Digitization TCN: Collaborative: Capturing California's Flowers: using digital images to investigate historical and geographic phenological change in a biodiversity hotspot

Award Period
Award Amount
Agency Name
National Science Foundation
Award Number
PI First Name
PI Last Name
Katja Seltmann
MSI People
Area/s of Research
Marine Conservation, Policy and Education

The digitization of herbarium specimens has advanced our ability to understand complex and changing biological systems. However, when digital records provide only taxon names, dates, and locations, the types of research questions that can be addressed with these records are limited. While basic data such as these can be used to detect changes in species distributions, herbarium specimens are rich in additional information regarding plant health, reproductive condition, and morphology that is generally not captured in digitization workflows. Flowering time, in particular, is a character that has cascading effects on multiple levels of biological organization from individuals to ecosystems. Here, 22 herbaria propose to capture the currently untapped research potential contained in California specimens through a massive imaging effort of the California flora. This endeavor will image, database, georeference, and score phenological traits on ~900,000 specimens at 22 collaborating institutions with significant California holdings. The target specimens include the oldest specimens (pre-1930) to establish a phenological baseline before the most recent onset of climate change, as well as the most diverse vascular plant families in California to understand the evolution of phenological shifts. The target taxa also include species currently monitored by the USA National Phenology Network (USA-NPN) and the California Phenology Project (CPP), making the data immediately applicable for current-day research. Data standards for scoring phenology on herbarium specimens are currently lacking. This project will collaborate with iDigBio and TDWG to create community-wide data standards for phenological traits, integrate those traits into the Darwin Core, and develop the training tools necessary for phenological digitization to be included in all future digitization workflows.