In the past decade, the ability to construct digital models of natural history specimens has become faster, cheaper, and easier for researchers. This in part has led to the modern movement to cre- ate models of representatives of all vertebrate species and make these data freely available to other researchers and the general public. The openVertebrate project (or “oVert”) is leading this charge by using micro computed tomographic (μCT) scanners at universities across the United States to synchronously tackle this ambitious initiative. But what happens to a specimen in a museum before a digital model of that specimen is published on the internet? Here we provide a window into some of the steps involved in this process and focus on what is involved in scanning specimens of fishes. more »« less
Bentley, Ian; Ralston, Joel; Garman, Satin D.; Hershberger, Olivia; Probst, Charlotte M.; Washer, Campbell
(, IEEE)
Vuong, Son; Bradford, Phillip; Rajashree, Paul
(Ed.)
Phenotypic analysis from digital photographs is a useful tool in bioinformatics, and it has become increasingly important in the study of museum specimens as more natural history museum archives are digitized. However, steep learning curves and high costs associated with currently available image analysis software limits archive use by undergraduates, K-12 students, researchers at smaller educational institutions, and citizen scientists. We have created the Scientific Image Analysis (SIA) application to overcome these limitations with software that is freely available to any user and has an intuitive interface. SIA includes tools to measure length, angle, color and area from digital photographs, and includes tools to correct for color biases and skew from the perspective of the photograph. In this short paper we test these tools and their repeatability by measuring 497 avian museum specimens. We have quantified variation in bill length, angle of curvature of the bill, and plumage color. We find that measurements from SIA tools were highly repeatable across measurers, across replicate photographs of the same specimen, and were robust to user choices within SIA tools. Index Terms—bioinformatics, color correction, graphical output, image analysis, morphometrics, museum specimens
Islam, Sharif; Beach, James; Ellwood, Elizabeth R; Fortes, Jose; Lannom, Larry; Nelson, Gil; Plale, Beth
(, Research Ideas and Outcomes)
In the first decades of the 21stcentury, there has been a global trend towards digitisation and the mobilisation of data from natural history museums and research institutions. The development of national and international aggregator systems, which focused on data standards, made it possible to access millions of museum specimen records. These records serve as an empirical foundation for research across various fields. In addition, community efforts have expanded the concept of natural history collection specimens to include physical preparations and digital resources, resulting in the Digital Extended Specimen (DES), which also includes derived and related data. Within this context, the paper proposes using the FAIR Digital Object (FDO) framework to accelerate the global vision of the DES, arguing that FDO-enabled infrastructures can reduce barriers to the discovery and access of specimens, help ensure credit back to contributors and increase the amount of research that incorporates biodiversity data.
Cobb, Neil S.; Gall, Lawrence F.; Zaspel, Jennifer M.; Dowdy, Nicolas J.; McCabe, Lindsie M.; Kawahara, Akito Y.
(, PeerJ)
Over 300 million arthropod specimens are housed in North American natural history collections. These collections represent a “vast hidden treasure trove” of biodiversity −95% of the specimen label data have yet to be transcribed for research, and less than 2% of the specimens have been imaged. Specimen labels contain crucial information to determine species distributions over time and are essential for understanding patterns of ecology and evolution, which will help assess the growing biodiversity crisis driven by global change impacts. Specimen images offer indispensable insight and data for analyses of traits, and ecological and phylogenetic patterns of biodiversity. Here, we review North American arthropod collections using two key metrics, specimen holdings and digitization efforts, to assess the potential for collections to provide needed biodiversity data. We include data from 223 arthropod collections in North America, with an emphasis on the United States. Our specific findings are as follows: (1) The majority of North American natural history collections (88%) and specimens (89%) are located in the United States. Canada has comparable holdings to the United States relative to its estimated biodiversity. Mexico has made the furthest progress in terms of digitization, but its specimen holdings should be increased to reflect the estimated higher Mexican arthropod diversity. The proportion of North American collections that has been digitized, and the number of digital records available per species, are both much lower for arthropods when compared to chordates and plants. (2) The National Science Foundation’s decade-long ADBC program (Advancing Digitization of Biological Collections) has been transformational in promoting arthropod digitization. However, even if this program became permanent, at current rates, by the year 2050 only 38% of the existing arthropod specimens would be digitized, and less than 1% would have associated digital images. (3) The number of specimens in collections has increased by approximately 1% per year over the past 30 years. We propose that this rate of increase is insufficient to provide enough data to address biodiversity research needs, and that arthropod collections should aim to triple their rate of new specimen acquisition. (4) The collections we surveyed in the United States vary broadly in a number of indicators. Collectively, there is depth and breadth, with smaller collections providing regional depth and larger collections providing greater global coverage. (5) Increased coordination across museums is needed for digitization efforts to target taxa for research and conservation goals and address long-term data needs. Two key recommendations emerge: collections should significantly increase both their specimen holdings and their digitization efforts to empower continental and global biodiversity data pipelines, and stimulate downstream research.
