Summary Confirmation of invasive species eradication following management programmes is typically determined by waiting an arbitrary period of time before determining success or failure based upon the then obvious presence or absence of the target species. Rapid eradication assessment could be achieved more expediently by applying statistical models of the probability of detecting survivors and their offspring, using a grid of detection devices, for a given set of biological and monitoring parameters. We simulate estimation of the probability of eradication for invasive rodents on islands across a range of monitoring parameters in order to provide guidance to managers on the optimal values, diminishing returns and trade‐offs in monitoring to achieve a given level of confidence in successful eradication. We found that monitoring an island for survivors over 15–20 nights is optimal and that waiting longer than a year before commencing monitoring has a negligible impact on the estimated probability of success. The spacing between detection devices has a considerable influence on estimated probability of success but only when it is <60 m. Intrinsic biological parameters of the target species have a substantial impact on confirming the probability of success, but validated field data are lacking to reliably incorporate these in current rapid eradication assessment models. We present case studies demonstrating cost savings of at least 5% to managers when applying rapid eradication assessment to the eradication of house mice Mus musculus from Isla Pájaros and Isla Muertos in Arrecife Alacranes (Scorpion Reef) Mexico, and implement the rapid eradication assessment model in an HTML GUI interface for eradication managers ( www.rea.is). Synthesis and applications. Rapid eradication assessment (REA) is a powerful tool for managers to design optimal invasive species eradication monitoring programmes. We recommend island eradication managers routinely implement REA on small islands for the demonstrated cost savings and to accelerate eradication confirmation, ultimately facilitating island restoration.

We show here that computer game players can build high-quality crystal structures. Introduction of a new feature into the computer game Foldit allows players to build and real-space refine structures into electron density maps. To assess the usefulness of this feature, we held a crystallographic model-building competition between trained crystallographers, undergraduate students, Foldit players and automatic model-building algorithms. After removal of disordered residues, a team of Foldit players achieved the most accurate structure. Analysing the target protein of the competition, YPL067C, uncovered a new family of histidine triad proteins apparently involved in the prevention of amyloid toxicity. From this study, we conclude that crystallographers can utilize crowdsourcing to interpret electron density information and to produce structure solutions of the highest quality.

TableToLongForm automatically converts hierarchical Tables intended for a human reader into a simple LongForm dataframe that is machine readable, making it easier to access and use the data for analysis. It does this by recognising positional cues present in the hierarchical Table (which would normally be interpreted visually by the human brain) to decompose, then reconstruct the data into a LongForm dataframe. The article motivates the benefit of such a conversion with an example Table, followed by a short user manual, which includes a comparison between the simple one argument call to TableToLongForm, with code for an equivalent manual conversion. The article then explores the types of Tables the package can convert by providing a gallery of all recognised patterns. It finishes with a discussion of available diagnostic methods and future work.