Establishment of a Prairie on a Borrow-Pit Site at the Bergamo-Mt. St. John Nature Preserve in Greene County, Ohio

Author Institution: Department of Biological Sciences, University of Cincinnati and Department of Biology, University of DaytonDuring the spring of 1986, development of a prairie was begun on a site at the Bergamo-Mt. St. John Nature Preserve located in Greene County, Ohio. A major objective of the project was to reclaim a sand and gravel borrow-pit. Prairie was chosen for reclamation of this area because prairie vegetation was present in the immediate area and that type of community is well-suited to the extremes in moisture conditions on the site. The prairie is intended to provide a habitat for some species being displaced by human disturbance and to provide a specific plant community within the preserve. To establish grasses, seeds obtained from Western sources were planted in April of 1986 by hydroseeding on the graded site. Just prior to this, seeds of several forbs obtained from Western sources were broadcast over the area. Subsequently, seeds of grasses and forbs collected locally were broadcast. For species more difficult to establish, plants were propagated in soil-filled plastic-film cylinders. These, and other plants collected locally from disturbed sites, were transplanted into holes prepared with a soil auger. After three seasons of growth, approximately 36 species of Ohio prairie indicator plant species, along with a number of species of animals, have become established on the site despite the severe drought of 1988

Geometric and dynamic perspectives on phase-coherent and noncoherent chaos

Statistically distinguishing between phase-coherent and noncoherent chaotic dynamics from time series is a contemporary problem in nonlinear sciences. In this work, we propose different measures based on recurrence properties of recorded trajectories, which characterize the underlying systems from both geometric and dynamic viewpoints. The potentials of the individual measures for discriminating phase-coherent and noncoherent chaotic oscillations are discussed. A detailed numerical analysis is performed for the chaotic R\"ossler system, which displays both types of chaos as one control parameter is varied, and the Mackey-Glass system as an example of a time-delay system with noncoherent chaos. Our results demonstrate that especially geometric measures from recurrence network analysis are well suited for tracing transitions between spiral- and screw-type chaos, a common route from phase-coherent to noncoherent chaos also found in other nonlinear oscillators. A detailed explanation of the observed behavior in terms of attractor geometry is given.Comment: 12 pages, 13 figure

Partisan Asymmetries in Online Political Activity

We examine partisan differences in the behavior, communication patterns and social interactions of more than 18,000 politically-active Twitter users to produce evidence that points to changing levels of partisan engagement with the American online political landscape. Analysis of a network defined by the communication activity of these users in proximity to the 2010 midterm congressional elections reveals a highly segregated, well clustered partisan community structure. Using cluster membership as a high-fidelity (87% accuracy) proxy for political affiliation, we characterize a wide range of differences in the behavior, communication and social connectivity of left- and right-leaning Twitter users. We find that in contrast to the online political dynamics of the 2008 campaign, right-leaning Twitter users exhibit greater levels of political activity, a more tightly interconnected social structure, and a communication network topology that facilitates the rapid and broad dissemination of political information.Comment: 17 pages, 10 figures, 6 table

Inference with interference between units in an fMRI experiment of motor inhibition

An experimental unit is an opportunity to randomly apply or withhold a treatment. There is interference between units if the application of the treatment to one unit may also affect other units. In cognitive neuroscience, a common form of experiment presents a sequence of stimuli or requests for cognitive activity at random to each experimental subject and measures biological aspects of brain activity that follow these requests. Each subject is then many experimental units, and interference between units within an experimental subject is likely, in part because the stimuli follow one another quickly and in part because human subjects learn or become experienced or primed or bored as the experiment proceeds. We use a recent fMRI experiment concerned with the inhibition of motor activity to illustrate and further develop recently proposed methodology for inference in the presence of interference. A simulation evaluates the power of competing procedures.Comment: Published by Journal of the American Statistical Association at http://www.tandfonline.com/doi/full/10.1080/01621459.2012.655954 . R package cin (Causal Inference for Neuroscience) implementing the proposed method is freely available on CRAN at https://CRAN.R-project.org/package=ci

Novel statistical approaches for non-normal censored immunological data: analysis of cytokine and gene expression data

Background: For several immune-mediated diseases, immunological analysis will become more complex in the future with datasets in which cytokine and gene expression data play a major role. These data have certain characteristics that require sophisticated statistical analysis such as strategies for non-normal distribution and censoring. Additionally, complex and multiple immunological relationships need to be adjusted for potential confounding and interaction effects. Objective: We aimed to introduce and apply different methods for statistical analysis of non-normal censored cytokine and gene expression data. Furthermore, we assessed the performance and accuracy of a novel regression approach in order to allow adjusting for covariates and potential confounding. Methods: For non-normally distributed censored data traditional means such as the Kaplan-Meier method or the generalized Wilcoxon test are described. In order to adjust for covariates the novel approach named Tobit regression on ranks was introduced. Its performance and accuracy for analysis of non-normal censored cytokine/gene expression data was evaluated by a simulation study and a statistical experiment applying permutation and bootstrapping. Results: If adjustment for covariates is not necessary traditional statistical methods are adequate for non-normal censored data. Comparable with these and appropriate if additional adjustment is required, Tobit regression on ranks is a valid method. Its power, type-I error rate and accuracy were comparable to the classical Tobit regression. Conclusion: Non-normally distributed censored immunological data require appropriate statistical methods. Tobit regression on ranks meets these requirements and can be used for adjustment for covariates and potential confounding in large and complex immunological datasets