Hedrick, Brandon P; Heberling, J Mason; Meineke, Emily K; Turner, Kathryn G; Grassa, Christopher J; Park, Daniel S; Kennedy, Jonathan; Clarke, Julia A; Cook, Joseph A; Blackburn, David C; et al
(, BioScience)
Abstract Natural history collections (NHCs) are the foundation of historical baselines for assessing anthropogenic impacts on biodiversity. Along these lines, the online mobilization of specimens via digitization—the conversion of specimen data into accessible digital content—has greatly expanded the use of NHC collections across a diversity of disciplines. We broaden the current vision of digitization (Digitization 1.0)—whereby specimens are digitized within NHCs—to include new approaches that rely on digitized products rather than the physical specimen (Digitization 2.0). Digitization 2.0 builds on the data, workflows, and infrastructure produced by Digitization 1.0 to create digital-only workflows that facilitate digitization, curation, and data links, thus returning value to physical specimens by creating new layers of annotation, empowering a global community, and developing automated approaches to advance biodiversity discovery and conservation. These efforts will transform large-scale biodiversity assessments to address fundamental questions including those pertaining to critical issues of global change.
Kates, Heather R.; Doby, Joshua R.; Siniscalchi, Carol M.; LaFrance, Raphael; Soltis, Douglas E.; Soltis, Pamela S.; Guralnick, Robert P.; Folk, Ryan A.
(, Frontiers in Plant Science)
Phylogenetic datasets are now commonly generated using short-read sequencing technologies unhampered by degraded DNA, such as that often extracted from herbarium specimens. The compatibility of these methods with herbarium specimens has precipitated an increase in broad sampling of herbarium specimens for inclusion in phylogenetic studies. Understanding which sample characteristics are predictive of sequencing success can guide researchers in the selection of tissues and specimens most likely to yield good results. Multiple recent studies have considered the relationship between sample characteristics and DNA yield and sequence capture success. Here we report an analysis of the relationship between sample characteristics and sequencing success for nearly 8,000 herbarium specimens. This study, the largest of its kind, is also the first to include a measure of specimen quality (“greenness”) as a predictor of DNA sequencing success. We found that taxonomic group and source herbarium are strong predictors of both DNA yield and sequencing success and that the most important specimen characteristics for predicting success differ for DNA yield and sequencing: greenness was the strongest predictor of DNA yield, and age was the strongest predictor of proportion-on-target reads recovered. Surprisingly, the relationship between age and proportion-on-target reads is the inverse of expectations; older specimens performed slightly better in our capture-based protocols. We also found that DNA yield itself is not a strong predictor of sequencing success. Most literature on DNA sequencing from herbarium specimens considers specimen selection for optimal DNA extraction success, which we find to be an inappropriate metric for predicting success using next-generation sequencing technologies.
Luparell, Jennifer L., Summers, Adam P., and Buser, Thaddaeus J. Digitizing North American Fishes. Retrieved from https://par.nsf.gov/biblio/10188581. American currents Summer 2019.
Luparell, Jennifer L., Summers, Adam P., & Buser, Thaddaeus J. Digitizing North American Fishes. American currents, Summer 2019 (). Retrieved from https://par.nsf.gov/biblio/10188581.
Luparell, Jennifer L., Summers, Adam P., and Buser, Thaddaeus J.
"Digitizing North American Fishes". American currents Summer 2019 (). Country unknown/Code not available. https://par.nsf.gov/biblio/10188581.
@article{osti_10188581,
place = {Country unknown/Code not available},
title = {Digitizing North American Fishes},
url = {https://par.nsf.gov/biblio/10188581},
abstractNote = {In the past decade, the ability to construct digital models of natural history specimens has become faster, cheaper, and easier for researchers. This in part has led to the modern movement to cre- ate models of representatives of all vertebrate species and make these data freely available to other researchers and the general public. The openVertebrate project (or “oVert”) is leading this charge by using micro computed tomographic (μCT) scanners at universities across the United States to synchronously tackle this ambitious initiative. But what happens to a specimen in a museum before a digital model of that specimen is published on the internet? Here we provide a window into some of the steps involved in this process and focus on what is involved in scanning specimens of fishes.},
journal = {American currents},
volume = {Summer 2019},
author = {Luparell, Jennifer L. and Summers, Adam P. and Buser, Thaddaeus J.},
}
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