392 research outputs found

    Superanalogs of the Calogero operators and Jack polynomials

    Full text link
    A depending on a complex parameter kk superanalog SL{\mathcal S}{\mathcal L} of Calogero operator is constructed; it is related with the root system of the Lie superalgebra gl(nm){\mathfrak{gl}}(n|m). For m=0m=0 we obtain the usual Calogero operator; for m=1m=1 we obtain, up to a change of indeterminates and parameter kk the operator constructed by Veselov, Chalykh and Feigin [2,3]. For k=1,12k=1, \frac12 the operator SL{\mathcal S}{\mathcal L} is the radial part of the 2nd order Laplace operator for the symmetric superspaces corresponding to pairs (GL(V)×GL(V),GL(V))(GL(V)\times GL(V), GL(V)) and (GL(V),OSp(V))(GL(V), OSp(V)), respectively. We will show that for the generic mm and nn the superanalogs of the Jack polynomials constructed by Kerov, Okunkov and Olshanskii [5] are eigenfunctions of SL{\mathcal S}{\mathcal L}; for k=1,12k=1, \frac12 they coinside with the spherical functions corresponding to the above mentioned symmetric superspaces. We also study the inner product induced by Berezin's integral on these superspaces

    Interrelationships Within the Bacterial Flora of the Female Genital Tract

    Get PDF
    Analysis of 240 consecutive vaginal swabs using the compatibility profile technique revealed that only 2 bacteria have the ability to be a sole isolate and as such a candidate to be a major aerobic regulator of the bacterial flora of the female genital tract (BFFGT). Compatibility profiles of Lactobacillus and Gardnerella vaginalis have shown that these organisms shared compatibility profiling for the majority of the normal bacterial constituents of the female genital tract. Dominance disruption appears to come from the addition of compatible co-isolates and presumed loss of numerical superiority. These phenomena appear to be the keys to reregulation of BFFGT. Lactobacillus appears to be the major regulator of both G. vaginalis and anaerobic bacteria. When additional organisms are added to the bacterial flora, they may add to or partially negate the inhibitory influence of Lactobacillus on the BFFGT. Inhibitor interrelationships appear to exist between coagulase-negative staphylococci and Staphylococcus aureus and the group B streptococci (GBS) and other beta hemolytic streptococci. Facilitating interrelationships appear to exist between S. aureus and the GBS and selected Enterobacteriaceae

    Integrating snow science and wildlife ecology in Arctic-boreal North America

    Get PDF
    Snow covers Arctic and boreal regions (ABRs) for approximately 9 months of the year, thus snowscapes dominate the form and function of tundra and boreal ecosystems. In recent decades, Arctic warming has changed the snowcover\u27s spatial extent and distribution, as well as its seasonal timing and duration, while also altering the physical characteristics of the snowpack. Understanding the little studied effects of changing snowscapes on its wildlife communities is critical. The goal of this paper is to demonstrate the urgent need for, and suggest an approach for developing, an improved suite of temporally evolving, spatially distributed snow products to help understand how dynamics in snowscape properties impact wildlife, with a specific focus on Alaska and northwestern Canada. Via consideration of existing knowledge of wildlife-snow interactions, currently available snow products for focus region, and results of three case studies, we conclude that improving snow science in the ABR will be best achieved by focusing efforts on developing data-model fusion approaches to produce fit-for-purpose snow products that include, but are not limited to, wildlife ecology. The relative wealth of coordinated in situ measurements, airborne and satellite remote sensing data, and modeling tools being collected and developed as part of NASA\u27s Arctic Boreal Vulnerability Experiment and SnowEx campaigns, for example, provide a data rich environment for developing and testing new remote sensing algorithms and retrievals of snowscape properties

    Linking ecosystem services, urban form and green space configuration using multivariate landscape metric analysis

    Get PDF
    Context: Landscape metrics represent powerful tools for quantifying landscape structure, but uncertainties persist around their interpretation. Urban settings add unique considerations, containing habitat structures driven by the surrounding built-up environment. Understanding urban ecosystems, however, should focus on the habitats rather than the matrix. Objectives: We coupled a multivariate approach with landscape metric analysis to overcome existing shortcomings in interpretation. We then explored relationships between landscape characteristics and modelled ecosystem service provision. Methods: We used principal component analysis and cluster analysis to isolate the most effective measures of landscape variability and then grouped habitat patches according to their attributes, independent of the surrounding urban form. We compared results to the modelled provision of three ecosystem services. Seven classes resulting from cluster analysis were separated primarily on patch area, and secondarily by measures of shape complexity and inter-patch distance. Results: When compared to modelled ecosystem services, larger patches up to 10 ha in size consistently stored more carbon per area and supported more pollinators, while exhibiting a greater risk of soil erosion. Smaller, isolated patches showed the opposite, and patches larger than 10 ha exhibited no additional areal benefit. Conclusions: Multivariate landscape metric analysis offers greater confidence and consistency than analysing landscape metrics individually. Independent classification avoids the influence of the urban matrix surrounding habitats of interest, and allows patches to be grouped according to their own attributes. Such a grouping is useful as it may correlate more strongly with the characteristics of landscape structure that directly affect ecosystem function

    Effects of body size on estimation of mammalian area requirements.