Spin measurements for 147Sm+n resonances: Further evidence for non-statistical effects

We have determined the spins J of resonances in the 147Sm(n,gamma) reaction by measuring multiplicities of gamma-ray cascades following neutron capture. Using this technique, we were able to determine J values for all but 14 of the 140 known resonances below En = 1 keV, including 41 firm J assignments for resonances whose spins previously were either unknown or tentative. These new spin assignments, together with previously determined resonance parameters, allowed us to extract separate level spacings and neutron strength functions for J = 3 and 4 resonances. Furthermore, several statistical test of the data indicate that very few resonances of either spin have been missed below En = 700eV. Because a non-statistical effect recently was reported near En = 350 eV from an analysis of 147Sm(n,alpha) data, we divided the data into two regions; 0 < En < 350 eV and 350 < En < 700 eV. Using neutron widths from a previous measurement and published techniques for correcting for missed resonances and for testing whether data are consistent with a Porter-Thomas distribution, we found that the reduced-neutron-width distribution for resonances below 350 eV is consistent with the expected Porter-Thomas distribution. On the other hand, we found that reduced-neutron-width data in the 350 < En < 700 eV region are inconsistent with a Porter-Thomas distribution, but in good agreement with a chi-squared distribution having two or more degrees of freedom. We discuss possible explanations for these observed non-statistical effects and their possible relation to similar effects previously observed in other nuclides.Comment: 40 pages, 13 figures, accepted by Phys. Rev.

Twitter-based analysis of the dynamics of collective attention to political parties

Large-scale data from social media have a significant potential to describe complex phenomena in real world and to anticipate collective behaviors such as information spreading and social trends. One specific case of study is represented by the collective attention to the action of political parties. Not surprisingly, researchers and stakeholders tried to correlate parties' presence on social media with their performances in elections. Despite the many efforts, results are still inconclusive since this kind of data is often very noisy and significant signals could be covered by (largely unknown) statistical fluctuations. In this paper we consider the number of tweets (tweet volume) of a party as a proxy of collective attention to the party, identify the dynamics of the volume, and show that this quantity has some information on the elections outcome. We find that the distribution of the tweet volume for each party follows a log-normal distribution with a positive autocorrelation of the volume over short terms, which indicates the volume has large fluctuations of the log-normal distribution yet with a short-term tendency. Furthermore, by measuring the ratio of two consecutive daily tweet volumes, we find that the evolution of the daily volume of a party can be described by means of a geometric Brownian motion (i.e., the logarithm of the volume moves randomly with a trend). Finally, we determine the optimal period of averaging tweet volume for reducing fluctuations and extracting short-term tendencies. We conclude that the tweet volume is a good indicator of parties' success in the elections when considered over an optimal time window. Our study identifies the statistical nature of collective attention to political issues and sheds light on how to model the dynamics of collective attention in social media.Comment: 16 pages, 7 figures, 3 tables. Published in PLoS ON

USING CONDITIONED TASTE AVERSIONS TO PROTECT BLUEBERRIES FROM BIRDS: COMPARISON OF TWO CARBAMATE REPELLENTS

This study compared the effectiveness of two carbamate repellents, trimethacarb and methiocarb, in preventing bird damage to blueberry fields by establishing in birds a conditioned taste aversion to treated berries. These experiments were conducted during 1982 and 1983 at the Lockwood Farm in Hamden, Connecticut, where these repellents were tested on a 0.05 ha blueberry planting and at Rose\u27s Berry Farm in Glastonbury, Connecticut, where five 0.4-1.0 ha fields were used. To test the efficacy of these repellents, the plot at the Station\u27s farm was divided in half; and the plots at Rose\u27s Berry Farm were divided into thirds. Bird damage in each of these sections was first measured during a one-week pre-treatment period. Thereafter, one of the sections in each field was randomly selected and treated with one of the repellents. Two weeks later, another section in each field was sprayed with the other repellent. Bird damage in the treated sections and in the nearby untreated sections was compared to that occurring in these same sections during the pre·treatment period, using a Student\u27s t·test for statistically significant (P \u3c 0.05) differences. My results indicated that methiocarb and trimethacarb significantly reduced berry loss in the treated plots by 25% and 52%, respectively, during the first week after application. The difference in repellent effectiveness, however, was not statistically significant. Moreover, neither repellent significantly reduced berry loss in adjacent untreated plots. These results indicate that both repellents caused birds to avert only from treated berries and not from the taste or sight of blueberries themselves