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

Mapping bugweed (Solanum mauritianum) infestations in Pinus patula plantations using hyperspectral imagery and support vector machines

The invasive plant known as bugweed (Solanum mauritianum) is a notorious invader of forestry plantations in the eastern parts of South Africa. Not only is bugweed considered to be one of five most widespread invasive alien plant (IAP) species in the summer rainfall regions of South Africa but it is also one of the worst invasive alien plants in Africa. It forms dense infestations that not only impacts upon commercial forestry activities but also causes significant ecological and environment damage within natural areas. Effective weed management efforts therefore require robust approaches to accurately detect; map and monitor weed distribution in order to mitigate the impact on forestry operations. The main objective of this research was to determine the utility of support vector machines (SVMs) with a 272-waveband AISA Eagle image to detect and map the presence of co-occurring bugweed within mature Pinus patula compartments in KwaZulu Natal. The SVMwhen utilized with a recursive feature elimination (SVM-RFE) approach required only 17 optimal wavebands from the original image to produce a classification accuracy of 93% and True Skills Statistic of 0.83. Results from this study indicate that (1) there is definite potential for using SVMs for the accurate detection and mapping of bugweed in commercial plantations and (2) it is not necessary to use the entire 272-waveband dataset because the SVM-RFE approach identified an optimal subset of wavebands for weed detection thus enabling improved data processing and analysis.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?reload=true&punumber=4609443hb201