CrowdCurio: an online crowdsourcing platform to facilitate climate change studies using herbarium specimens

Abstract

Phenology is a key aspect of plant success. Recent research has demonstrated that herbarium specimens can provide important information on plant phenology. Massive digitization efforts have the potential to greatly expand herbarium-based phenological research, but also pose a serious challenge regarding efficient data collection. Here, we introduce CrowdCurio, a crowdsourcing tool for the collection of phenological data from herbarium specimens. We test its utility by having workers collect phenological data (number of flower buds, open flowers and fruits) from specimens of two common New England (USA) species: Chelidonium majus and Vaccinium angustifolium. We assess the reliability of using nonexpert workers (i.e. Amazon Mechanical Turk) against expert workers. We also use these data to estimate the phenological sensitivity to temperature for both species across multiple phenophases. We found no difference in the data quality of nonexperts and experts. Nonexperts, however, were a more efficient way of collecting more data at lower cost. We also found that phenological sensitivity varied across both species and phenophases. Our study demonstrates the utility of CrowdCurio as a crowdsourcing tool for the collection of phenological data from herbarium specimens. Furthermore, our results highlight the insight gained from collecting large amounts of phenological data to estimate multiple phenophases.

The unrealized potential of herbaria for global change biology

“…Recent collaborations between biologists and computer scientists present new opportunities (Willis et al. ) and have allowed for the development of crowdsourcing image annotation tools (e.g., CrowdCurio, available online ) to extract phenological data from digitized herbarium specimens . These tools are already being adopted and have enormous power for leveraging herbarium data for climate change research, and preliminary studies suggest they can generate highly usable data (Williams et al.…”

Testing the potential of Twitter mining methods for data acquisition: Evaluating novel opportunities for ecological research in multiple taxa

“…Hart, Hesselberg, Nesbit, & Goodenough, 2017). There are some challenges with using citizen science data (Lukyanenko, Parsons, & Wiersma, 2016) including the fact that: (1) data often cannot be validated; (2) data on rare species or complex ecological phenomena can be hard to obtain; (3) data can be of lower quality and consistency than those collected by experts (but see Willis et al, 2017); and (4) recording frequency can be biased towards highly populated areas or times such as weekends and holidays. Despite these issues, large datasets can be assembled across larger spatial scales and longer time periods than would otherwise be possible.…”

Phenology models using herbarium specimens are only slightly improved by using finer‐scale stages of reproduction

“…Some herbarium studies have used fine‐scale divisions to assess the complexity of climatic effects on phenological events; for example, in a study of Rubus L. species in which flowering and fruiting phenology were each divided into two stages, three of the four stages were found to be correlated with temperature (Diskin et al., ). In another study of a temperate shrub and a wildflower species in which flowering and fruiting were each divided into two stages, first flowering/fruit‐set and peak flowering/fruit‐set, correlations of phenology with temperature varied in strength and significance across stages (Willis et al., ).…”