ABSTRACT
PREMISE: Statistical methods used by most morphologists to validate species boundaries (such as principal component analysis [PCA] and non-metric multidimensional scaling [nMDS]) are limiting because these methods are mostly used as visualization methods, and because the groups are identified by taxonomists (i.e., supervised), adding human bias. Here, we use a spectral clustering algorithm for the unsupervised discovery of species boundaries followed by the analysis of the cluster-defining characters. METHODS: We used spectral clustering, nMDS, and PCA on 16 morphological characters within the genus Hedychium to group 93 individuals from 10 taxa. A radial basis function kernel was used for the spectral clustering with user-specified tuning values (gamma). The goodness of the discovered clusters using each gamma value was quantified using eigengap, a normalized mutual information score, and the Rand index. Finally, mutual information-based character selection and a t-test were used to identify cluster-defining characters. RESULTS: Spectral clustering revealed five, nine, and 12 clusters of taxa in the species complexes examined here. Character selection identified at least four characters that defined these clusters. DISCUSSION: Together with our proposed character analysis methods, spectral clustering enabled the unsupervised discovery of species boundaries along with an explanation of their biological significance. Our results suggest that spectral clustering combined with a character selection analysis can enhance morphometric analyses and is superior to current clustering methods for species delimitation.
ABSTRACT
PREMISE: We present a low-cost, battery-operated, portable pump, "FloPump," which allows regulated air sampling for the study of volatile organic compounds (VOCs). VOCs are routinely investigated in applications such as atmospheric chemistry, agriculture, and fragrance biology. METHODS AND RESULTS: We compared the performance of FloPump with the Supelco pump in collecting VOCs using two test samples: guava fruit (Psidium guajava) and a perfume. The sampling and identification of volatiles was carried out using a dynamic headspace sampling method followed by gas chromatography-mass spectrometry. We show that the sampling efficiency of FloPump is comparable to the commercial pump, and at an affordable cost of ~US$115 (~86% cheaper), it provides a viable option for researchers interested in sampling volatiles on a constrained budget. CONCLUSIONS: Accurate air sampling is critical for the study of VOCs. We propose that FloPump will make air sampling more affordable, thus encouraging studies of VOCs.
ABSTRACT
Large carpenter bees are charismatic and ubiquitous flower visitors in the tropics and sub-tropics. Unlike honeybees and bumblebees that have been popular subjects of extensive studies on their neuroethology, behaviour and ecology, carpenter bees have received little attention. This review integrates what is known about their foraging behaviour as well as sensory, physiological and cognitive adaptations and is motivated by their versatility as flower visitors and pollinators. This is evident from their extremely generalist foraging and adeptness at handling diverse flower types as legitimate pollinators and as illegitimate nectar robbers. They purportedly use traplining to forage between isolated patches and are long-distance flyers over several kilometres suggesting well-developed spatial learning, route memory and navigational capabilities. They have a broad range of temperature tolerance and thermoregulatory capabilities which are likely employed in their forays into crepuscular and nocturnal time periods. Such temporal extensions into dim-light periods invoke a suite of visual adaptations in their apposition optics. Thus, we propose that carpenter bees are an excellent though understudied group for exploring the complex nature of plant-pollinator mutualisms from ecological and mechanistic perspectives.
