Phenology is a key biological trait that can determine an organism's survival and provides one of the clearest indicators of the effects of recent climatic change. Long time-series observations of plant phenology collected at continental scales could clarify latitudinal and regional patterns of plant responses and illuminate drivers of that variation, but few such datasets exist. Here, we use the web tool CrowdCurio to crowdsource phenological data from over 7000 herbarium specimens representing 30 diverse flowering plant species distributed across the eastern United States. Our results, spanning 120 years and generated from over 2000 crowdsourcers, illustrate numerous aspects of continental-scale plant reproductive phenology. First, they support prior studies that found plant reproductive phenology significantly advances in response to warming, especially for early-flowering species. Second, they reveal that fruiting in populations from warmer, lower latitudes is significantly more phenologically sensitive to temperature than that for populations from colder, higher-latitude regions. Last, we found that variation in phenological sensitivities to climate within species between regions was of similar magnitude to variation between species. Overall, our results suggest that phenological responses to anthropogenic climate change will be heterogeneous within communities and across regions, with large amounts of regional variability driven by local adaptation, phenotypic plasticity and differences in species assemblages. As millions of imaged herbarium specimens become available online, they will play an increasingly critical role in revealing large-scale patterns within assemblages and across continents that ultimately can improve forecasts of the impacts of climatic change on the structure and function of ecosystems.
This article is part of the theme issue ‘Biological collections for understanding biodiversity in the Anthropocene’.
The billions of specimens housed in natural science collections provide a tremendous source of under-utilized data that are useful for scientific research, conservation, commerce, and education. Digitization and mobilization of specimen data and images promises to greatly accelerate their utilization. While digitization of natural science collection specimens has been occurring for decades, the vast majority of specimens remain un-digitized. If the digitization task is to be completed in the near future, innovative, high-throughput approaches are needed. To create a dataset for the study of global change in New England, we designed and implemented an industrial-scale, conveyor-based digitization workflow for herbarium specimen sheets. The workflow is a variation of an object-to-image-to-data workflow that prioritizes imaging and the capture of storage container-level data. The workflow utilizes a novel conveyor system developed specifically for the task of imaging flattened herbarium specimens. Using our workflow, we imaged and transcribed specimen-level data for almost 350,000 specimens over a 131-week period; an additional 56 weeks was required for storage container-level data capture. Our project has demonstrated that it is possible to capture both an image of a specimen and a core database record in 35 seconds per herbarium sheet (for intervals between images of 30 minutes or less) plus some additional overhead for container-level data capture. This rate was in line with the pre-project expectations for our approach. Our throughput rates are comparable with some other similar, high-throughput approaches focused on digitizing herbarium sheets and is as much as three times faster than rates achieved with more conventional non-automated approaches used during the project. We report on challenges encountered during development and use of our system and discuss ways in which our workflow could be improved. The conveyor apparatus software, database schema, configuration files, hardware list, and conveyor schematics are available for download on GitHub.