Digitization and the Future of Natural History Collections

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.

Anthropologically introduced biases in natural history collections, with a case study on the invertebrate paleontology collections from the middle Cambrian Spence Shale Lagerstätte

“…Natural history collections (NHCs) are undergoing a transformative role within science during the twenty-first century. More so than ever, the specimens they contain are being applied to "big data" interdisciplinary problems such as disease control, the global biodiversity and ecological crises, and mitigation and measurement of the effects of global warming (Suarez and Tsutsui, 2004;Winker, 2004;Baird, 2010;Pyke and Ehrlich, 2010;Bakker et al, 2020;Hedrick et al, 2020). New technological applications and methodologies, such as genomics, computational statistics, CT scanning, and machine learning are bringing renewed interest and application to historic collections, decades or even centuries after they have been established (Wandeler et al, 2007;Nelson and Ellis, 2018).…”

A New Method for Counting Reproductive Structures in Digitized Herbarium Specimens Using Mask R-CNN

“…A key functional trait in this regard is phenology: the timing of life-history events, such as the onset of flowering or migration. The use of museum specimens has invigorated and enriched the investigation of phenological responses to climatic change, and is one of several research directions that has brought a renewed sense of purpose and timeliness to natural history collections (Davis et al, 2015;Willis et al, 2017;Meineke et al, 2018;Meineke et al, 2019;Hedrick et al, 2020). Herbarium specimens greatly expand the historical depth, spatial scale, and species diversity of phenological observations relative to those available from field observations (Wolkovich et al, 2014).…”

“…The ongoing digitization and online mobilization of herbarium specimens has facilitated their broad access with significant economies of scale (Sweeney et al, 2018;Nelson and Ellis, 2019;Hedrick et al, 2020) and accelerated advances in scientific investigations, including phenological assessment efforts that were underway prior to mass digitization (Primack et al, 2004;Miller-Rushing et al, 2006;Davis et al, 2015). A new vision of digitization, Digitization 2.0 (sensu Hedrick et al, 2020), has also sparked the integration and development of new scholarly disciplines and lines of inquiry not possible previously. Whereas Digitization 1.0 refers to the generation of digitized products from physical specimens, Digitization 2.0 is the use of natural history collections to answer scientific questions using only their digitized representation, rather than the physical specimen itself.…”

“…In recent years, scientists have used these digitized herbarium specimens in novel ways (e.g., Meineke et al, 2018;Meineke et al, 2019;Hedrick et al, 2020) and greatly increased the pace at which key phenological trait data can be harvested from tens of thousands of specimens. The platform CrowdCurio-Thoreau's Field Notes (Willis et al, 2017) was one of the first attempts to move beyond the standard practice of coding phenology of herbarium specimens using binary (presence/absence) coding (e.g., specimen A has flowers, specimen B has fruits: Primack et al, 2004;Miller-Rushing et al, 2006).…”

Predicting amphibian intraspecific diversity with machine learning: Challenges and prospects for integrating traits, geography, and genetic data

“…Solving this challenge will require collaborative efforts by the research community to standardize trait information, contribute to trait datasets, and make these datasets easily available (e.g., Oliveira et al, 2017). In the future, increasing efforts to digitize natural history collections and develop informatics tools will ultimately enable the incorporation of individual and population-level trait variation into these types of studies (Guralnick et al, 2016; Hedrick et al, 2020). The second major challenge to extending the scope of this study is the limited amount of georeferenced genetic data available for most species.…”