search for the gravitational waves from primordial black hole (PBH) binary coalescence with component masses in the range 0.2--$1.0 M_\odot$. The analysis requires a signal to be found in the data from both LIGO observatories, according to a set of coincidence criteria. No inspiral signals were found. Assuming a spherical halo with core radius 5 kpc extending to 50 kpc containing non-spinning black holes with masses in the range 0.2--$1.0 M_\odot$, we place an observational upper limit on the rate of PBH coalescence of 63 per year per Milky Way halo (MWH) with 90% confidence.Comment: 7 pages, 4 figures, to be submitted to Phys. Rev.

Bayesian inversion of synthetic AVO data to assess fluid and shale content in sand-shale media

Reservoir characterization of sand-shale sequences has always challenged geoscientists due to the presence of anisotropy in the form of shale lenses or shale layers. Water saturation and volume of shale are among the fundamental reservoir properties of interest for sand-shale intervals, and relate to the amount of fluid content and accumulating potentials of such media. This paper suggests an integrated workflow using synthetic data for the characterization of shaley-sand media based on anisotropic rock physics (T-matrix approximation) and seismic reflectivity modelling. A Bayesian inversion scheme for estimating reservoir parameters from amplitude vs. offset (AVO) data was used to obtain the information about uncertainties as well as their most likely values. The results from our workflow give reliable estimates of water saturation from AVO data at small uncertainties, provided background sand porosity values and isotropic overburden properties are known. For volume of shale, the proposed workflow provides reasonable estimates even when larger uncertainties are present in AVO data

Integrated methodological framework fos assesing the risk of failure in water supply incorporating drought forecast. Case study: Andean regulated river basin

