The movement towards open science is a consequence of seemingly pervasive failures to replicate previous research. This transition comes with great benefits but also significant challenges that are likely to affect those who carry out the research, usually early career researchers (ECRs). Here, we describe key benefits, including reputational gains, increased chances of publication, and a broader increase in the reliability of research. The increased chances of publication are supported by exploratory analyses indicating null findings are substantially more likely to be published via open registered reports in comparison to more conventional methods. These benefits are balanced by challenges that we have encountered and that involve increased costs in terms of flexibility, time, and issues with the current incentive structure, all of which seem to affect ECRs acutely. Although there are major obstacles to the early adoption of open science, overall open science practices should benefit both the ECR and improve the quality of research. We review 3 benefits and 3 challenges and provide suggestions from the perspective of ECRs for moving towards open science practices, which we believe scientists and institutions at all levels would do well to consider.

The movement towards open science is an unavoidable consequence of seemingly pervasive failures to replicate previous research. This transition comes with great benefits but also significant challenges that are likely to afflict those who carry out the research, usually Early Career Researchers (ECRs). Here, we describe key benefits including reputational gains, increased chances of publication and a broader increase in the reliability of research. These are balanced by challenges that we have encountered, and which involve increased costs in terms of flexibility, time and issues with the current incentive structure, all of which seem to affect ECRs acutely. Although there are major obstacles to the early adoption of open science, overall open science practices should benefit both the ECR and improve the quality and plausibility of research. We review three benefits, three challenges and provide suggestions from the perspective of ECRs for moving towards open science practices.

Book Reviews 485 all relevant levels, from extremely local to regional, national and even supranational social contexts. For Murie, national policy should enable locally sensible policies to develop, rather than impose a common policy and trust that it will not produce locally damaging effects.In sum, even if not complete, the book offers a useful and interesting overview of social housing policies in Europe. Substantial statistical evidence is drawn upon with a strong analytical focus. Moreover, the salient and inspiring case studies chosen raise interesting questions that cry out for further research and analysis.

BackgroundExisting influenza surveillance in the United States is focused on the collection of data from sentinel physicians and hospitals; however, the compilation and distribution of reports are usually delayed by up to 2 weeks. With the popularity of social media growing, the Internet is a source for syndromic surveillance due to the availability of large amounts of data. In this study, tweets, or posts of 140 characters or less, from the website Twitter were collected and analyzed for their potential as surveillance for seasonal influenza.ObjectiveThere were three aims: (1) to improve the correlation of tweets to sentinel-provided influenza-like illness (ILI) rates by city through filtering and a machine-learning classifier, (2) to observe correlations of tweets for emergency department ILI rates by city, and (3) to explore correlations for tweets to laboratory-confirmed influenza cases in San Diego.MethodsTweets containing the keyword “flu” were collected within a 17-mile radius from 11 US cities selected for population and availability of ILI data. At the end of the collection period, 159,802 tweets were used for correlation analyses with sentinel-provided ILI and emergency department ILI rates as reported by the corresponding city or county health department. Two separate methods were used to observe correlations between tweets and ILI rates: filtering the tweets by type (non-retweets, retweets, tweets with a URL, tweets without a URL), and the use of a machine-learning classifier that determined whether a tweet was “valid”, or from a user who was likely ill with the flu.ResultsCorrelations varied by city but general trends were observed. Non-retweets and tweets without a URL had higher and more significant (P<.05) correlations than retweets and tweets with a URL. Correlations of tweets to emergency department ILI rates were higher than the correlations observed for sentinel-provided ILI for most of the cities. The machine-learning classifier yielded the highest correlations for many of the cities when using the sentinel-provided or emergency department ILI as well as the number of laboratory-confirmed influenza cases in San Diego. High correlation values (r=.93) with significance at P<.001 were observed for laboratory-confirmed influenza cases for most categories and tweets determined to be valid by the classifier.ConclusionsCompared to tweet analyses in the previous influenza season, this study demonstrated increased accuracy in using Twitter as a supplementary surveillance tool for influenza as better filtering and classification methods yielded higher correlations for the 2013-2014 influenza season than those found for tweets in the previous influenza season, where emergency department ILI rates were better correlated to tweets than sentinel-provided ILI rates. Further investigations in the field would require expansion with regard to the location that the tweets are collected from, as well as the availability of more ILI data.

