2022 ESA Annual Meeting (August 14 - 19)

SYMP 13 Methods for occurrence data from natural history collections and community science data

3:30 PM-5:00 PM
520F
Organizer:
Laura M. Guzman, n/a
Co-organizer:
Vaughn Shirey, Rassim Khelifa
Moderator:
Rassim Khelifa
Species’ occurrence data is becoming more widely available through digitization of museum collections (Hedrick et al., 2020) and citizen science platforms (Dickinson et al., 2012) At the time of writing, the Global Biodiversity Information Facility (GBIF) and Integrated Digitized Biocollections (iDigBio) contain over 1.5-billion records of species occurrences across the planet. Occurrence data is rich with metadata that includes a species name, location, date of collection, and sometimes even photographs of specimens or individuals. The richness of this data allows us to ask questions about changes in biodiversity through time, particularly in taxonomic groups that have not been consistently monitored.The use of occurrence data from museum collections is becoming more common in ecological analyses over the last several years. Importantly, however, improper treatment of these data can lead to misleading inferences (Guzman et al. 2021, Larsen et al. 2021). In this symposium we will present recent advances in methodological approaches that allow us to leverage digitized museum collections. Specifically, we will address how to make inferences about changes in species distributions using occurrence data (Laura Melissa Guzman), how these inferences can be linked to changes in climate (Vaughn Shirey), how we can infer phenology and changes in phenology through time (Michael Belitz), and how we can integrate multiple data sources, such as structured diversity surveys and occurrence data, to make inferences about populations through time (Courtney Davis). Together we tackle methods that ecologists want to use to answer questions about how biodiversity has changed in the anthropocene. References: Hedrick, B. P., J. M. Heberling, E. K. Meineke, K. G. Turner, C. J. Grassa, D. S. Park,J. Kennedy, J. A. Clarke, J. A. Cook, D. C. Blackburn, et al., 2020. Digitization and thefuture of natural history collections. BioScience 70:243–251.Dickinson, J. L., J. Shirk, D. Bonter, R. Bonney, R. L. Crain, J. Martin, T. Phillips, andK. Purcell, 2012. The current state of citizen science as a tool for ecological researchand public engagement. Frontiers in Ecology and the Environment 10:291–297.Guzman, L. M., S. A. Johnson, A. O. Mooers, and L. K. M’Gonigle, 2021. Using historicaldata to estimate bumble bee occurrence: Variable trends across species provide littlesupport for community-level declines. Biological Conservation 257:109141Larsen, E. A. and V. Shirey, 2021. Method matters: pitfalls in analysing phenology fromoccurrence records. Ecol. Lett. P. Early View.
3:30 PM
Using historical data to estimate changes in species occurrences
Laura M. Guzman, n/a, University of Southern California;Vaughn Shirey, Georgetown University;Leithen K. M'Gonigle, PhD, Simon Fraser University;Rassim Khelifa, Concordia University;
3:50 PM
Utilizing occupancy-detection models with opportunistic data to detect climate-driven changes in communities
Vaughn Shirey, Georgetown University;Naresh Neupane, Georgetown University;Leslie Ries, Georgetown University;
4:10 PM
Phenological research based on natural history collections: practical guidelines and a Lepidopteran case study
Michael W. Belitz, Florida Museum of Natural History;Elise A. Larsen, Georgetown University;Vaughn Shirey, Georgetown University;Daijiang Li, Louisiana State University;Robert P. Guralnick, Florida Museum of Natural History;
4:30 PM
CANCELLED - Data Integration Methods For Estimating Long-Term Population Trends Using Opportunistic Data
Courtney L. Davis, Cornell University;Robert P. Guralnick, Florida Museum of Natural History;Elise Zipkin, Michigan State University;
4:50 PM