[EN] Hydroclimatic drought conditions can affect the hydrological services offered by mountain river basins causing severe impacts on the population, becoming a challenge for water resource managers in Andean river basins. This study proposes an integrated methodological framework for assessing the risk of failure in water supply, incorporating probabilistic drought forecasts, which assists in making decisions regarding the satisfaction of consumptive, non-consumptive and environmental requirements under water scarcity conditions. Monte Carlo simulation was used to assess the risk of failure in multiple stochastic scenarios, which incorporate probabilistic forecasts of drought events based on a Markov chains (MC) model using a recently developed drought index (DI). This methodology was tested in the Machángara river basin located in the south of Ecuador. Results were grouped in integrated satisfaction indexes of the system (DSIG). They demonstrated that the incorporation of probabilistic drought forecasts could better target the projections of simulation scenarios, with a view of obtaining realistic situations instead of optimistic projections that would lead to riskier decisions. Moreover, they contribute to more effective results in order to propose multiple alternatives for prevention and/or mitigation under drought conditions.This study was part of the doctoral thesis of Aviles A. at the Technical University of Valencia. This research was funded by the University of Cuenca through its Research Department (DIUC) and the Municipal public enterprise of telecommunications, drinking water, sewage and sanitation of Cuenca (ETAPA) through the projects: BIdentificacion de los procesos hidrometeorologicos que desencadenan inundaciones en la ciudad de Cuenca usando un radar de precipitacion" and "Ciclos meteorologicos y evapotranspiracion a lo largo de una gradiente altitudinal del Parque Nacional Cajas". The authors also thank INAMHI and the CBRM for providing the information for this study. The authors wish to thank the Spanish Ministry of Economy and Competitiveness for its financial support through the ERAS project (CTM2016-77804-P). We thank Angel Vazquez, who helped in the programming of the multiple simulations. Also we thank to the TropiSeca project.Avilés-Añazco, A.; Solera Solera, A.; Paredes Arquiola, J.; Pedro Monzonís, M. (2018). Integrated methodological framework fos assesing the risk of failure in water supply incorporating drought forecast. Case study: Andean regulated river basin. Water Resources Management. 32(4):1209-1223. https://doi.org/10.1007/s11269-017-1863-7S12091223324Andreu J, Capilla J, Sanchís E (1996) AQUATOOL, a generalized decision-support system for water-resources planning and operational management. J Hydrol 177(3-4):269–291. https://doi.org/10.1016/0022-1694(95)02963-XAndreu J, Solera A, Capilla J, Ferrer J (2007) Modelo SIMGES para simulación de cuencas. Manual de usuario v3. 00. Universidad Politécnica de Valencia, ValenciaAndreu J, Ferrer J, Perez MA et al (2013) Drought planning and management in the Júcar River Basin, Spain. In: Schwabe K et al (eds) Drought in arid and semi-arid regions. Springer science, Dordrecht, pp 237–249. https://doi.org/10.1007/978-94-007-6636-5_13Avilés A, Solera A (2013) Análisis de sistemas de recursos hídricos de la cuenca del rio Tomebamba en Ecuador, mediante modelos estocásticos y de gestión. In: Solera A, Paredes J, Andreu J (eds) Aplicaciones de sistemas soporte a la decisión en planificación y gestión integradas de cuencas hidrográficas. Marcombo, Barcelona, España pp 51–61Avilés A, Célleri R, Paredes J, Solera A (2015) Evaluation of Markov chain based drought forecasts in an Andean Regulated River basin using the skill scores RPS and GMSS. Water Resour Manag 29(6):1949–1963. https://doi.org/10.1007/s11269-015-0921-2Avilés A, Célleri R, Solera A, Paredes J (2016) Probabilistic forecasting of drought events using Markov chain-and Bayesian network-based models: a case study of an Andean Regulated River Basin. Water 8:1–16Barua S, Ng A, Perera B (2012) Drought assessment and forecasting: a case study on the Yarra River catchment in Victoria, Australia. Aust J Water Resour 15(2):95–108. https://doi.org/10.7158/W10-848.2012.15.2Bazaraa MS, Jarvis JJ, Sherali HD (2011) Linear programming and network flows, fourth Edi. John Wiley & Sons, New JerseyBrown C, Baroang KM, Conrad E et al (2010) IRI technical report 10–15, managing climate risk in water supply systems. Palisades, NYCancelliere A, Di Mauro G, Bonaccorso B, Rossi G (2007) Drought forecasting using the standardized precipitation index. Water Resour Manag 21(5):801–819. https://doi.org/10.1007/s11269-006-9062-yCancelliere A, Nicolosi V, Rossi G (2009) Assessment of drought risk in water supply systems in coping with drought risk in agriculture and water supply systems. Advances in natural and technological hazards research 26. In: Coping with drought risk in agriculture. Springer, pp 93–109. https://doi.org/10.1007/978-1-4020-9045-5_8Chen YD, Zhang Q, Xiao M, Singh VP, Zhang S (2016) Probabilistic forecasting of seasonal droughts in the Pearl River basin, China. Stoch Environ Res Risk Assess 30(7):2031–2040. https://doi.org/10.1007/s00477-015-1174-6Gong G, Wang L, Condon L, Shearman A, Lall U (2010) A simple framework for incorporating seasonal