Natural history collections contain data that are critical for many scientific endeavors. Recent efforts in mass digitization are generating large datasets from these collections that can provide unprecedented insight. Here, we present examples of how deep convolutional neural networks can be applied in analyses of imaged herbarium specimens. We first demonstrate that a convolutional neural network can detect mercury-stained specimens across a collection with 90% accuracy. We then show that such a network can correctly distinguish two morphologically similar plant families 96% of the time. Discarding the most challenging specimen images increases accuracy to 94% and 99%, respectively. These results highlight the importance of mass digitization and deep learning approaches and reveal how they can together deliver powerful new investigative tools.

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Echinacea laevigata (Boynton and Beadle) Blake is a federally endangered flowering plant species restricted to four states in the southeastern United States.To determine the population structure and outcrossing rate across the range of the species, we conducted AFLP analysis using four primer combinations for 22 populations. The genetic diversity of this species was high based on the level of polymorphic loci (200 of 210 loci; 95.24%) and Nei's gene diversity (ranging from 0.1398 to 0.2606; overall 0.2611). There was significant population genetic differentiation (G ST = 0.294; O -II = 0.218 from the Bayesian f = 0 model). Results from the AMOVA analysis suggest that a majority of the genetic variance is attributed to variation within populations (70.26%), which is also evident from the PCoA. However, 82% of individuals were assigned back to the original population based on the results of the assignment test. An isolation by distance analysis indicated that genetic differentiation among populations was a function of geographic distance, although long-distance gene dispersal between some populations was suggested from an analysis of relatedness between populations using the neighbor-joining method. An estimate of the outcrossing rate based on genotypes of progenies from six of the 22 populations using the multilocus method from the program MLTR ranged from 0.780 to 0.912, suggesting that the species is predominantly outcrossing. These results are encouraging for conservation, signifying that populations may persist due to continued genetic exchange sustained by the outcrossing mating system of the species.

Abstract.-Mercuric chloride has been used to control insect and fungal infestations in natural history collections for the past two centuries. Due to health concerns, its use was discontinued in the mid-1980s, but specimens treated with mercuric chloride are commonly found in modern collections and present a hazard to collection staff and researchers. Cabinets used to store mercuric chloridetreated specimens also become contaminated with the substance and represent a source of exposure even after specimens are removed. A team at the US National Herbarium, in coordination with the Smithsonian's Office of Safety, Health and Environmental Management, developed a protocol to clean herbarium cabinets that were contaminated with mercuric chloride. Cabinets were cleaned with 70% ethanol and laboratory wipes, and effectiveness was measured using a portable mercury vapor analyzer and surface wipe sampling. Cleaning with ethanol was found to be more effective than just removing treated specimens, but the differences in reduction of airborne and surface mercury concentrations were not statistically significant. This study provides important insight and guidance for museums seeking to eliminate legacy mercuric chloride contamination from their herbarium cabinets.