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Large-scale digitization of natural history collections requires automation of image acquisition and processing. Reflecting this fact, various approaches, some highly sophisticated, have been developed to support imaging of museum specimens. However, most of these systems are complex and expensive, restricting their deployment. Here we describe a simple, inexpensive technique for imaging arthropods larger than 5 mm. By mounting a digital SLR camera on a CNC (computer numerical control) motor-drive rig, we created a system that captures high-resolution z-axis stacked images (6960 × 4640 pixels) of 95 specimens in 30 minutes. This system can be assembled inexpensively ($1000 USD without a camera) and it is easy to set-up and maintain. By coupling low cost with high production capacity, it represents a solution for digitizing any natural history collection.

Abstract Global biodiversity gradients are generally expected to reflect greater species replacement closer to the equator. However, empirical validation of global biodiversity gradients largely relies on vertebrates, plants, and other less diverse taxa. Here we assess the temporal and spatial dynamics of global arthropod biodiversity dynamics using a beta-diversity framework. Sampling includes 129 sampling sites whereby malaise traps are deployed to monitor temporal changes in arthropod communities. Overall, we encountered more than 150,000 unique barcode index numbers (BINs) (i.e. species proxies). We assess between site differences in community diversity using beta-diversity and the partitioned components of species replacement and richness difference. Global total beta-diversity (dissimilarity) increases with decreasing latitude, greater spatial distance and greater temporal distance. Species replacement and richness difference patterns vary across biogeographic regions. Our findings support long-standing, general expectations of global biodiversity patterns. However, we also show that the underlying processes driving patterns may be regionally linked.

The taxonomic identification of organisms from images is an active research area within the machine learning community. Current algorithms are very effective for object recognition and discrimination, but they require extensive training datasets to generate reliable assignments. This study releases 5.6 million images with representatives from 10 arthropod classes and 26 insect orders. All images were taken using a Keyence VHX-7000 Digital Microscope system with an automatic stage to permit high-resolution (4K) microphotography. Providing phenotypic data for 324,000 species derived from 48 countries, this release represents, by far, the largest dataset of standardized arthropod images. As such, this dataset is well suited for testing the efficacy of machine learning algorithms for identifying specimens into higher taxonomic categories.

DNA barcoding protocols require the linkage of each sequence record to a voucher specimen that has, whenever possible, been authoritatively identified. Natural history collections would seem an ideal resource for barcode library construction, but they have never seen large-scale analysis because of concerns linked to DNA degradation. The present study examines the strength of this barrier, carrying out a comprehensive analysis of moth and butterfly (Lepidoptera) species in the Australian National Insect Collection. Protocols were developed that enabled tissue samples, specimen data, and images to be assembled rapidly. Using these methods, a five-person team processed 41,650 specimens representing 12,699 species in 14 weeks. Subsequent molecular analysis took about six months, reflecting the need for multiple rounds of PCR as sequence recovery was impacted by age, body size, and collection protocols. Despite these variables and the fact that specimens averaged 30.4 years old, barcode records were obtained from 86% of the species. In fact, one or more barcode compliant sequences (>487 bp) were recovered from virtually all species represented by five or more individuals, even when the youngest was 50 years old. By assembling specimen images, distributional data, and DNA barcode sequences on a web-accessible informatics platform, this study has greatly advanced accessibility to information on thousands of species. Moreover, much of the specimen data became publically accessible within days of its acquisition, while most sequence results saw release within three months. As such, this study reveals the speed with which DNA barcode workflows can mobilize biodiversity data, often providing the first web-accessible information for a species. These results further suggest that existing collections can enable the rapid development of a comprehensive DNA barcode library for the most diverse compartment of terrestrial biodiversity - insects.