Streamflow forecasts into existing water resource management practices. JAWRA J Am Water Resour Assoc 46(3):574–585. https://doi.org/10.1111/j.1752-1688.2010.00435.xHaro D, Solera A, Paredes J, Andreu J (2014) Methodology for drought risk assessment in within-year regulated reservoir systems. Application to the Orbigo River system (Spain). Water Resour Manag 28(11):3801–3814. https://doi.org/10.1007/s11269-014-0710-3Haro-Monteagudo D, Solera A, Andreu J (2017) Drought early warning based on optimal risk forecasts in regulated river systems: application to the Jucar River basin (Spain). J Hydrol 544:36–45. https://doi.org/10.1016/j.jhydrol.2016.11.022Hashimoto T, Loucks DP, Stedinger JR (1982) Reliability, resiliency, and vulnerability criteria. Water Resour Res 18(1):14–20. https://doi.org/10.1029/WR018i001p00014Hwang Y, Carbone GJ (2009) Ensemble forecasts of drought indices using a conditional residual resampling technique. J Appl Meteorol Climatol 48(7):1289–1301. https://doi.org/10.1175/2009JAMC2071.1Kao S-C, Govindaraju RS (2010) A copula-based joint deficit index for droughts. J Hydrol 380(1-2):121–134. https://doi.org/10.1016/j.jhydrol.2009.10.029Keyantash JA, Dracup JA (2004) An aggregate drought index: assessing drought severity based on fluctuations in the hydrologic cycle and surface water storage. Water Resour Res 40(9):1–13. https://doi.org/10.1029/2003WR002610Khadr M (2016) Forecasting of meteorological drought using hidden Markov model (case study: the upper Blue Nile river basin, Ethiopia). Ain Shams Eng J 7(1):47–56. https://doi.org/10.1016/j.asej.2015.11.005Madadgar S, Moradkhani H (2013) A Bayesian framework for probabilistic seasonal drought forecasting. J Hydrometeorol 14(6):1685–1706. https://doi.org/10.1175/JHM-D-13-010.1Madadgar S, Moradkhani H (2014) Spatio-temporal drought forecasting within Bayesian networks. J Hydrol 512:134–146. https://doi.org/10.1016/j.jhydrol.2014.02.039Mahmoudzadeh H, Mahmoudzadeh H, Afshar M, Yousefi S (2016) Applying first-order Markov chains and SPI drought index to monitor and forecast drought in West Azerbaijan Province of Iran. Int J Geo Sci Environ Plan 1:44–53. 10.22034/ijgsep.2016.40669Mishra AK, Singh VP (2010) Review paper a review of drought concepts. J Hydrol 391(1-2):202–216. https://doi.org/10.1016/j.jhydrol.2010.07.012Nalbantis I, Tsakiris G (2009) Assessment of hydrological drought revisited. Water Resour Manag 23(5):881–897. https://doi.org/10.1007/s11269-008-9305-1Ochola WO, Kerkides P (2003) A Markov chain simulation model for predicting critical wet and dry spells in Kenya: Analysing rainfall events in the kano plains. Irrig Drain 52(4):327–342. https://doi.org/10.1002/ird.094Paulo AA, Pereira LS (2007) Prediction of SPI drought class transitions using Markov chains. Water Resour Manag 21(10):1813–1827. https://doi.org/10.1007/s11269-006-9129-9Phan TD, Smart JCR, Capon SJ, Hadwen WL, Sahin O (2016) Applications of Bayesian belief networks in water resource management: a systematic review. Environ Model Softw 85:98–111. https://doi.org/10.1016/j.envsoft.2016.08.006Pouget L, Roldán T, Gómez M et al (2015) Use of seasonal climate predictions in the water sector—preliminary results from the EUPORIAS project. In: Andreu J, Solera A, Paredes J et al (eds) Drought: research and science-policy interfacing. Taylor & Francis Group, London, UK, p 247Rossi G, Cancelliere A (2013) Managing drought risk in water supply systems in Europe: a review. Int J Water Resour Dev 29(2):272–289. https://doi.org/10.1080/07900627.2012.713848Rossi G, Caporali E, Garrote L (2012) Definition of risk indicators for reservoirs management optimization. Water Resour Manag 26(4):981–996. https://doi.org/10.1007/s11269-011-9842-xSánchez S, Andreu J, Solera A (2001) Gestión de Recursos Hídricos con Decisiones Basadas en Estimación del Riesgo. Universidad Politécnica De Valencia, ValenciaSandoval-Solis S, McKinney DC, Loucks M (2011) Sustainability index for water resources planning and management. J Water Resour Plan Manag 137(5):381–390. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000134Sankarasubramanian A, Lall U, Devineni N, Espinueva S (2009) The role of monthly updated climate forecasts in improving intraseasonal water allocation. J Appl Meteorol Climatol 48(7):1464–1482. https://doi.org/10.1175/2009JAMC2122.1Shukla S, Wood AW (2008) Use of a standardized runoff index for characterizing hydrologic drought. Geophys Res Lett 35(2):1–7. https://doi.org/10.1029/2007GL032487Staudinger M, Stahl K, Seibert J (2014) A drought index accounting for snow. Water Resour Res 50(10):7861–7872. https://doi.org/10.1002/2013WR015143Sveinsson O, Salas JD, Lane W, Frevert D (2007) Stochastic analysis, modeling, and simulation (SAMS) version 2007, user’s manual. Computing Hydrology Laboratory, Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, ColoradoSvoboda M, Hayes M, Wilhite D, Tadesse T (2004) Recent advances in drought monitoring. Drought Mitig Cent Fac Publ 6:6Vogel RM (2017) Stochastic watershed models for hydrologic risk management. Water Secur 1:28–35. https://doi.org/10.1016/j.wasec.2017.06.001Wilks DS (2011) Statistical methods in the atmospheric sciences, third edit. Academic Press, USAWorld Meteorological Organization (2012) Standardized precipitation index user Guide (M. Svoboda, M. Hayes and D. Wood). (WMO - No. 1090), Geneva