Traditional methods for monitoring influenza are haphazard and lack fine-grained details regarding the spatial and temporal dynamics of outbreaks. Twitter gives researchers and public health officials an opportunity to examine the spread of influenza in real-time and at multiple geographical scales. In this paper, we introduce an improved framework for monitoring influenza outbreaks using the social media platform Twitter. Relying upon techniques from geographic information science (GIS) and data mining, Twitter messages were collected, filtered, and analyzed for the thirty most populated cities in the United States during the 2013–2014 flu season. The results of this procedure are compared with national, regional, and local flu outbreak reports, revealing a statistically significant correlation between the two data sources. The main contribution of this paper is to introduce a comprehensive data mining process that enhances previous attempts to accurately identify tweets related to influenza. Additionally, geographical information systems allow us to target, filter, and normalize Twitter messages.

Recent neuroimaging evidence suggests that visual inputs arising beyond the fovea can be 'fed back' to foveal visual cortex to construct a new retinotopic representation. However, whether these representations are critical for extra-foveal perception remains unclear. Using transcranial magnetic stimulation we found that relatively late (350-400 msec) disruption of foveal retinotopic cortex impaired perceptual discrimination of objects in the periphery. These results are consistent with the hypothesis that feedback to the foveal retinotopic cortex is crucial for extra-foveal perception, and provide additional evidence for 'constructive' feedback in human vision.

To compare community assemblage patterns in tropical northeastern and subtropical central eastern Australia across selected gradients and scales, we tested the relationship of species traits with phylogenetic structure, and niche breadth. We considered phylogenetic relationships across current-day species in assemblages in relation to rain forest species pool sizes, and trait values along gradients including elevation and latitude. Trait values were quantified across scales for seed size, leaf area, wood density and maximum height at maturity for 1137 species and 596 assemblages using trait gradient analysis (TGA). Local assemblages of subtropical species had narrower trait ranges, and higher niche breadth values than corresponding assemblages of tropical species. Leaf size and seed size increased at low latitudes, and community phylogenetic structure was most strongly correlated with seed traits in the subtropics, reflecting dispersal and recolonization processes. Elevation accounted for little of the variance in community phylogenetic structure or trait variation across local and regional scales. Stable moist forest areas retained many species from ancestral rain forest lineages across a range of temporally conserved habitats; species within assemblages were less related; and rain forest assemblages had higher functional diversity, but lower niche breadth. This suggests that on average, assemblages of species in stable areas had greater trait variation and narrower distributions. Historic and recent rain forest contraction and re-expansion can result in recolonized areas that are dominated by species that are more related (phylogenetically) than by chance, have smaller, widely dispersed seeds, and greater niche breadth (broader distributions).

Aim  We examine the range expansion/contraction dynamics during the last glacial cycle of the late‐successional tropical rain forest conifer Podocarpus elatus using a combination of modelling and molecular marker analyses. Specifically, we test whether distributional changes predicted by environmental niche modelling are in agreement with (1) the glacial maximum contractions inferred from the southern fossil record, and (2) population genetic‐based estimates of range disjunctions and demographic dynamics. In addition, we test whether northern and southern ranges are likely to have experienced similar expansion/contraction dynamics. Location  Eastern Australian tropical and subtropical rain forests. Methods  Environmental niche modelling was completed for three time periods during the last glacial cycle and was interpreted in light of the known palynology. We collected 109 samples from 32 populations across the entire range of P. elatus. Six microsatellite loci and Bayesian coalescence analysis were used to infer population expansion/contraction dynamics, and five sequenced loci (one plastid and four nuclear) were used to quantify genetic structure/diversity. Results  Environmental niche modelling suggested that the northern and southern ranges of P. elatus experienced different expansion/contraction dynamics. In the northern range, the habitat suitable for P. elatus persisted in a small refugial area during the Last Glacial Maximum (LGM, 21 ka) and then expanded during the post‐glacial period. Conversely, in the south suitable habitat was widespread during the LGM but subsequently contracted. These differential dynamics were supported by Bayesian analyses of the population genetic data (northern dispersal) and are consistent with the greater genetic diversity in the south compared with the north. A contact zone between the two genetically divergent groups (corresponding to the Macleay Overlap Zone) was supported by environmental niche modelling and molecular analyses. Main conclusions  The climatic fluctuations of the Quaternary have differentially impacted the northern and southern ranges of a broadly distributed rain forest tree in Australia. Recurrent contraction/expansion cycles contributed to the genetic distinction between northern and southern distributions of P. elatus. By combining molecular and environmental niche modelling evidence, this unique study undermines the general assumption that broadly distributed species respond in a uniform way to climate change.