Flower color in the weedy perennial Plantago lanceolata is phenotypically plastic. Darker flowers are produced at cooler ambient temperatures, and circumstantial evidence suggests that this is adaptive. The goal of this project was to investigate the chemical basis for the color plasticity. To test the hypothesis that increased anthocyanin production at low temperatures underlies the plasticity, extracts of P. lanceolata flowers produced at warm and cool temperatures were analyzed using UV/visible spectrophotometry coupled with mass spectrometry. Mass spectrometry allowed us to compare relative abundances of individual anthocyanins. Seventeen anthocyanins, derived from both cyanidin and delphinidin branches of the anthocyanin biosynthetic pathway, were detected. Most of these significantly increased in abundance under cool conditions. Genotypes differed significantly in anthocyanin levels and in their sensitivity to temperature change. Genotypes that showed greater floral color plasticity tended to show also greater temperature sensitivity with respect to anthocyanin production. Data suggest that the temperature regulation of the anthocyanin biosynthetic pathway occurs both upstream and downstream of the divergence of the cyanidin and delphinidin branches. The degree of temperature sensitivity, i.e. phenotypic plasticity, appears to be controlled downstream, whereas the overall temperature effect appears to be controlled upstream.

Objective This study advances the presidential primary literature in two ways. First, since many studies in this literature advocate for more detailed theoretical development, we incorporate an interdisciplinary approach by utilizing social contagion theory from the field of sociology. Second, presidential primaries do not adequately explore what role the public plays during the invisible primary. We thus incorporate Google Trends data into presidential primary models to account for the relative amount of public attention for each presidential primary candidate. Methods We use fixed effects regression to determine the impact of public attention on a candidate's share of the contested primary vote (CPV). Results We find that increased public attention leads to higher levels of support for a candidate in the Iowa caucuses, New Hampshire primary, and CPV. Conclusion These findings illustrate the extra‐voting role the public plays in presidential primary elections and helps us further distinguish how party elites, voters, and candidates uniquely determine the selection of our executive.

The invisible primary is an important time in United States Presidential primary politics as candidates gain momentum for their campaigns before they compete formally in the first state caucus (Iowa) and primaries (e.g. New Hampshire). This critical period has not been possible to observe, hence the name. However, by simulating networks of primary followers, we can explicate hypotheses for how messages travel through networks to a ect voter preferences. To do so, we use a threshold model to drive our simulated network analysis testing spread of public support for candidates in invisible primaries. We assign voter thresholds for candidates and vary number of voters, attachment to candidates and decay. We also vary social graph structure and model. Results of the algorithm show e ects of size of lead, an unwavering base of support, and information loss.

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We examine the criterion validity of using internet searches as a measure of public attention to United States Supreme Court (USSC) cases.  First, we construct a measure of public attention to three cases by comparing relevant search terms in Google Trends to one top search terms of the year, then sum the measure week by week during the period of the research design.  To test the measure’s criterion validity, we replicate Scott and Saunders’ (2006) models using their dataset (created by conducting phone interviews of a national sample using random digit dialing) that was designed to assess awareness of USSC decisions. We find that public attention as measured by Google Trends data is predictive of public awareness of USSC decisions for two of their three models. We conclude that using free, publically available big data to measure public attention to USSC cases has criterion validity, and is a valuable tool for researchers studying public policy and process.