    Get PDF
    Accurately quantifying species' area requirements is a prerequisite for effective area-based conservation. This typically involves collecting tracking data on species of interest and then conducting home range analyses. Problematically, autocorrelation in tracking data can result in space needs being severely underestimated. Based on the previous work, we hypothesized the magnitude of underestimation varies with body mass, a relationship that could have serious conservation implications. To evaluate this hypothesis for terrestrial mammals, we estimated home-range areas with global positioning system (GPS) locations from 757 individuals across 61 globally distributed mammalian species with body masses ranging from 0.4 to 4000 kg. We then applied blockcross validation to quantify bias in empirical home range estimates. Area requirements of mammals 1, meaning the scaling of the relationship changedsubstantially at the upper end of the mass spectrum

    SNAPSHOT USA 2019: a coordinated national camera trap survey of the United States

    Get PDF
    With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14-week period (17 August-24 November of 2019). We sampled wildlife at 1,509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian's eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the United States. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban-wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot-usa, as will future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species-specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication

    Urban Biodiversity and Landscape Ecology: Patterns, Processes and Planning

    Get PDF
    Effective planning for biodiversity in cities and towns is increasingly important as urban areas and their human populations grow, both to achieve conservation goals and because ecological communities support services on which humans depend. Landscape ecology provides important frameworks for understanding and conserving urban biodiversity both within cities and considering whole cities in their regional context, and has played an important role in the development of a substantial and expanding body of knowledge about urban landscapes and communities. Characteristics of the whole city including size, overall amount of green space, age and regional context are important considerations for understanding and planning for biotic assemblages at the scale of entire cities, but have received relatively little research attention. Studies of biodiversity within cities are more abundant and show that longstanding principles regarding how patch size, configuration and composition influence biodiversity apply to urban areas as they do in other habitats. However, the fine spatial scales at which urban areas are fragmented and the altered temporal dynamics compared to non-urban areas indicate a need to apply hierarchical multi-scalar landscape ecology models to urban environments. Transferring results from landscape-scale urban biodiversity research into planning remains challenging, not least because of the requirements for urban green space to provide multiple functions. An increasing array of tools is available to meet this challenge and increasingly requires ecologists to work with planners to address biodiversity challenges. Biodiversity conservation and enhancement is just one strand in urban planning, but is increasingly important in a rapidly urbanising world

    A comprehensive analysis of autocorrelation and bias in home range estimation

    Get PDF
    Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated-Gaussian reference function [AKDE], Silverman´s rule of thumb, and least squares cross-validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half-sample cross-validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ((Formula presented.)) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID-based estimates by a mean factor of 2. The median number of cross-validated locations included in the hold-out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing (Formula presented.). To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal´s movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small (Formula presented.). While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an (Formula presented.) >1,000, where 30% had an (Formula presented.) <30. In this frequently encountered scenario of small (Formula presented.), AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.Fil: Noonan, Michael J.. National Zoological Park; Estados Unidos. University of Maryland; Estados UnidosFil: Tucker, Marlee A.. Senckenberg Gesellschaft Für Naturforschung; . Goethe Universitat Frankfurt; AlemaniaFil: Fleming, Christen H.. University of Maryland; Estados Unidos. National Zoological Park; Estados UnidosFil: Akre, Thomas S.. National Zoological Park; Estados UnidosFil: Alberts, Susan C.. University of Duke; Estados UnidosFil: Ali, Abdullahi H.. Hirola Conservation Programme. Garissa; KeniaFil: Altmann, Jeanne. University of Princeton; Estados UnidosFil: Antunes, Pamela Castro. Universidade Federal do Mato Grosso do Sul; BrasilFil: Belant, Jerrold L.. State University of New York; Estados UnidosFil: Beyer, Dean. Universitat Phillips; AlemaniaFil: Blaum, Niels. Universitat Potsdam; AlemaniaFil: Böhning Gaese, Katrin. Senckenberg Gesellschaft Für Naturforschung; Alemania. Goethe Universitat Frankfurt; AlemaniaFil: Cullen Jr., Laury. Instituto de Pesquisas Ecológicas; BrasilFil: de Paula, Rogerio Cunha. National Research Center For Carnivores Conservation; BrasilFil: Dekker, Jasja. Jasja Dekker Dierecologie; Países BajosFil: Drescher Lehman, Jonathan. George Mason University; Estados Unidos. National Zoological Park; Estados UnidosFil: Farwig, Nina. Michigan State University; Estados UnidosFil: Fichtel, Claudia. German Primate Center; AlemaniaFil: Fischer, Christina. Universitat Technical Zu Munich; AlemaniaFil: Ford, Adam T.. University of British Columbia; CanadáFil: Goheen, Jacob R.. University of Wyoming; Estados UnidosFil: Janssen, René. Bionet Natuuronderzoek; Países BajosFil: Jeltsch, Florian. Universitat Potsdam; AlemaniaFil: Kauffman, Matthew. University Of Wyoming; Estados UnidosFil: Kappeler, Peter M.. German Primate Center; AlemaniaFil: Koch, Flávia. German Primate Center; AlemaniaFil: LaPoint, Scott. Max Planck Institute für Ornithologie; Alemania. Columbia University; Estados UnidosFil: Markham, A. Catherine. Stony Brook University; Estados UnidosFil: Medici, Emilia Patricia. Instituto de Pesquisas Ecológicas (IPE) ; BrasilFil: Morato, Ronaldo G.. Institute For Conservation of The Neotropical Carnivores; Brasil. National Research Center For Carnivores Conservation; BrasilFil: Nathan, Ran. The Hebrew University of Jerusalem; IsraelFil: Oliveira Santos, Luiz Gustavo R.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Olson, Kirk A.. Wildlife Conservation Society; Estados Unidos. National Zoological Park; Estados UnidosFil: Patterson, Bruce. Field Museum of National History; Estados UnidosFil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; ArgentinaFil: Ramalho, Emiliano Esterci. Institute For Conservation of The Neotropical Carnivores; Brasil. Instituto de Desenvolvimento Sustentavel Mamirauá; BrasilFil: Rösner, Sascha. Michigan State University; Estados UnidosFil: Schabo, Dana G.. Michigan State University; Estados UnidosFil: Selva, Nuria. Institute of Nature Conservation of The Polish Academy of Sciences; PoloniaFil: Sergiel, Agnieszka. Institute of Nature Conservation of The Polish Academy of Sciences; PoloniaFil: Xavier da Silva, Marina. Parque Nacional do Iguaçu; BrasilFil: Spiegel, Orr. Universitat Tel Aviv; IsraelFil: Thompson, Peter. University of Maryland; Estados UnidosFil: Ullmann, Wiebke. Universitat Potsdam; AlemaniaFil: Ziḝba, Filip. Tatra National Park; PoloniaFil: Zwijacz Kozica, Tomasz. Tatra National Park; PoloniaFil: Fagan, William F.. University of Maryland; Estados UnidosFil: Mueller, Thomas. Senckenberg Gesellschaft Für Naturforschung; . Goethe Universitat Frankfurt; AlemaniaFil: Calabrese, Justin M.. National Zoological Park; Estados Unidos. University of Maryland; Estados Unido