The Role of Environmental Transmission in Recurrent Avian Influenza Epidemics

Avian influenza virus (AIV) persists in North American wild waterfowl, exhibiting major outbreaks every 2–4 years. Attempts to explain the patterns of periodicity and persistence using simple direct transmission models are unsuccessful. Motivated by empirical evidence, we examine the contribution of an overlooked AIV transmission mode: environmental transmission. It is known that infectious birds shed large concentrations of virions in the environment, where virions may persist for a long time. We thus propose that, in addition to direct fecal/oral transmission, birds may become infected by ingesting virions that have long persisted in the environment. We design a new host–pathogen model that combines within-season transmission dynamics, between-season migration and reproduction, and environmental variation. Analysis of the model yields three major results. First, environmental transmission provides a persistence mechanism within small communities where epidemics cannot be sustained by direct transmission only (i.e., communities smaller than the critical community size). Second, environmental transmission offers a parsimonious explanation of the 2–4 year periodicity of avian influenza epidemics. Third, very low levels of environmental transmission (i.e., few cases per year) are sufficient for avian influenza to persist in populations where it would otherwise vanish

How does ethical leadership trickle down? Test of an integrative dual-process model

Although the trickle-down effect of ethical leadership has been documented in the literature, its underlying mechanism still remains largely unclear. To address this gap, we develop a cross-level dual-process model to explain how the effect occurs. Drawing on social learning theory, we hypothesize that the ethical leadership of high-level managers could cascade to middle-level supervisors via its impact on middle-level supervisors’ two ethical expectations. Using a sample of 69 middle-level supervisors and 381 subordinates across 69 sub-branches from a large banking firm in China, we found that middle-level supervisors’ ethical efficacy expectation and unethical behavior–punishment expectation (as one form of ethical outcome expectations) accounted for the trickle-down effect. The explanatory role of middle-level supervisors’ ethical behavior–reward expectation (as the other form of ethical outcome expectations), however, was not supported. The theoretical and practical implications are discussed

Estimating the delay between host infection and disease (incubation period) and assessing its significance to the epidemiology of plant diseases.

Knowledge of the incubation period of infectious diseases (time between host infection and expression of disease symptoms) is crucial to our epidemiological understanding and the design of appropriate prevention and control policies. Plant diseases cause substantial damage to agricultural and arboricultural systems, but there is still very little information about how the incubation period varies within host populations. In this paper, we focus on the incubation period of soilborne plant pathogens, which are difficult to detect as they spread and infect the hosts underground and above-ground symptoms occur considerably later. We conducted experiments on Rhizoctonia solani in sugar beet, as an example patho-system, and used modelling approaches to estimate the incubation period distribution and demonstrate the impact of differing estimations on our epidemiological understanding of plant diseases. We present measurements of the incubation period obtained in field conditions, fit alternative probability models to the data, and show that the incubation period distribution changes with host age. By simulating spatially-explicit epidemiological models with different incubation-period distributions, we study the conditions for a significant time lag between epidemics of cryptic infection and the associated epidemics of symptomatic disease. We examine the sensitivity of this lag to differing distributional assumptions about the incubation period (i.e. exponential versus Gamma). We demonstrate that accurate information about the incubation period distribution of a pathosystem can be critical in assessing the true scale of pathogen invasion behind early disease symptoms in the field; likewise, it can be central to model-based prediction of epidemic risk and evaluation of disease management strategies. Our results highlight that reliance on observation of disease symptoms can cause significant delay in detection of soil-borne pathogen epidemics and mislead practitioners and epidemiologists about the timing, extent, and viability of disease control measures for limiting economic loss.ML thanks the Institut Technique français de la Betterave industrielle (ITB) for funding this project. CAG and JANF were funded by the UK’s Biotechnology and Biological Sciences Research Council (BBSRC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript