Quantifying iridescent coloration in animals: a method for improving repeatability

Quantification of animal colors is important to a variety of fields of research, especially those dealing with visual communication and sexual selection. Most animal colors are easily measured using well-established spectrophotometric techniques. However, the unique characteristics of iridescent colors present particular challenges and opportunities to quantify novel color metrics. Due to the fine-scale angle dependence of iridescent coloration, color metrics, such as hue and brightness, must be measured using methods that allow for repeatable comparison across individuals (e.g., by carefully controlling and measuring viewing geometry). Here, we explain how the optical characteristics of iridescent colors should be considered when developing measurement techniques, describe the pitfalls of some commonly used techniques, and recommend improved methods and metrics (angular degree of color change and breadth of reflectance) for quantifying iridescent color. In particular, most studies of iridescent birds to date have used less than ideal procedures and have not provided repeatability estimates for their methods. For example, we demonstrate here that measuring coloration from overlapping patches of iridescent feathers may be problematic, and we argue against methods that do not carefully control viewing geometry. We recommend measuring iridescence at maximal reflectance angles using an apparatus that allows for sample rotation, and we compare this technique to some other commonly used methods using iridescent gorget and crown feathers from Anna’s hummingbirds (Calypte anna). Our apparatus allows for the quantification of angular color change, and we found that maximal reflectance measurements using single feathers are highly repeatable both within feather samples and among samples within an individual.     

Challenges in providing residual risks in carrier testing

The probability an individual is a carrier for a recessive disorder despite a negative carrier test, referred to as residual risk, has been part of carrier screening for over 2 decades. Residual risks are calculated by subtracting the frequency of carriers of pathogenic variants detected by the test from the carrier frequency in a population, estimated from the incidence of the disease. Estimates of the incidence (and therefore carrier frequency) of many recessive disorders differ among different population groups and are inaccurate or unavailable for many genes on large carrier screening panels for most of the world's populations. The pathogenic variants detected by the test and their frequencies also vary across groups and over time as variants are newly discovered or reclassified, which requires today's residual carrier risks to be continually updated. Even when a residual carrier risk is derived using accurate data obtained in a particular group, it may not apply to many individuals in that group because of misattributed ancestry or unsuspected admixture. Missing or inaccurate data, the challenge of determining meaningful ancestry-specific risks and applying them appropriately, and a lack of evidence they impact management, suggest that patients be counseled that although carrier screening may miss a small fraction of carriers, residual risks with contemporary carrier screening are well below the risk posed by invasive prenatal diagnosis, even if one member of the couple is a carrier, and that efforts to provide precise residual carrier risks are unnecessary.     

Eigenbehaviors: identifying structure in routine

Longitudinal behavioral data generally contains a significant amount of structure. In this work, we identify the structure inherent in daily behavior with models that can accurately analyze, predict, and cluster multimodal data from individuals and communities within the social network of a population. We represent this behavioral structure by the principal components of the complete behavioral dataset, a set of characteristic vectors we have termed eigenbehaviors. In our model, an individual’s behavior over a specific day can be approximated by a weighted sum of his or her primary eigenbehaviors. When these weights are calculated halfway through a day, they can be used to predict the day’s remaining behaviors with 79% accuracy for our test subjects. Additionally, we demonstrate the potential for this dimensionality reduction technique to infer community affiliations within the subjects’ social network by clustering individuals into a “behavior space” spanned by a set of their aggregate eigenbehaviors. These behavior spaces make it possible to determine the behavioral similarity between both individuals and groups, enabling 96% classification accuracy of community affiliations within the population-level social network. Additionally, the distance between individuals in the behavior space can be used as an estimate for relational ties such as friendship, suggesting strong behavioral homophily amongst the subjects. This approach capitalizes on the large amount of rich data previously captured during the Reality Mining study from mobile phones continuously logging location, proximate phones, and communication of 100 subjects at MIT over the course of 9 months. As wearable sensors continue to generate these types of rich, longitudinal datasets, dimensionality reduction techniques such as eigenbehaviors will play an increasingly important role in behavioral research. This contribution is part of the special issue “Social Networks: new perspectives” (Guest Editors: J. Krause, D. Lusseau and R. James). An erratum to this article can be found at     

Pathways for the oxidation of sarin in urban atmospheres

The nerve agent sarin has recently been deployed by terrorists in a major city. The molecule is volatile and made its way to many victims by passing as vapor through a highly reactive medium. Here we estimate rates and pathways for the removal of gas phase sarin from a generalized urban atmosphere. Only information from the open scientific literature is used. By structure reactivity comparisons with the organophosphorus pesticides, hydroxyl radical hydrogen abstraction may occur in as little as one hour. Decomposition of side chains after hydroxyl attack leads to organic oxygenates which preserve the phosphonofluoridate and so toxicity. The aqueous aerosol surface is contacted in minutes and offers access to a range of dissolved nucleophiles. Substitution displaces the fluoride leaving group, giving safe phosphoric acid analogs. Because of uncertainties in the electron distribution and in aqueous decay mechanisms, the time constants must be viewed as lower limits.     

The effect of ambient ozone pollution and acidic rain on the growth and chlorophyll content of green and white ash

Two- and three-year old green ash (Fraxinus americana L.) and white ash (Fraxinus pennsylvanica Marsh.) seedlings were exposed to combinations of ambient ozone and acidic ambient rainfall in New Brunswick, New Jersey. During the 3-year study the potted seedlings did not develop typical foliar ozone toxicity symptoms, despite the occurrence of as many as 78 h in exceedance of the National Ambient Air Quality Standard of 0.12 ppm. Although the pH of the rainfall was as low as 3.6 and averaged 4.1, no symptoms were observed resulting from the ambient precipitation. The rate of shoot growth in terms of height and diameter was generally not affected by either of the pollutants during the growing season. Although the chlorophyll content of white ash foliage was low following frequent rainfall in the early summer of 1984, there was no statistically significant evidence that acid raid or ambient ozone decreased chlorophyll in ash seedlings during the 3-year study.