Tracking neonicotinoids following their use as cotton seed treatments

Neonicotinoids are a leading class of insecticides on the global market, accounting for nearly 25%. They are widely used in both agricultural and residential settings. Causing neuron failure by irreversibly binding to the insect nicotinic acetylcholine receptor, neonicotinoids offer broad spectrum efficacy against a variety of pests. However, because they are non-selective with regard to insect species, there has been some concern with neonicotinoid use over threats to pollinators such as honeybees, and potential indirect effects to migratory waterfowl as a result of invertebrate prey population depletion. In order to study occurrence and fate of neonicotinoids (thiamethoxam and imidacloprid), we analyzed cotton leaves on plants grown from neonicotinoid-treated seeds and corresponding soil samples between cotton rows. Neonicotinoid concentration data from cotton leaves appears to be consistent with the claim that seed treatments protect plants for 3–4 weeks; by 30 days post-planting, neonicotinoid concentrations fell, in general, to 200 ng/g or lower. This represents about a 10-fold decrease from plant concentrations at approximately 2 weeks post-planting. It was found that neonicotinoids used as seed treatments remained present in the soil for months post planting and could be available for runoff. To that end, 21 playa wetlands were sampled; 10 had at least one quantifiable neonicotinoid present, three of which were classified as grassland or rangeland playas, two were urban, and the remaining five were cropland playas. In several instances, neonicotinoid concentrations in playas exceeded EPA chronic benchmarks for aquatic invertebrates

Setting an Optimal α That Minimizes Errors in Null Hypothesis Significance Tests

Null hypothesis significance testing has been under attack in recent years, partly owing to the arbitrary nature of setting α (the decision-making threshold and probability of Type I error) at a constant value, usually 0.05. If the goal of null hypothesis testing is to present conclusions in which we have the highest possible confidence, then the only logical decision-making threshold is the value that minimizes the probability (or occasionally, cost) of making errors. Setting α to minimize the combination of Type I and Type II error at a critical effect size can easily be accomplished for traditional statistical tests by calculating the α associated with the minimum average of α and β at the critical effect size. This technique also has the flexibility to incorporate prior probabilities of null and alternate hypotheses and/or relative costs of Type I and Type II errors, if known. Using an optimal α results in stronger scientific inferences because it estimates and minimizes both Type I errors and relevant Type II errors for a test. It also results in greater transparency concerning assumptions about relevant effect size(s) and the relative costs of Type I and II errors. By contrast, the use of α = 0.05 results in arbitrary decisions about what effect sizes will likely be considered significant, if real, and results in arbitrary amounts of Type II error for meaningful potential effect sizes. We cannot identify a rationale for continuing to arbitrarily use α = 0.05 for null hypothesis significance tests in any field, when it is possible to determine an optimal α

Upper limit map of a background of gravitational waves

We searched for an anisotropic background of gravitational waves using data from the LIGO S4 science run and a method that is optimized for point sources. This is appropriate if, for example, the gravitational wave background is dominated by a small number of distinct astrophysical sources. No signal was seen. Upper limit maps were produced assuming two different power laws for the source strain power spectrum. For an f^-3 power law and using the 50 Hz to 1.8 kHz band the upper limits on the source strain power spectrum vary between 1.2e-48 Hz^-1 (100 Hz/f)^3 and 1.2e-47 Hz^-1 (100 Hz /f)^3, depending on the position in the sky. Similarly, in the case of constant strain power spectrum, the upper limits vary between 8.5e-49 Hz^-1 and 6.1e-48 Hz^-1. As a side product a limit on an isotropic background of gravitational waves was also obtained. All limits are at the 90% confidence level. Finally, as an application, we focused on the direction of Sco-X1, the closest low-mass X-ray binary. We compare the upper limit on strain amplitude obtained by this method to expectations based on the X-ray luminosity of Sco-X1.Comment: 11 pages, 9 figures, 2 table

Upper limit map of a background of gravitational waves

We searched for an anisotropic background of gravitational waves using data from the LIGO S4 science run and a method that is optimized for point sources. This is appropriate if, for example, the gravitational wave background is dominated by a small number of distinct astrophysical sources. No signal was seen. Upper limit maps were produced assuming two different power laws for the source strain power spectrum. For an f^-3 power law and using the 50 Hz to 1.8 kHz band the upper limits on the source strain power spectrum vary between 1.2e-48 Hz^-1 (100 Hz/f)^3 and 1.2e-47 Hz^-1 (100 Hz /f)^3, depending on the position in the sky. Similarly, in the case of constant strain power spectrum, the upper limits vary between 8.5e-49 Hz^-1 and 6.1e-48 Hz^-1. As a side product a limit on an isotropic background of gravitational waves was also obtained. All limits are at the 90% confidence level. Finally, as an application, we focused on the direction of Sco-X1, the closest low-mass X-ray binary. We compare the upper limit on strain amplitude obtained by this method to expectations based on the X-ray luminosity of Sco-X1.Comment: 11 pages, 9 figures, 2 table

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

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Probabilities of Type I (<i>α</i>), Type II (<i>β</i>) cost-weighted average error (<i>ω</i>_c), and average error (<i>ω</i>), with corresponding test conclusions for Type I/Type II error cost ratios of 4, 1, and 0.25 using standard <i>α</i> levels and by setting <i>α</i> to minimize cost-weighted average of probabilities of Type I and Type II error.

a<p><i>p</i>-value used for significance testing is 0.02495 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032734#pone.0032734-Crawley1" target="_blank">[12]</a>.</p><p>Probabilities are calculated for a one-way ANOVA with <i>N</i> = 30, <i>k</i> = 3, and <i>σ</i>_{p (within groups)} = 3.4, and critical effect size = <i>σ</i>_{p (within groups)} from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032734#pone.0032734-Crawley1" target="_blank">[12]</a>.</p

The non-linear relationship between <i>α</i> and <i>β</i>.

<p>The relationship between <i>α</i> and <i>β</i> for an independent 2-sample, 2-tailed <i>t</i>-test with n₁ = n₂ = 10, and critical effect size = 1 <i>σ</i>.</p