Many interactive human skills are based on real-time error detection and correction. Here we investigate the spectral properties of such skills, focusing on a synchronization task. A simple autoregressive error correction model, based on separate 'motor' and 'cognitive' sources, provides an excellent fit to experimental spectral data. The model can also apply to recurrent processes not based on error correction, allowing commentary on previous claims of 1/f-type noise in human cognition. A comparison of expert and non-expert subjects suggests that performance skill is not only based on reduced variance and bias, but also on the construction of richer mental models of error correction.

Biodiversity is most commonly measured in taxonomic richness. For example, it is common to describe how diverse a genus or a geographic area is by counting the number of species within them. Phylogenetic diversity (PD), a measurement of the branch lengths in a phylogenetic tree, is a better measure of biodiversity that provides a comparable, evolutionary measure of biodiversity not possible with species counts. Despite its advantages, PD is rarely used as the primary measure of biodiversity. We developed a genus‐level phylogeny for nearly 90% of taxonomically described Australian land plants and compared PD to genus richness in multiple clades. The proportion of PD per genera was skewed among clades. Non‐angiosperm clades had more PD than expected given the number of genera while angiosperm clades had less PD than expected. For example, ferns comprised only 4.7% of the genera yet 13.0% of the PD, while the angiosperms as a whole comprised 78.9% of the genera but only 62.7% of the PD. It is likely that cultural reasons, such as taxonomic biases, are more important than methodological and biological phenomena in explaining these discrepancies. Regardless of reasons for the observed results, we conclude that a shift towards the use of PD as the primary descriptor of biodiversity will promote an important conceptual shift in biodiversity studies as a quantitative science.

Contemporary collections of sponges in the Indo-west Pacific have escalated substantially due to pharmaceutical discovery, national bioregional planning, and compliance with international conventions on the seabed and its marine genetic resources beyond national jurisdictions. These partially processed operational taxonomic unit (OTU) collections now vastly outweigh the expertise available to make them better "known" via complete taxonomy, yet for many bioregions they represent the most significant body of currently available knowledge. Increasing numbers of cryptic species, previously undetected morphologically, are now being discovered by molecular and chemical analyses. The uncoordinated and fragmented nature of many previous collections, however, means that knowledge and expertise gained from a particular project are often lost to future projects without a biodiversity informatics legacy. Integrating these diverse data (GIS; OTUs; images; molecular, chemical, and other datasets) required a two-way iterative process so far unavailable for sponges with existing biodiversity informatics tools. SpongeMaps arose from the initial need for online collaboration to integrate morphometric data with molecular barcodes, including the Porifera Tree of Life (PorTol) project. It provides interrogation of existing data to better process new collections; capacity to create new OTUs; publication of online pages for individual species, so as to interpret GIS and other data for online biodiversity databases and services; and automatic links to external datasets for taxonomic hierarchy, specimen GIS and mapping, DNA sequence data, chemical structures, and images.

A new, ultra-small, light-activated microtransponder ("p-Chip") has been integrated into the heads of entomological pins toimprove efficiency in collections management and research through radio frequency identification (RFID) of insect specimens.These specimens are typically small, fragile, numerous and especially difficult to track. Globally, the majority are not currentlyrecorded in any database. The application of unique identifiers has previously proven time consuming and difficult. Permanentand integral to the specimen, each p-Chip transmits a unique serial number allowing tracking without contact and reducing therisk of damage to specimens and repetitive strain injuries (RSI) in curators. The p-Chips and the specimens they tag can belinked immediately to biodiversity web services and collections databases. Specimens can be rapidly assigned to groupings asthey are sorted and their taxonomic identity refined; and accurately tracked through high throughput methods and analyses.Quite importantly, with the p-Chips, the profile of the pin head is unchanged, and there is no discernible tactile difference fromstandard entomological pins. We also describe how p-Chips can be retro-fitted to provide complete compendia of legacy samples.

Computer analysis of video footage is one option for recording locomotor behavior for a range of neurophysiological and behavioral studies. This technique is reasonably well established and accepted, but its use for some behavioral analyses remains a challenge. For example, filming through water can lead to reflection, and filming nocturnal activity can reduce resolution and clarity of filmed images. The aim of this study was to develop a noninvasive method for recording nocturnal activity in aquatic decapods and test the accuracy of analysis by video tracking software. We selected crayfish, Cherax destructor, because they are often active at night, they live underwater, and data on their locomotion is important for answering biological and physiological questions such as how they explore and navigate. We constructed recording arenas and filmed animals in infrared light. Wethen compared human observer data and software-acquired values. In this article, we outline important apparatus and software issues to obtain reliable computer tracking.