    Search for neutral charmless B decays at LEP

    Get PDF
    A search for rare charmless decays of \Bd and \Bs mesons has been performed in the exclusive channels \Bd_{(\mathrm s)}\ra\eta\eta, \Bd_{(\mathrm s)}\ra\eta\pio and \Bd_{(\mathrm s)}\ra\pio\pio. The data sample consisted of three million hadronic \Zo decays collected by the L3 experiment at LEP from 1991 through 1994. No candidate event has been observed and the following upper limits at 90\% confidence level on the branching ratios have been set \begin{displaymath} \mathrm{Br}(\Bd\ra\eta\eta)<4.1\times 10^{-4},\,\, \mathrm{Br}(\Bs\ra\eta\eta)<1.5\times 10^{-3},\,\, \end{displaymath} \begin{displaymath} \mathrm{Br}(\Bd\ra\eta\pio)<2.5\times 10^{-4},\,\, \mathrm{Br}(\Bs\ra\eta\pio)<1.0\times 10^{-3},\,\, \end{displaymath} \begin{displaymath} \mathrm{Br}(\Bd\ra\pio\pio)<6.0\times 10^{-5},\,\, \mathrm{Br}(\Bs\ra\pio\pio)<2.1\times 10^{-4}. \end{displaymath} These are the first experimental limits on \Bd\ra\eta\eta and on the \Bs neutral charmless modes

    Heavy Quarkonium Production in Z Decays

    Get PDF
    We report measurements of the inclusive production of heavy quarkonium states in Z\mathrm {Z} decays based on the analysis of 3.6 million hadronic events collected by the L3 detector at LEP. The measurement of inclusive J production and an improved 95%95\% confidence level upper limit on Υ\Upsilon production are presented. In addition, two independent measurements of the ratio, fpf_{\mathrm{p}}, of prompt J mesons to those from B decay are made using two different isolation cuts to separate prompt J mesons from J mesons produced in the decays of b hadrons. The results are: % \begin{eqnarray} \mathrm{Br}(\mathrm{Z} \rightarrow \mathrm{J} + \mathrm{X}) & = & (3.21 \pm 0.21 \; \mathrm{(stat.)} \; ^{+ 0.19}_{- 0.28} \; \mathrm{(sys.)} ) \times 10^{-3} \; , \nonumber \\ \mathrm{Br}(\mathrm {Z} \rightarrow \Upsilon(\mathrm{1S} + X) & < & 4.4 \times 10^{-5} \; , \nonumber \\ %% f_{\mathrm{p}} & = & (7.1 \pm 2.1 \; \mathrm{(stat.)} \; \pm 1.2 \; \mathrm{(sys.)} \; ^{+1.5}_{-0.8} \;\mathrm{(theo.)} ) \times 10^{-2} \; . \nonumbe
    corecore