Synchronizing Sequencing Software to a Live Drummer

Copyright 2013 Massachusetts Institute of Technology. MIT allows authors to archive published versions of their articles after an embargo period. The article is available at

The distribution and spread of the invasive alien common myna, Acridotheres tristis L. (Aves: Sturnidae), in southern Africa

The common myna is an Asian starling that has become established in many parts of the world outside of its native range due to accidental or deliberate introductions by humans. The South African population of this species originated from captive birds that escaped in Durban in 1902. A century later, the common myna has become abundant throughout much of South Africa and is considered to pose a serious threat to indigenous biodiversity. Preliminary observations suggest that the common myna's distribution is closely tied to that of humans, but empirical evidence for this hypothesis is lacking. We have investigated the relationships between common myna distribution, human population size and land-transformation values at a quarter-degree resolution in South Africa. Common mynas were found more frequently than expected by chance in areas with greater human population numbers and land-transformation values. We also investigated the spatial relationship between the bird's range and the locations of South Africa's protected areas at the quarter-degree scale. These results indicate that, although there is some overlap, the common myna distribution is not closely tied to the spatial arrangement of protected areas. We discuss the original introduction, establishment and rate of spread of the common myna in South Africa and neighbouring countries and contrast the current distribution with that presented in The Atlas of Southern African Birds. We also discuss the factors that affect the common myna's success and the consequences that invasion by this species is likely to have, specifically in protected areas

On the interpretation of Michelson-Morley experiments

Recent proposals for improved optical tests of Special Relativity have renewed interest in the interpretation of such tests. In this paper we discuss the interpretation of modern realizations of the Michelson-Morley experiment in the context of a new model of electrodynamics featuring a vector-valued photon mass. This model is gauge invariant, unlike massive-photon theories based on the Proca equation, and it predicts anisotropy of both the speed of light and the electric field of a point charge. The latter leads to an orientation dependence of the length of solid bodies which must be accounted for when interpreting the results of a Michelson-Morley experiment. Using a simple model of ionic solids we show that, in principle, the effect of orientation dependent length can conspire to cancel the effect of an anisotropic speed of light in a Michelson-Morley experiment, thus, complicating the interpretation of the results.Comment: To appear in Phys.Lett.

Biogeo : an R package for assessing and improving data quality of occurrence record datasets

Occurrence data from museum and herbarium collections are valuable for mapping biodiversity patterns in space and time. Unfortunately these collections datasets contain many errors and suffer from several data quality issues that can influence the quality of the products derived from them. It is up to the user to identify these errors and data quality issues when using these data. Despite the large number of potential users of these datasets there are few software tools dedicated to error detection and correction of collections datasets. The R package biogeo was developed for detecting and correcting errors and for assessing of data quality of collections datasets consisting of occurrence records. Features of the package include error detection, such as mismatches between the recorded country and the country where the record is plotted, records of terrestrial species that fall into the sea and outlier detection. A key feature of the package is the ability to identify likely alternative positions for points that represent obvious errors in the dataset and functions to explore records in geographical and environmental space in order to identify possible errors in the dataset. Functions are also available for converting coordinates that are in various text formats into degrees, minutes and seconds and then into decimal degrees.The DST-NRF Centre for Invasion Biology, the National Research Foundation and the University of Pretoria.http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1600-05872017-04-30hb2017Zoology and Entomolog

Biogeo : an R package for assessing and improving data quality of occurrence record datasets

Occurrence data from museum and herbarium collections are valuable for mapping biodiversity patterns in space and time. Unfortunately these collections datasets contain many errors and suffer from several data quality issues that can influence the quality of the products derived from them. It is up to the user to identify these errors and data quality issues when using these data. Despite the large number of potential users of these datasets there are few software tools dedicated to error detection and correction of collections datasets. The R package biogeo was developed for detecting and correcting errors and for assessing of data quality of collections datasets consisting of occurrence records. Features of the package include error detection, such as mismatches between the recorded country and the country where the record is plotted, records of terrestrial species that fall into the sea and outlier detection. A key feature of the package is the ability to identify likely alternative positions for points that represent obvious errors in the dataset and functions to explore records in geographical and environmental space in order to identify possible errors in the dataset. Functions are also available for converting coordinates that are in various text formats into degrees, minutes and seconds and then into decimal degrees.The DST-NRF Centre for Invasion Biology, the National Research Foundation and the University of Pretoria.http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1600-05872017-04-30hb2017Zoology and Entomolog

Biogeo : an R package for assessing and improving data quality of occurrence record datasets

Occurrence data from museum and herbarium collections are valuable for mapping biodiversity patterns in space and time. Unfortunately these collections datasets contain many errors and suffer from several data quality issues that can influence the quality of the products derived from them. It is up to the user to identify these errors and data quality issues when using these data. Despite the large number of potential users of these datasets there are few software tools dedicated to error detection and correction of collections datasets. The R package biogeo was developed for detecting and correcting errors and for assessing of data quality of collections datasets consisting of occurrence records. Features of the package include error detection, such as mismatches between the recorded country and the country where the record is plotted, records of terrestrial species that fall into the sea and outlier detection. A key feature of the package is the ability to identify likely alternative positions for points that represent obvious errors in the dataset and functions to explore records in geographical and environmental space in order to identify possible errors in the dataset. Functions are also available for converting coordinates that are in various text formats into degrees, minutes and seconds and then into decimal degrees.The DST-NRF Centre for Invasion Biology, the National Research Foundation and the University of Pretoria.http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1600-05872017-04-30hb2017Zoology and Entomolog

A PCA-based modelling technique for predicting environmental suitability for organisms from presence records

We present a correlative modelling technique that uses locality records (associated with species presence) and a set of predictor variables to produce a statistically justifiable probability response surface for a target species. The probability response surface indicates the suitability of each grid cell in a map for the target species in terms of the suite of predictor variables. The technique constructs a hyperspace for the target species using principal component axes derived from a principal components analysis performed on a training dataset. The training dataset comprises the values of the predictor variables associated with the localities where the species has been recorded as present. The origin of this hyperspace is taken to characterize the centre of the niche of the organism. All the localities (grid‐cells) in the map region are then fitted into this hyperspace using the values of the predictor variables at these localities (the prediction dataset). The Euclidean distance from any locality to the origin of the hyperspace gives a measure of the ‘centrality’ of that locality in the hyperspace. These distances are used to derive probability values for each grid cell in the map region. The modelling technique was applied to bioclimatic data to predict bioclimatic suitability for three alien invasive plant species (Lantana camara L., Ricinus communis L. and Solanum mauritianum Scop.) in South Africa, Lesotho and Swaziland. The models were tested against independent test records by calculating area under the curve (AUC) values of receiver operator characteristic (ROC) curves and kappa statistics. There was good agreement between the models and the independent test records. The pre‐processing of climatic variable data to reduce the deleterious effects of multicollinearity, and the use of stopping rules to prevent overfitting of the models are important aspects of the modelling process