There are 12 new articles in PLoS ONE today. As always, you should rate the articles, post notes and comments and send trackbacks when you blog about the papers. You can now also easily place articles on various social services (CiteULike, Connotea, Stumbleupon, Facebook and Digg) with just one click. Here are my own picks for the week - you go and look for your own favourites:
A Meta-Analysis of Local Adaptation in Plants:
Local adaptation is of fundamental importance in evolutionary, population, conservation, and global-change biology. The generality of local adaptation in plants and whether and how it is influenced by specific species, population and habitat characteristics have, however, not been quantitatively reviewed. Therefore, we examined published data on the outcomes of reciprocal transplant experiments using two approaches. We conducted a meta-analysis to compare the performance of local and foreign plants at all transplant sites. In addition, we analysed frequencies of pairs of plant origin to examine whether local plants perform better than foreign plants at both compared transplant sites. In both approaches, we also examined the effects of population size, and of the habitat and species characteristics that are predicted to affect local adaptation. We show that, overall, local plants performed significantly better than foreign plants at their site of origin: this was found to be the case in 71.0% of the studied sites. However, local plants performed better than foreign plants at both sites of a pair-wise comparison (strict definition of local adaption) only in 45.3% of the 1032 compared population pairs. Furthermore, we found local adaptation much more common for large plant populations (>1000 flowering individuals) than for small populations (<1000 flowering individuals) for which local adaptation was very rare. The degree of local adaptation was independent of plant life history, spatial or temporal habitat heterogeneity, and geographic scale. Our results suggest that local adaptation is less common in plant populations than generally assumed. Moreover, our findings reinforce the fundamental importance of population size for evolutionary theory. The clear role of population size for the ability to evolve local adaptation raises considerable doubt on the ability of small plant populations to cope with changing environments.
Estimating the Confidence Level of White Matter Connections Obtained with MRI Tractography:
Since the emergence of diffusion tensor imaging, a lot of work has been done to better understand the properties of diffusion MRI tractography. However, the validation of the reconstructed fiber connections remains problematic in many respects. For example, it is difficult to assess whether a connection is the result of the diffusion coherence contrast itself or the simple result of other uncontrolled parameters like for example: noise, brain geometry and algorithmic characteristics. In this work, we propose a method to estimate the respective contributions of diffusion coherence versus other effects to a tractography result by comparing data sets with and without diffusion coherence contrast. We use this methodology to assign a confidence level to every gray matter to gray matter connection and add this new information directly in the connectivity matrix. Our results demonstrate that whereas we can have a strong confidence in mid- and long-range connections obtained by a tractography experiment, it is difficult to distinguish between short connections traced due to diffusion coherence contrast from those produced by chance due to the other uncontrolled factors of the tractography methodology.
In the absence of other evidence, modelling has been used extensively to help policy makers plan for a potential future influenza pandemic. We have constructed an individual based model of a small community in the developed world with detail down to exact household structure obtained from census collection datasets and precise simulation of household demographics, movement within the community and individual contact patterns. We modelled the spread of pandemic influenza in this community and the effect on daily and final attack rates of four social distancing measures: school closure, increased case isolation, workplace non-attendance and community contact reduction. We compared the modelled results of final attack rates in the absence of any interventions and the effect of school closure as a single intervention with other published individual based models of pandemic influenza in the developed world. We showed that published individual based models estimate similar final attack rates over a range of values for R0 in a pandemic where no interventions have been implemented; that multiple social distancing measures applied early and continuously can be very effective in interrupting transmission of the pandemic virus for R0 values up to 2.5; and that different conclusions reached on the simulated benefit of school closure in published models appear to result from differences in assumptions about the timing and duration of school closure and flow-on effects on other social contacts resulting from school closure. Models of the spread and control of pandemic influenza have the potential to assist policy makers with decisions about which control strategies to adopt. However, attention needs to be given by policy makers to the assumptions underpinning both the models and the control strategies examined.
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