Communicating statistics through the media in the time of Covid-19

Professor Kevin McConway and Professor Sir David Spiegelhalter discuss their experiences of communicating statistical research to the media and offer 12 tips for researchers to effectively engage with the media. The coronavirus pandemic has brought an unprecedented demand from the media for statistical commentary. Whereas a trip to a studio for a radio or TV interview was ... Continue

Ecological and genetic correlates of long-term population trends in the Park Grass Experiment

The Park Grass Experiment (PGE) is the longest observed set of experimental plant communities in existence. Although the gross composition of the vegetation was at equilibrium over the 60-yr period from 1920 to 1979, annual records show that individual species exhibited a range of dynamics. We tested two hypotheses to explain why some species initially increased nd why subsequently some of these (the outbreak species) decreased gain. The study was designed around eight phylogenetically ndependent contrasts (PICs), each containing related species with ifferent dynamics. Our first hypothesis was that persistent increasers and utbreakers have higher intrinsic rates of natural increase than ontrol species (species without trends), allowing them to spread hen interspecific competition is reduced by drought. This was tested by measuring establishment and seed production of species in ield experiments, with and without interspecific competition. Seed production in outbreak species responded more strongly to release from interspecific competition than it did in either of the ther groups of species. Our second hypothesis was that outbreak species eventually declined because they lacked the genetic variation ecessary to adapt to the novel habitats to which they had initially spread. We tested this by measuring mating systems and genetic diversity in persistent and outbreak species in the PGE. In seven out of seven PICs tested, the outbreak species was more selfing than its persistent relative. There was a significant positive correlation between outcrossing rate and gene diversity. These results support roles for both ecological and genetic traits in long-term dynamics

Crowdsourcing the identification of organisms: a case-study of iSpot

Accurate species identification is fundamental to biodiversity science, but the natural history skills required for this are neglected in formal education at all levels. In this paper we describe how the web application ispotnature.org and its sister site ispot.org.za (collectively, “iSpot”) are helping to solve this problem by combining learning technology with crowdsourcing to connect beginners with experts. Over 94% of observations submitted to iSpot receive a determination. External checking of a sample of 3,287 iSpot records verified > 92% of them. To mid 2014, iSpot crowdsourced the identification of 30,000 taxa (>80% at species level) in > 390,000 observations with a global community numbering > 42,000 registered participants. More than half the observations on ispotnature.org were named within an hour of submission. iSpot uses a unique, 9-dimensional reputation system to motivate and reward participants and to verify determinations. Taxon-specific reputation points are earned when a participant proposes an identification that achieves agreement from other participants, weighted by the agreers’ own reputation scores for the taxon. This system is able to discriminate effectively between competing determinations when two or more are proposed for the same observation. In 57% of such cases the reputation system improved the accuracy of the determination, while in the remainder it either improved precision (e.g. by adding a species name to a genus) or revealed false precision, for example where a determination to species level was not supported by the available evidence. We propose that the success of iSpot arises from the structure of its social network that efficiently connects beginners and experts, overcoming the social as well as geographic barriers that normally separate the two

Citizen Science Reveals Unexpected Continental-Scale Evolutionary Change in a Model Organism

Organisms provide some of the most sensitive indicators of climate change and evolutionary responses are becoming apparent in species with short generation times. Large datasets on genetic polymorphism that can provide an historical benchmark against which to test for recent evolutionary responses are very rare, but an exception is found in the brown-lipped banded snail (Cepaea nemoralis). This species is sensitive to its thermal environment and exhibits several polymorphisms of shell colour and banding pattern affecting shell albedo in the majority of populations within its native range in Europe. We tested for evolutionary changes in shell albedo that might have been driven by the warming of the climate in Europe over the last half century by compiling an historical dataset for 6,515 native populations of C. nemoralis and comparing this with new data on nearly 3,000 populations. The new data were sampled mainly in 2009 through the Evolution MegaLab, a citizen science project that engaged thousands of volunteers in 15 countries throughout Europe in the biggest such exercise ever undertaken. A known geographic cline in the frequency of the colour phenotype with the highest albedo (yellow) was shown to have persisted and a difference in colour frequency between woodland and more open habitats was confirmed, but there was no general increase in the frequency of yellow shells. This may have been because snails adapted to a warming climate through behavioural thermoregulation. By contrast, we detected an unexpected decrease in the frequency of Unbanded shells and an increase in the Mid-banded morph. Neither of these evolutionary changes appears to be a direct response to climate change, indicating that the influence of other selective agents, possibly related to changing predation pressure and habitat change with effects on micro-climate

Justify your alpha

Benjamin et al. proposed changing the conventional “statistical significance” threshold (i.e.,the alpha level) from p ≤ .05 to p ≤ .005 for all novel claims with relatively low prior odds. They provided two arguments for why lowering the significance threshold would “immediately improve the reproducibility of scientific research.” First, a p-value near .05provides weak evidence for the alternative hypothesis. Second, under certain assumptions, an alpha of .05 leads to high false positive report probabilities (FPRP2 ; the probability that a significant finding is a false positive

Justify your alpha

In response to recommendations to redefine statistical significance to p ≤ .005, we propose that researchers should transparently report and justify all choices they make when designing a study, including the alpha level

[Book review] Bayesian Data Analysis for Animal Scientists: the Basics

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Investigating causes and evaluating treatments

About the book: What makes us ill? How do we know what makes us ill? Biologists, doctors, statisticians, sociologists and historians all study health and disease. This book describes the basic methods of investigation used by all these professional, and shows how they are related and how they differ. The book works through examples such as diabetes and spina bifida to demonstrate how the causation of disease can be studied at many different levels - from microscopic processes within body cells to large-scale matters like the relationships between different groups of people in society. The aim is to provide readers with a critical understanding of the ways in which our knowledge of health and disease was arrived at, and to show how knowledge from various disciplines can fit together to provide a full picture of health and disease in our world